U.S. patent application number 13/896389 was filed with the patent office on 2014-04-10 for analyzing microseismic data from a fracture treatment.
The applicant listed for this patent is Avi Lin, Jianfu Ma, Harold Grayson Walters. Invention is credited to Avi Lin, Jianfu Ma, Harold Grayson Walters.
Application Number | 20140100786 13/896389 |
Document ID | / |
Family ID | 50432561 |
Filed Date | 2014-04-10 |
United States Patent
Application |
20140100786 |
Kind Code |
A1 |
Ma; Jianfu ; et al. |
April 10, 2014 |
Analyzing Microseismic Data from a Fracture Treatment
Abstract
Systems, methods, and software can be used to analyze
microseismic data from a fracture treatment. In some aspects, data
for a new microseismic event are from a fracture treatment of a
subterranean zone. An updated parameter for a fracture plane is
calculated. The fracture plane was previously generated based on
data for prior microseismic events. The updated parameter
calculated is calculated based on the data for the new microseismic
event and the data for the prior microseismic events. A graphical
representation of the fracture plane is displayed based on the
updated parameter.
Inventors: |
Ma; Jianfu; (Sugar Land,
TX) ; Lin; Avi; (Houston, TX) ; Walters;
Harold Grayson; (Tomball, TX) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Ma; Jianfu
Lin; Avi
Walters; Harold Grayson |
Sugar Land
Houston
Tomball |
TX
TX
TX |
US
US
US |
|
|
Family ID: |
50432561 |
Appl. No.: |
13/896389 |
Filed: |
May 17, 2013 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
61710582 |
Oct 5, 2012 |
|
|
|
Current U.S.
Class: |
702/16 |
Current CPC
Class: |
G01V 1/301 20130101;
G01V 1/40 20130101; G01V 1/345 20130101; G01V 1/34 20130101; G01V
2210/1234 20130101; G01V 1/288 20130101; G01V 2210/646
20130101 |
Class at
Publication: |
702/16 |
International
Class: |
G01V 1/34 20060101
G01V001/34 |
Claims
1. A computer-implemented method for analyzing microseismic data
from a fracture treatment, the method comprising: receiving data
for a new microseismic event associated with a fracture treatment
of a subterranean zone; calculating, by data processing apparatus,
an updated parameter for a fracture plane, the fracture plane being
previously-generated based on data for prior microseismic events,
the updated parameter calculated based on the data for the new
microseismic event and the data for the prior microseismic events;
and displaying a graphical representation of the fracture plane
based on the updated parameter.
2. The method of claim 1, wherein the updated parameter is
calculated and the graphical representation is displayed in real
time during the fracture treatment.
3. The method of claim 1, further comprising: selecting the
fracture plane, from a plurality of fracture planes, based on the
data for the new microseismic event; and associating the new
microseismic event with the selected fracture plane.
4. The method of claim 3, wherein displaying a graphical
representation of the fracture plane includes updating a graphical
representation of the plurality of fracture planes in real time
during the fracture treatment.
5. The method of claim 3, wherein selecting the fracture plane from
a plurality of fracture planes includes: determining a distance
between the new microseismic event and the facture plane; and
determining that the distance is less than a threshold
distance.
6. The method of claim 5, further comprising computing the
threshold distance by multiplying a predefined coefficient by the
standard deviation of the microseismic events associated with the
fracture plane.
7. The method of claim 1, wherein calculating an updated parameter
for the fracture plane includes calculating at least one of an
updated orientation or an updated area for the fracture plane based
on the data for the new microseismic event and the data for the
prior microseismic events.
8. The method of claim 1, wherein calculating an updated parameter
for the fracture plane includes calculating an average distance
from the fracture plane for the new microseismic event and the
prior microseismic events.
9. The method of claim 8, wherein the new microseismic event and
the prior microseismic events define a set, and the method further
comprises: detecting that the average distance is greater than a
predefined threshold distance; and calculating an updated average
distance after removing one or more microseismic events from the
set.
10. The method of claim 1, wherein calculating an updated parameter
for the fracture plane includes calculating an updated area for the
fracture plane, and the method further comprises: comparing the
updated area for the fracture plane to a prior area for the
fracture plane; and disassociating the new microseismic event from
the fracture plane if the updated area for the fracture plane is
less than the prior area for the fracture plane.
11. The method of claim 1, further comprising: identifying one or
more microseismic events that are farther than a threshold distance
from the fracture plane; and disassociating the identified
microseismic events from the fracture plane.
12. The method of claim 1, wherein the new microseismic event
comprises a first new microseismic event, the method further
comprising: after displaying the graphical representation based on
the first new microseismic event, receiving data for a second new
microseismic event from the fracture treatment; calculating a
second updated parameter for the fracture plane based in part on
the data for the second new microseismic event; and displaying a
graphical representation of the fracture plane based on the second
updated parameter.
13. A non-transitory computer-readable medium encoded with
instructions that, when executed by data processing apparatus,
perform operations comprising: receiving data for a new
microseismic event associated with a fracture treatment of a
subterranean zone; calculating an updated parameter for a fracture
plane, the fracture plane being previously generated based on data
for prior microseismic events, the updated parameter calculated
based on the data for the new microseismic event and the data for
the prior microseismic events; and generating a graphical
representation of the fracture plane based on the updated
parameter.
14. The computer-readable medium of claim 13, wherein the updated
parameter is calculated and the graphical representation is
generated in real time during the fracture treatment.
15. The computer-readable medium of claim 13, the operations
further comprising: selecting the fracture plane, from a plurality
of fracture planes, based on the data for the new microseismic
event; and associating the new microseismic event with the selected
fracture plane.
16. The computer-readable medium of claim 13, wherein calculating
an updated parameter for the fracture plane includes calculating at
least one of an updated orientation or an updated area for the
fracture plane based on the data for the new microseismic event and
the data for the prior microseismic events.
17. The computer-readable medium of claim 13, wherein calculating
an updated parameter for the fracture plane includes calculating an
average distance from the fracture plane for the new microseismic
event and the prior microseismic events.
18. A system comprising: data processing apparatus operable to:
receive data for a new microseismic event associated with a
fracture treatment of a subterranean zone; and calculate an updated
parameter for a fracture plane, the fracture plane being previously
generated based on data for prior microseismic events, the updated
parameter calculated based on the data for the new microseismic
event and the data for the prior microseismic events; and a display
device operable to display a graphical representation of the
fracture plane based on the updated parameter.
19. The system of claim 18, further comprising a communication
interface operable to receive microseismic event data from one or
more sensors associated with the subterranean zone.
20. The system of claim 18, wherein the updated parameter is
calculated and the graphical representation is displayed in real
time during the fracture treatment.
21. The system of claim 18, wherein the data processing apparatus
is further operable to: select the fracture plane, from a plurality
of fracture planes, based on the data for the new microseismic
event; and associate the new microseismic event with the selected
fracture plane.
22. The system of claim 18, wherein calculating an updated
parameter for the fracture plane includes calculating at least one
of an updated orientation or an updated area for the fracture plane
based on the data for the new microseismic event and the data for
the prior microseismic events.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application claims priority to U.S. Provisional
Application Ser. No. 61/710,582, entitled "Identifying Dominant
Fracture Orientations," filed on Oct. 5, 2012.
BACKGROUND
[0002] This specification relates to analyzing microseismic data
from a fracture treatment. Microseismic data are often acquired in
association with hydraulic fracturing treatments applied to a
subterranean formation. The hydraulic fracturing treatments are
typically applied to induce artificial fractures in the
subterranean formation, and to thereby enhance hydrocarbon
productivity of the subterranean formation. The pressures generated
by the fracture treatment can induce low-amplitude or low-energy
seismic events in the subterranean formation, and the events can be
detected by sensors and collected for analysis.
SUMMARY
[0003] In one general aspect, microseismic data from a fracture
treatment are analyzed. In some instances, the data may be analyzed
in real time, for example, during the fracture treatment.
[0004] In some aspects, data for a new microseismic event are
collected from a fracture treatment of a subterranean zone. An
updated parameter for a fracture plane is calculated. The fracture
plane was previously generated based on data for prior microseismic
events. The updated parameter calculated is calculated based on the
data for the new microseismic event and the data for the prior
available microseismic events. A graphical representation of the
fracture plane (or a numerical representation of the fracture plane
parameters) is displayed based on the updated parameter.
[0005] Implementations may include one or more of the following
features. Prior knowledge or estimates of possible fracture planes
orientations is used to calculate a fracture plane parameter. The
graphical representation are continuously updated, for example, as
long as additional new microseismic events appear in the system
input buffer. New microseismic events are collected from the
fracture treatment before the fracture treatment begins, during the
fracture treatment, after the fracture treatment has terminated, or
any combination of these. The updated parameter is calculated and
the graphical representation is displayed in real time during the
fracture treatment. The fracture plane is selected from multiple
fracture planes based on the data for the new microseismic event.
The new microseismic event is associated with the selected fracture
plane. Displaying a graphical representation of the fracture plane
includes updating a graphical representation of the fracture planes
in real time during the fracture treatment. Selecting the fracture
plane from the fracture planes includes identifying a distance
between the new microseismic event and the selected facture plane
and determining that the distance is less than a threshold
distance. The threshold value is a static predefined value. The
predefined threshold is computed by multiplying a coefficient and
the standard deviation or uncertainty of the fracture plane. The
coefficient can be a predefined constant value, for example,
between 1 and 2, or another value.
[0006] Additionally or alternatively, these and other
implementations may include one or more of the following features.
Calculating an updated parameter for the fracture plane includes
calculating at least one of an updated orientation or an updated
area for the fracture plane based on the data for the new
microseismic event and the data for the prior microseismic events.
Calculating an updated parameter for the fracture plane includes
calculating an average distance from the fracture plane for the new
microseismic event and the prior microseismic events. The new
microseismic event and the prior microseismic events define a set.
In response to detecting that the average distance is greater than
a predefined threshold distance, an updated average distance is
calculated after removing one or more microseismic events from the
set.
[0007] Additionally or alternatively, these and other
implementations may include one or more of the following features.
Calculating an updated parameter for the fracture plane includes
calculating an updated area for the fracture plane. The updated
area for the fracture plane is compared to a prior area for the
fracture plane. The new microseismic event is disassociated from
the fracture plane if the updated area for the fracture plane is
less than the prior area for the fracture plane. The new
microseismic event is a first new microseismic event. After
displaying the graphical representation based on the first new
microseismic event, data for a second new microseismic event
collected from the fracture treatment is received. A second updated
parameter is calculated for the fracture plane based in part on the
data for the second new microseismic event. An updated graphical
representation of the fracture plane is generated based on the
second updated parameter.
[0008] The details of one or more implementations are set forth in
the accompanying drawings and the description below. Other
features, objects, and advantages will be apparent from the
description and drawings, and from the claims.
DESCRIPTION OF DRAWINGS
[0009] FIG. 1A is a diagram of an example well system; FIG. 1B is a
diagram of the example computing subsystem 110 of FIG. 1A.
[0010] FIGS. 2A and 2B are plots showing example fracture
planes.
[0011] FIGS. 3A-3F are plots showing updates for an example
fracture plane.
[0012] FIG. 4 is a flow chart of an example technique for analyzing
microseismic data.
[0013] Like reference symbols in the various drawings indicate like
elements.
DETAILED DESCRIPTION
[0014] In some aspects of what is described here, fracture
parameters, dominant fracture orientations, or other data are
identified from microseismic data. In some instances, these or
other types of data are dynamically identified, for example, in a
real-time fashion during a fracture treatment. For many
applications and analysis techniques, an identification of fracture
planes from real-time microseismic events is needed, and individual
fracture planes can be displayed to show time evolution and
geometric elimination, including location, propagation, growth,
reduction, or elimination of the fracture planes. Such capabilities
can be incorporated into control systems, software, hardware, or
other types of tools available to oil and gas field engineers when
they analyze potential oil and gas fields, while stimulating
hydraulic fractures and analyzing the resultant signals. Such tools
can provide a reliable and direct interface for presenting and
visualizing the dynamics of hydraulic fractures, which may assist
in analyzing the fracture complexity, fracture network structure,
and reservoir geometry. Such tools can assist in evaluating the
effectiveness of hydraulic fracturing treatment, for example, by
improving, enhancing, or optimizing the fracture density and trace
lengths and heights. Such improvements in the fracture treatment
applied to the reservoir may enhance production of hydrocarbons or
other resources from the reservoir.
[0015] Hydraulic fracture treatments can be applied in any suitable
subterranean zone. Hydraulic fracture treatments are often applied
in tight formations with low-permeability reservoirs, which may
include, for example, low-permeability conventional oil and gas
reservoirs, continuous basin-centered resource plays and shale gas
reservoirs, or other types of formations. Hydraulic fracturing can
induce artificial fractures in the subsurface, which can enhance
the hydrocarbon productivity of a reservoir.
[0016] During the application of a hydraulic fracture treatment,
the injection of high-pressure fluids can alter stresses,
accumulate shear stresses, and cause other effects within the
geological subsurface structures. In some instances, microseismic
events are associated with hydraulic fractures induced by the
fracturing activities. The acoustic energy or sounds associated
with rock stresses, deformations, and fracturing can be detected
and collected by sensors. In some instances, microseismic events
have low-energy (e.g., with the value of the log of the intensity
or moment magnitude of less than three), and some uncertainty or
accuracy or measurement error is associated with the event
locations. The uncertainty can be described, for example, by a
prolate spheroid, where the highest likelihood is at the spheroid
center and the lowest likelihood is at the edge.
[0017] Microseismic event mapping can be used to geometrically
locate the source point of the microseismic events based on the
detected compressional and shear waves. The detected compressional
and shear waves (e.g., p-waves and s-waves) can yield additional
information about microseismic events, including the location of
the source point, the event's location and position measurement
uncertainty, the event's occurrence time, the event's moment
magnitude, the direction of particle motion and energy emission
spectrum, and possibly others. The microseismic events can be
monitored in real time, and in some instances, the events are also
processed in real time during the fracture treatment. In some
instances, after the fracture treatment, the microseismic events
collected from the treatment are processed together as "post
data."
[0018] Processing microseismic event data collected from a fracture
treatment can include fracture matching (also called fracture
mapping). Fracture matching processes can identify fracture planes
in any zone based on microseismic events collected from the zone.
Some example computational algorithms for fracture matching utilize
microseismic event data (e.g., an event's location, an event's
location measurement uncertainty, an event's moment magnitude,
etc.) to identify individual fractures that match the collected set
of microseismic events. Some example computational algorithms can
compute statistical properties of fracture patterns. The
statistical properties may include, for example, fracture
orientation, fracture orientation trends, fracture size (e.g.,
length, height, area, etc.), fracture density, fracture complexity,
fracture network properties, etc. Some computational algorithms
account for uncertainty in the events' location by using multiple
realizations of the microseismic event locations. For example,
alternative statistical realizations associated with Monte Carlo
techniques can be used for a defined probability distribution on a
spheroid or another type of distribution.
[0019] Generally, fracture matching algorithms can operate on
real-time data, post data, or any suitable combination of these and
other types of data. Some computational algorithms for fracture
matching operate only on post data. Algorithms operating on post
data can be used when any subset or several subsets of microseismic
data to be processed has been collected from the fracture
treatment; such algorithms can access (e.g., as an initial input)
the full subset of microseismic events to be processed. In some
implementations, fracture matching algorithms can operate on
real-time data. Such algorithms may be used for real-time automatic
fracture matching during the fracture treatment. Algorithms
operating on real-time data can be used during the fracture
treatment, and such algorithms can adapt or dynamically update a
previously-identified fracture model to reflect newly-acquired
microseismic events. For example, once a microseismic event is
detected and collected from the treatment field, a real-time
automatic fracture matching algorithm may respond to this new event
by dynamically identifying and extracting fracture planes from the
already-collected microseismic events in a real-time fashion. Some
computational algorithms for fracture matching can operate on a
combination of post data and real-time data.
[0020] In some cases, fracture mapping algorithms are configured to
handle conditions that arise in real-time microseismic data
processing. For example, several types of challenges or conditions
may occur more predominantly in the real-time context. In some
instances, real-time processing techniques can be adapted to
account for (or to reduce or avoid) the lower accuracy that is
sometimes associated with fractures extracted from data sets
lacking a sufficient number of microseismic events or lacking a
sufficient number of microseismic events in certain parts of the
domain. Some real-time processing techniques can be adapted to
produce fracture data that are consistent with the fracture data
obtainable from post data processing techniques. For example, some
of the example real-time processing techniques described here have
produced results that are statistically the same, according to the
statistical hypothesis test (t test and F test), as results
produced by post data processing techniques on the same data.
[0021] In some cases, real-time processing techniques can be
adapted to readily (e.g., instantaneously, from a user's
perspective) offer the identified fracture data to users. Such
features may allow field engineers or operators to dynamically
obtain fracture geometric information and adjust fracture treatment
parameters when appropriate (e.g. to improve, enhance, optimize, or
otherwise change the treatment). In some instances, fracture planes
are dynamically extracted from microseismic data and displayed to
field engineers in real time. Real-time processing techniques can
exhibit high-speed performance. In some cases, the performance can
be enhanced by parallel computing technology, distributed computing
technology, parallel threading approaches, fast binary-search
algorithms, or a combination of these and other hardware and
software solutions that facilitate the real-time operations.
[0022] In some implementations, fracture matching technology can
directly present information about fractures planes associated with
three-dimensional microseismic events. The fracture planes
presented can represent fracture networks that exhibit multiple
orientations and activate complex fracture patterns. In some cases,
hydraulic fracture parameters are extracted from a cloud of
microseismic event data; such parameters may include, for example,
fracture orientation trends, fracture density and fracture
complexity. The fracture parameter information can be presented to
field engineers or operators, for example, in a tabular, numerical,
or graphical interface or an interface that combines tabular,
numerical, and graphical elements. The graphical interface can be
presented in real time and can exhibit the real-time dynamics of
hydraulic fractures. In some instances, this can help field
engineers analyze the fracture complexity, the fracture network and
reservoir geometry, or it can help them better understand the
hydraulic fracturing process as it progresses.
[0023] In some implementations, accuracy confidence values are used
to quantify the certainty of the fracture planes extracted from
microseismic data. The accuracy confidence values can be used to
classify the fractures into confidence levels. For example, three
confidence levels (low confidence level, medium confidence level
and high confidence level) are appropriate for some contexts, while
in other contexts a different number (e.g., two, four, five, etc.)
of confidence levels may be appropriate. A fracture plane's
accuracy confidence value can be calculated based on any
appropriate data. In some implementations, a fracture plane's
accuracy confidence value is calculated based on the microseismic
events' locations and position uncertainties, individual
microseismic events' moment magnitude, distances between individual
events and their supporting fracture plane, the number of
supporting events associated with the fracture plane, and the
weight of variation of the fracture orientation, among others.
[0024] The accuracy confidence values can be computed and the
fracture planes can be classified at any appropriate time. In some
cases, the accuracy confidence values are computed and the fracture
planes are classified in real time during the fracture treatment.
The fracture planes can be presented to the user at any appropriate
time and in any suitable format. In some instances, the fracture
planes are presented graphically in a user interface in real time
according to the accuracy confidence values, according to the
accuracy confidence levels, or according to any other type of
classification. In some instances, users can select individual
groups or individual planes (e.g., those with high confidence
levels) for viewing or analysis. The fracture planes can be
presented to the user in an algebraic format, a numerical format,
graphical format, or a combination of these and other formats.
[0025] In some implementations, microseismic events are monitored
in real time during the hydraulic fracture treatment. As the events
are monitored, they may also be processed in real time, they may be
processed later as post data, or they may be processed using a
combination of real time and post data processing. The events may
be processed by any suitable technique. In some cases, the events
are processed individually, at the time and in the order in which
they are received. For example, a system state S(M, N-1) can be
used to represent the M number of planes generated from the N-1
previous events. The new incoming N.sup.th event can trigger the
system S(M, N-1). In some cases, upon receiving the the N.sup.th
event, a histogram or distribution of orientation ranges is
generated. For example, a probability distribution histogram or the
Hough transform histogram of the degenerated planes in the strike
and dip angle domain can be generated to identify the feasible
dominant orientations imbedded in the fractures sets.
[0026] A basic plane can be generated from a subset of microseismic
events. For example, any three non-collinear points in space
mathematically define a basic plane. The basic plane defined by
three non-collinear microseismic events can be represented by the
normal vector (a, b, c). The normal vector (a, b, c) may be
computed based on the three events' positions. The basic plane's
orientation can be computed from the normal vector. For example,
the dip .theta. and the strike .phi. can be given by
.theta. = arctan a 2 + b 2 2 , .PHI. = arctan b a . ( 1 )
##EQU00001##
The dip angle .theta. of a fracture plane can represent the angle
between the fracture plane and the horizontal plane (e.g., the
xy-plane). The strike angle .phi. of a fracture plane can represent
the angle between a horizontal reference axis (e.g., the x-axis)
and a horizontal line where the fracture plane intersects the
horizontal plane. For example, the strike angle can be defined with
respect to North or another horizontal reference direction. A
fracture plane can be defined by other parameters, including
angular parameters other than the strike angle and dip angle.
[0027] In general, N events can support P basic planes, where
P=N(N-1)(N-2)/6, strike and dip angles. A probability histogram can
be constructed from the orientation angles. The probability
histogram or the enhanced Hough transformation histogram can have
any suitable configuration. For example, the histogram
configuration can be based on a fixed bin size and a fixed number
of bins, natural optimal bin size in the strike and dip angle
domain, or other types of bins. The histogram can be based on any
suitable number of microseismic events (e.g., tens, hundreds,
thousands, etc.), and any suitable range of orientations. In some
cases, multiple discrete bins are defined for the histogram, and
each bin represents a discrete range of orientations. A quantity of
basic planes in each discrete range can be computed from the basic
planes. In some cases, each basic plane's orientation falls within
the orientation range associated with one of the bins. For example,
for N microseismic events, each of the P basic planes can be
assigned to a bin, and the quantity of basic planes assigned to
each bin can be computed. The quantity computed for each bin can be
any suitable value. For example, the quantity can be a
non-normalized number of basic planes, the quantity can be a
normalized probability, frequency, or fraction of basic planes, or
the quantity can be another type of value that is suitable for a
histogram. A histogram can be generated to represent the quantity
of basic planes assigned to all of the bins, or to represent the
quantity of basic planes assigned to a subset of the bins.
[0028] In some examples, the histogram is presented as a
three-dimensional bar chart, a three-dimensional surface map, or
another suitable plot in an appropriate coordinate system. The
peaks on the histogram plot can indicate dominant fracture
orientations. For example, along one axis the histogram may
represent strike angles from 0.degree. through 360.degree. (or
another range), and the strike angles can be divided into any
suitable number of bins; along another axis the histogram may
represent dip angles from 60.degree. through 90.degree. (or another
range), and the dip angles can be divided into any suitable number
of bins. The quantity (e.g., probability) for each bin can be
represented along a third axis in the histogram. The resulting plot
can exhibit local maxima (peaks). Each local maximum (peak) can
indicate a respective strike angle and dip angle that represents a
dominant fracture orientation. For example, the local maximum of
the histogram may indicate that more basic planes are aligned along
this direction (or range of directions) than along neighboring
directions, and these basic planes are either closely parallel or
substantially on the same plane.
[0029] The orientation range represented by each bin in the
histogram can be determined by any appropriate technique. In some
cases, each bin represents a pre-determined range of orientations.
For example, the fixed bin size method can be used. In some cases,
the range or size for each bin is computed based on the data to be
represented by the histogram. For example, the natural optimal bin
size method can be used. In some instances, the basic plane
orientations are sorted, and clusters of sorted orientations are
identified. For example, all strikes can be sorted in a decreasing
or increasing order and then grouped into clusters; similarly, all
dip values can be sorted in a decreasing or increasing order and
then grouped into clusters. The clusters can be associated with
two-dimensional grid, and the number of basic planes in each grid
cell can be counted. In some cases, this technique can generate
adaptive and dynamic clusters, leading to highly accurate values
for the dominant orientations. This technique and associated
refinements can be implemented with N.sup.3log(N) computational
complexity. In some cases, the bin sizes for both the strike and
dip are fixed, and each basic plane's location grid cell can be
explicitly determined by the associated strike and dip with N.sup.3
computational complexity.
[0030] Fracture planes associated with a set of microseismic events
can be extracted from the dominant orientations embedded in the
histogram data. Basic planes that support the dominant orientation
(.theta., .phi.) may be either nearly parallel or on the same
plane. Basic planes located within the same plane can be merged
together, forming a new fracture plane with stronger support (e.g.,
representing a larger number of microseismic events). Any suitable
technique can be used to merge the fracture planes. In some cases,
for each dominant orientation (.theta., .phi.), a normal to the
plane vector is constructed with components (sin .theta. cos .phi.,
sin .theta. sin .phi., cos .theta.). In some instances, the results
are insensitive to the location of the plane, and without loss of
generality, the plane can be constructed from this normal vector
(e.g., assuming the origin is in the plane). The plane can be
described by x sin .theta. cos .phi.+y sin .theta. sin .phi.+z cos
.theta.=0. The normal signed distance of each event (x.sub.o,
y.sub.o, z.sub.o) from a basic plane to the constructed plane can
be represented d=-(x.sub.0 sin .theta. cos .phi.+y.sub.0 sin
.theta. sin .phi.+x.sub.0 cos .theta.). In this representation,
events with opposite signs of d are located opposite sides of the
plane.
[0031] In some cases, microseismic events are grouped into clusters
based on their distance from the constructed fracture planes. For
example, a cluster of events can contain the group of events
closest to a constructed fracture plane. As such, each cluster of
microseismic events can support a particular fracture plane. The
cluster size refers to the number of the events the cluster
contains. In some cases, user input or other program data can
designate a minimum number of events in a sustained cluster. The
minimum cluster size can depend on the number of microseismic
events in the data. In some instances, the minimum cluster size
should be larger than or equal three. For example, clusters having
a size larger than or equal to the minimum cluster size can be
considered legitimate fracture planes. A fitting algorithm can be
applied to the location and location uncertainty values for the
events in each cluster to find their corresponding fracture
plane.
[0032] Any suitable technique can be used to identify a fracture
plane from a set of microseismic events. In some cases, a
Chi-square fitting technique is used. Given K observed microseismic
events, the locations can be represented (x.sub.i, y.sub.i,
z.sub.i), and their measurement uncertainties can be represented
.sigma..sub.i,x, .sigma..sub.i,y, .sigma..sub.i,z), where
1.ltoreq.i.ltoreq.K. The parameters of the plane model z=ax+by+c
can be calculated, for example, by minimizing the Chi-square merit
function
.chi. 2 ( a , b , c ) = i = 1 K ( z i - ax i - by i - c ) 2 .sigma.
i , z 2 + a 2 .sigma. i , x 2 + b 2 .sigma. i , y 2 ( 2 )
##EQU00002##
The Chi-square merit function can be solved by any suitable
technique. In some instances, a solution can be obtained by solving
three equations, which are the partial derivatives of .chi..sup.2
(a, b, c) with respect to its variables, where each partial
derivative is forced to zero. In some instances, there is no
analytical solution for this nonlinear mathematical system of
equations. Numerical methods (e.g., Newton's numerical method, the
Newton Rafson method, the conjugate gradient method, or another
technique) can be applied to solve for the parameters a, b and c,
and the strike and dip angles can be computed (e.g., using equation
(1) above). The orientation of the dominant fracture plane computed
from the microseismic events can be the same as, or it can be
slightly different from, the dominant fracture orientation
identified from the histogram.
[0033] In some implementations, an algorithm iterates over all
possible dominant orientations to expand all feasible fracture
planes. In some cases, the algorithm iterates over a selected
subset of possible dominant orientations. The iterations can
converge to planes. Some planes may be exactly equal to each other
and some may be close to each other. Two planes can be considered
"close" to each other, for example, when the average distance of
one plane's events from another plane is less than a given
threshold. The threshold distance can be designated, for example,
as a control parameter. The algorithm can merge close planes
together and the support events of one plane can be associated with
the support events of the other merged plane(s).
[0034] In some cases, constraints are imposed on the fracture
planes identified from the microseismic data. For example, in some
cases, the distance residual of events must be less than a given
tolerance distance. The tolerance distance can be designated, for
example, as a control parameter. In some instances, the identified
fracture planes need to be properly truncated to represent the
finite size of fractures. The boundary of truncated planes can be
calculated from the support events' position and the events'
location measurement uncertainty. The new finite-size fracture
planes can be merged with the already-identified fractures.
[0035] In some instances, a new incoming N.sup.th microseismic
event is associated with the fracture planes already identified
based on the previous N-1 microseismic events. Upon associating the
new event with an existing fracture, an algorithm can be used to
update the existing fracture. For example, updating the fracture
may change the fracture's geometry, location, orientation, or other
parameters. Upon choosing one of the previously-identified fracture
planes, the fracture plane's distance from the new event can be
calculated. If the distance is less than or equal to the distance
control parameter, the new event can be added to the supporting
event set for the fracture plane. If the distance is larger than
the distance control parameter, other previously-identified
fracture planes can be selected (e.g., iteratively or recursively)
until a plane within the threshold distance is found. After the new
event is added to a support set for a fracture plane, new strike
and dip values can be evaluated and if needed can be re-calculated
(e.g., using the Chi-square fitting method, or another statistical
or deterministic technique) for the fracture plane. Typically,
re-calculating the fracture parameters causes limited change in the
orientation due to the conditional control of the distance.
[0036] In some cases, when a new microseismic event is associated
with a fracture plane, one or more parameters (e.g., distance
residual, area, etc.) can be modified or optimized. The plane's
distance residual r can represent the average distance from the
supporting events to the plane. If the distance residual is less
than the given residual tolerance T, the new event can be flagged
to the associated events set for the plane. In some cases, an
additional process, via which other associated events of the
supporting set are taken-off the list, is launched and is
terminated when the distance residual r falls within the given T. A
fracture plane's area can represent the size of the fracture plane.
Experience shows that usually a new event causes the fracture plane
to propagate in length, grow in height, or both. Thus computational
processes can be constrained by a non-decreasing area condition,
whereby the new plane's area should grow larger than or remain
equal to that of the original plane (rather than shrink) when the
new event is added to the plane.
[0037] A fracture plane's orientation can represent the angle of
the fracture plane. For example, a normal vector, the strike and
dip angles, or other suitable parameters can be used to represent
the fracture plane orientation. A change in a fracture plane's
orientation (or other changes to a fracture plane) can cause some
associated support events to be removed out of the associated
events list to the un-associated event list based on their distance
from the updated fracture plane. Additionally or alternatively, a
change in a fracture plane's orientation can cause some
previously-unassociated events to be assigned to the fracture plane
based on their proximity to the updated fracture plane.
Additionally, some events associated with nearby planes may also be
associated with the current plane. If a new event is associated to
two fracture planes, the fracture planes may intersect each other.
In some cases, intersecting planes can be merged. If the new event
does not belong to any existing fracture plane, it can be assigned
to the "unassociated events" list.
[0038] The accumulated N microseismic events can be considered at
any point to be a subset of the final post data event set. In such
cases, the histogram or distribution of orientations based on the
first N events may be different from the histogram or distribution
of orientations constructed from the final post data. Some fracture
planes extracted from N microseismic events may not be accurate,
and this inaccuracy can decrease as time increases and more events
are accumulated. As an example, accuracy and confidence may be
lower at an initial time when the detected fracture planes are
associated with microseismic events located close to the well bore.
Such data may indicate fracture planes that are nearly parallel to
the wellbore, even if those planes do not represent real
fractures.
[0039] Fracture accuracy confidence can be used a measure for the
certainty associated with fracture planes identified from
microseismic data. In some cases, the accuracy confidence is
identified in real time during the fracture treatment. The accuracy
confidence can be determined from any suitable data using any
suitable calculations. In some cases, the accuracy confidence value
for a fracture plane is influenced by the number of microseismic
events associated with the fracture plane. For example, the
accuracy confidence value can scale (e.g., linearly, non-linearly,
exponentially, polynomially, etc.) with the number of microseismic
events according to a function. The number of microseismic events
associated with a fracture plane can be incorporated (e.g., as a
weight, an exponent, etc.) in an equation for calculating the
accuracy confidence. In some instances, a fracture plane has a
higher confidence value when the fracture plane is supported by a
larger number of microseismic data points (or a lower confidence
value when the fracture plane is supported by a smaller number of
microseismic data points).
[0040] In some cases, the accuracy confidence value for a fracture
plane is influenced by the location uncertainty for the
microseismic events associated with the fracture plane. For
example, the accuracy confidence value can scale (e.g., linearly,
non-linearly, exponentially, polynomially, etc.) with the
microseismic event's location uncertainty according to a function.
The microseismic event's location uncertainty can be incorporated
(e.g., as a weight, an exponent, or any decaying function of the
distance, etc.) in an equation for calculating the accuracy
confidence. In some instances, a fracture plane has a higher
confidence value when the fracture plane is supported by
microseismic data points having lower uncertainty (or a lower
confidence value when the fracture plane is supported by
microseismic data points having higher uncertainty).
[0041] In some cases, the accuracy confidence value for a fracture
plane is influenced by the moment magnitude for the microseismic
events associated with the fracture plane. For example, the
accuracy confidence value can scale (e.g., linearly, non-linearly,
exponentially, polynomially, etc.) with the microseismic event's
moment magnitude according to a function. The microseismic event's
moment magnitude can be incorporated (e.g., as a weight, an
exponent, etc.) in an equation for calculating the accuracy
confidence. The moment magnitude for a microseismic event can refer
to the energy or intensity (sometimes proportional to the square of
the amplitude) of the event. For example, the moment magnitude for
a microseismic event can be a logarithmic scale value of the energy
or intensity, or another type of value representing energy
intensity. In some instances, a fracture plane has a higher
confidence value when the fracture plane is supported by
microseismic data points having higher intensity (or a lower
confidence value when the fracture plane is supported by
microseismic data points having lower intensity).
[0042] In some cases, the accuracy confidence value for a fracture
plane is influenced by the distance between the fracture plane and
the microseismic events associated with the fracture plane. For
example, the accuracy confidence value can scale (e.g., linearly,
non-linearly, exponentially, polynomially, etc.) with the average
distance between the fracture plane and the microseismic events
supporting the fracture plane. The average distance can be
incorporated (e.g., as a weight, an exponent, etc.) in an equation
for calculating the accuracy confidence. In some instances, a
fracture plane has a higher confidence value when the fracture
plane is supported by microseismic data points that are, on
average, closer to the fracture plane (or a lower confidence value
when the fracture plane is supported by microseismic data points
that are, on average, farther from the fracture plane).
[0043] In some cases, the accuracy confidence value for a fracture
plane is influenced by the fracture plane's orientation with
respect to a dominant orientation trend in the microseismic data
set. For example, the accuracy confidence value can scale (e.g.,
linearly, non-linearly, exponentially, polynomially, etc.) with the
angular difference between the fracture plane's orientation and a
dominant orientation trend in the microseismic data. The
orientation angles can include strike, dip or any relevant
combination (e.g., a three-dimensional spatial angle). The
orientation can be incorporated (e.g., as a weight, an exponent,
etc.) in an equation for calculating the accuracy confidence. A
microseismic data set can have one dominant orientation trend or it
can have multiple dominant orientation trends. Dominant orientation
trends can be classified, for example, as primary, secondary, etc.
In some instances, a fracture plane has a higher confidence value
when the fracture plane is aligned with a dominant orientation
trend in the microseismic data set (or a lower confidence value
when the fracture plane is deviated from the dominant orientation
trend in the microseismic data set).
[0044] A weighting value called the "weight of variation of
fracture orientation" can represent the angular difference between
the fracture plane's orientation and a dominant orientation trend
in the microseismic data. The weight of variation of fracture
orientation can be a scalar value that is a maximum when the
fracture plane is aligned with a dominant orientation trend. The
weight of variation of fracture orientation can be a minimum for
fracture orientations that are maximally separated from a dominant
fracture orientation trend. For example, when there is a single
dominant fracture orientation trend, the weight of variation of
fracture orientation can be zero for fractures that are
perpendicular (or normal) to the dominant fracture orientation. As
another example, when there are multiple dominant fracture
orientation trends, the weight of variation of fracture orientation
can be zero for fractures having orientations between the dominant
fracture orientations. The weight of variation of the fracture
orientation can be the ratio of the calculated plane's orientation
and the orientation reflected by the homogeneous case.
[0045] In some cases, when there are multiple dominant fracture
orientation trends, the weight of variation of fracture orientation
has the same maximum value for each dominant fracture orientation
trend. In some cases, when there are multiple dominant fracture
orientations, the weight of variation of fracture orientation has a
different local maximum value for each dominant fracture
orientation. For example, the weight of variation of fracture
orientation can be 1.0 for fractures that are parallel to a first
dominant fracture orientation trend, 0.8 for fractures that are
parallel to a second dominant fracture orientation trend, and 0.7
for fractures that are parallel to a third dominant fracture
orientation trend. The weight of variation of fracture orientation
can decrease to local minima between the dominant fracture
orientations trend. For example, the weight of variation of
fracture orientation between each neighboring pair of dominant
fracture orientations can define a local minimum half way between
the dominant fracture orientations or at another point between the
dominant fracture orientations.
[0046] The accuracy confidence parameter can be influenced by the
supporting microseismic events' location uncertainty, the
supporting microseismic events' moment magnitude, distance between
the supporting microseismic events and the fracture plane, the
number of supporting events associated with the plane, the weight
of variation of fracture orientation, other values, or any
appropriate combination of one or more of these. In some general
models, the confidence increases as moment magnitude is larger, and
as the variation of the fraction orientation becomes larger, and
the number of supporting events is larger, and their accuracy in
their location is larger, and as the variation of the weight as a
function of the distance is larger. These factors can be used as
inputs for defining weight in an equation for the accuracy
confidence. For example, in some models, the weights are linear or
nonlinear functions of these factors and the weight of variation of
the fracture orientation may appear with higher weight when
influencing the plane's confidence. In some examples, the accuracy
confidence is calculated as:
Confidence = ( weight of variation of fracture orientation ) * i =
1 number of events ( ( location uncertainty weight ) * ( moment
magnitude weight ) * ( distance variation weight ) ) . ( 3 )
##EQU00003##
Other equations or algorithms can be used to compute the
confidence.
[0047] The identified fracture planes can be classified into
confidence levels based on the fracture planes' accuracy confidence
values. In some instances, three levels are used: low confidence
level, medium confidence level and high confidence level. Any
suitable number of confidence levels can be used. In some examples,
when a new event is added to the supporting set associated with an
existing fracture plane, its associated fracture confidence
parameter may increase, which may cause the fracture plane to roll
from its current confidence level to a higher one, if it exists. As
another example, if a fracture's orientation diverts away from
orientation trends exhibited by post microseismic event data, as
microseismic events gradually accumulate, a decrease in fracture
confidence may be induced, mainly by the weight of variation of
fracture orientation, causing the plane to decrease its level to a
lower confidence level, if it exists. This may particularly apply
to fractures created at the initial time of hydraulic fracturing
treatment; it may also apply to other types of fractures in other
contexts.
[0048] Users (e.g., field engineers, operational engineers and
analysts, and others) can be provided a graphical display of the
fracture planes identified from the microseismic data. In some
cases, the graphical display allows the user to visualize the
identified planes in a real time fashion, in graphical panels
presenting the confidence levels. For example, three graphical
panels can be used to separately present the low confidence level,
medium confidence level and high confidence level fracture planes.
In some cases, the lower confidence level fracture planes are
created in the initial times of the fracturing treatment. In some
cases, higher confidence level fracture planes propagate in time in
the direction nearly perpendicular to the wellbore. As new
microseismic events gradually accumulate in time, the graphical
display can be updated to enable users to dynamically observe the
fracture planes association among confidence levels associated with
the graphical panels.
[0049] The confidence level groups can be presented as plots of the
fracture planes, or the confidence level groups can be presented in
another format. The confidence level groups can be presented
algebraically, for example, by showing the algebraic parameters
(e.g., parameters for the equation of a plane) of the fracture
planes in each group. The confidence level groups can be presented
numerically, for example, by showing the numerical parameters
(e.g., strike, dip, area, etc.) of the fracture planes in each
group. The confidence level groups can be presented in a tabular
form, for example, by presenting a table of the algebraic
parameters or numerical parameters of the fracture planes in each
group. Moreover, a fracture plane can be represented graphically in
a three-dimensional space, a two-dimensional space, or another
space. For example, a fracture plane can be represented in a
rectilinear coordinate system (e.g., x, y, z coordinates) in a
polar coordinate system (e.g., r, .theta., .phi. coordinates), or
another coordinate system. In some examples, a fracture plane can
be represented as a line at the fracture plane's intersection with
another plane (e.g., a line in the xy-plane, a line in the
xz-plane, a line in the yz-plane, or a line in any arbitrary plane
or surface).
[0050] In some instances, a graphical display allows users to track
and visualize spatial and temporal evolution of specific fracture
planes, including their generation, propagation and growth. For
example, a user may observe stages of a specific fracture plane's
spatial and temporal evolution such as, for example, initially
identifying the fracture plane based on three microseismic events,
a new event that changes the plane's orientation, a new event that
causes the planes' area to grow (e.g., vertically, horizontally, or
both), or other stages in the evolution of a fracture plane. The
spatial and temporal evolution of fracture planes may present the
travel paths of stimulated fluids and proppants injected into the
rock matrix. Visualization of dynamics of fracture planes can help
users better understand the hydraulic fracturing process, analyze
the fracture complexity more accurately, evaluate the effectiveness
of hydraulic fracture, or improve the well performance.
[0051] Although this application describes examples involving
microseismic event data, the techniques and systems described in
this application can be applied to other types of data. For
example, the techniques and systems described here can be used to
process data sets that include data elements that are unrelated to
microseismic events, which may include other types of physical data
associated with a subterranean zone. In some aspects, this
application provides a framework for processing large volumes of
data, and the framework can be adapted for various applications
that are not specifically described here. For example, the
techniques and systems described here can be used to analyze
spatial coordinates, orientation data, or other types of
information collected from any source. As an example, soil or rock
samples can be collected (e.g., during drilling), and the
concentration of a given compound (e.g., a certain "salt") as
function of location can be identified. This may help geophysicists
and operators evaluate the geo-layers in the ground.
[0052] FIG. 1A shows a schematic diagram of an example well system
100 with a computing subsystem 110. The example well system 100
includes a treatment well 102 and an observation well 104. The
observation well 104 can be located remotely from the treatment
well 102, near the treatment well 102, or at any suitable location.
The well system 100 can include one or more additional treatment
wells, observation wells, or other types of wells. The computing
subsystem 110 can include one or more computing devices or systems
located at the treatment well 102, at the observation well 104, or
in other locations. The computing subsystem 110 or any of its
components can be located apart from the other components shown in
FIG. 1A. For example, the computing subsystem 110 can be located at
a data processing center, a computing facility, or another suitable
location. The well system 100 can include additional or different
features, and the features of the well system can be arranged as
shown in FIG. 1A or in any other suitable configuration.
[0053] The example treatment well 102 includes a well bore 101 in a
subterranean zone 121 beneath the surface 106. The subterranean
zone 121 can include one or less than one rock formation, or the
subterranean zone 121 can include more than one rock formation. In
the example shown in FIG. 1A, the subterranean zone 121 includes
various subsurface layers 122. The subsurface layers 122 can be
defined by geological or other properties of the subterranean zone
121. For example, each of the subsurface layers 122 can correspond
to a particular lithology, a particular fluid content, a particular
stress or pressure profile, or any other suitable characteristic.
In some instances, one or more of the subsurface layers 122 can be
a fluid reservoir that contains hydrocarbons or other types of
fluids. The subterranean zone 121 may include any suitable rock
formation. For example, one or more of the subsurface layers 122
can include sandstone, carbonate materials, shale, coal, mudstone,
granite, or other materials.
[0054] The example treatment well 102 includes an injection
treatment subsystem 120, which includes instrument trucks 116, pump
trucks 114, and other equipment. The injection treatment subsystem
120 can apply an injection treatment to the subterranean zone 121
through the well bore 101. The injection treatment can be a
fracture treatment that fractures the subterranean zone 121. For
example, the injection treatment may initiate, propagate, or open
fractures in one or more of the subsurface layers 122. A fracture
treatment may include a mini fracture test treatment, a regular or
full fracture treatment, a follow-on fracture treatment, a
re-fracture treatment, a final fracture treatment or another type
of fracture treatment.
[0055] The fracture treatment can inject a treatment fluid into the
subterranean zone 121 at any suitable fluid pressures and fluid
flow rates. Fluids can be injected above, at or below a fracture
initiation pressure, above at or below a fracture closure pressure,
or at any suitable combination of these and other fluid pressures.
The fracture initiation pressure for a formation is the minimum
fluid injection pressure that can initiate or propagate artificial
fractures in the formation. Application of a fracture treatment may
or may not initiate or propagate artificial fractures in the
formation. The fracture closure pressure for a formation is the
minimum fluid injection pressure that can dilate existing fractures
in the subterranean formation. Application of a fracture treatment
may or may not dilate natural or artificial fractures in the
formation.
[0056] A fracture treatment can be applied by any appropriate
system, using any suitable technique. The pump trucks 114 may
include mobile vehicles, immobile installations, skids, hoses,
tubes, fluid tanks or reservoirs, pumps, valves, or other suitable
structures and equipment. In some cases, the pump trucks 114 are
coupled to a working string disposed in the well bore 101. During
operation, the pump trucks 114 can pump fluid through the working
string and into the subterranean zone 121. The pumped fluid can
include a pad, proppants, a flush fluid, additives, or other
materials.
[0057] A fracture treatment can be applied at a single fluid
injection location or at multiple fluid injection locations in a
subterranean zone, and the fluid may be injected over a single time
period or over multiple different time periods. In some instances,
a fracture treatment can use multiple different fluid injection
locations in a single well bore, multiple fluid injection locations
in multiple different well bores, or any suitable combination.
Moreover, the fracture treatment can inject fluid through any
suitable type of well bore, such as, for example, vertical well
bores, slant well bores, horizontal well bores, curved well bores,
or any suitable combination of these and others.
[0058] A fracture treatment can be controlled by any appropriate
system, using any suitable technique. The instrument trucks 116 can
include mobile vehicles, immobile installations, or other suitable
structures. The instrument trucks 116 can include an injection
control system that monitors and controls the fracture treatment
applied by the injection treatment subsystem 120. In some
implementations, the injection control system can communicate with
other equipment to monitor and control the injection treatment. For
example, the instrument trucks 116 may communicate with the pump
truck 114, subsurface instruments, and monitoring equipment.
[0059] The fracture treatment, as well as other activities and
natural phenomena, can generate microseismic events in the
subterranean zone 121, and microseismic data can be collected from
the subterranean zone 121. For example, the microseismic data can
be collected by one or more sensors 112 associated with the
observation well 104, or the microseismic data can be collected by
other types of systems. The microseismic information detected in
the well system 100 can include acoustic signals generated by
natural phenomena, acoustic signals associated with a fracture
treatment applied through the treatment well 102, or other types of
signals. For example, the sensors 112 may detect acoustic signals
generated by rock slips, rock movements, rock fractures or other
events in the subterranean zone 121. In some instances, the
locations of individual microseismic events can be determined based
on the microseismic data.
[0060] Microseismic events in the subterranean zone 121 may occur,
for example, along or near induced hydraulic fractures. The
microseismic events may be associated with pre-existing natural
fractures or hydraulic fracture planes induced by fracturing
activities. In some environments, the majority of detectable
microseismic events are associated with shear-slip rock fracturing.
Such events may or may not correspond to induced tensile hydraulic
fractures that have significant width generation. The orientation
of a fracture can be influenced by the stress regime, the presence
of fracture systems that were generated at various times in the
past (e.g., under the same or a different stress orientation). In
some environments, older fractures can be cemented shut over
geologic time, and remain as planes of weakness in the rocks in the
subsurface.
[0061] The observation well 104 shown in FIG. 1A includes a well
bore 111 in a subterranean region beneath the surface 106. The
observation well 104 includes sensors 112 and other equipment that
can be used to detect microseismic information. The sensors 112 may
include geophones or other types of listening equipment. The
sensors 112 can be located at a variety of positions in the well
system 100. In FIG. 1A, sensors 112 are installed at the surface
106 and beneath the surface 106 in the well bore 111. Additionally
or alternatively, sensors may be positioned in other locations
above or below the surface 106, in other locations within the well
bore 111, or within another well bore. The observation well 104 may
include additional equipment (e.g., working string, packers,
casing, or other equipment) not shown in FIG. 1A. In some
implementations, microseismic data are detected by sensors
installed in the treatment well 102 or at the surface 106, without
use of an observation well.
[0062] In some cases, all or part of the computing subsystem 110
can be contained in a technical command center at the well site, in
a real-time operations center at a remote location, in another
appropriate location, or any suitable combination of these. The
well system 100 and the computing subsystem 110 can include or
access any suitable communication infrastructure. For example, well
system 100 can include multiple separate communication links or a
network of interconnected communication links. The communication
links can include wired or wireless communications systems. For
example, sensors 112 may communicate with the instrument trucks 116
or the computing subsystem 110 through wired or wireless links or
networks, or the instrument trucks 116 may communicate with the
computing subsystem 110 through wired or wireless links or
networks. The communication links can include a public data
network, a private data network, satellite links, dedicated
communication channels, telecommunication links, or any suitable
combination of these and other communication links.
[0063] The computing subsystem 110 can analyze microseismic data
collected in the well system 100. For example, the computing
subsystem 110 may analyze microseismic event data from a fracture
treatment of a subterranean zone 121. Microseismic data from a
fracture treatment can include data collected before, during, or
after fluid injection. The computing subsystem 110 can receive the
microseismic data at any suitable time. In some instances, the
computing subsystem 110 receives the microseismic data in real time
(or substantially in real time) during the fracture treatment. For
example, the microseismic data may be sent to the computing
subsystem 110 immediately upon detection by the sensors 112. In
some instances, the computing subsystem 110 receives some or all of
the microseismic data after the fracture treatment has been
completed. The computing subsystem 110 can receive the microseismic
data in any suitable format. For example, the computing subsystem
110 can receive the microseismic data in a format produced by
microseismic sensors or detectors, or the computing subsystem 110
can receive the microseismic data after the microseismic data has
been formatted, packaged, or otherwise processed. The computing
subsystem 110 can receive the microseismic data by any suitable
means. For example, the computing subsystem 110 can receive the
microseismic data by a wired or wireless communication link, by a
wired or wireless network, or by one or more disks or other
tangible media.
[0064] The computing subsystem 110 can be used to perform fracture
mapping in real time during a fracture treatment. For example, the
computing subsystem 110 can receive microseismic data as a time
series of individual microseismic events as the fracture treatment
is applied. At any given time, the computing subsystem 110 can
identify fracture planes based on the microseismic data that has
been accumulated thus far. When a new microseismic event is
detected, the computing subsystem 110 can updated the
previously-generated fracture planes based on the new microseismic
event. For example, the computing subsystem 110 can identify a
previously-generated fracture plane that is most likely to be
associated with the new microseismic event. The
previously-generated fracture plane can be identified, for example,
based on spatial proximity or other considerations. The new
microseismic event can be combined with other microseismic events
associated with the previously-generated fracture plane, and the
combined set of microseismic events can be fitted to a plane.
Various checks can be performed, for example, to improve the
accuracy of the results. In some instances, the updated fracture
plane can be displayed to a user in real time, to allow the user to
view the growth, propagation, or evolution of fractures in the
subterranean zone.
[0065] Some of the techniques and operations described herein may
be implemented by a computing subsystem configured to provide the
functionality described. In various embodiments, a computing device
may include any of various types of devices, including, but not
limited to, personal computer systems, desktop computers, laptops,
notebooks, mainframe computer systems, handheld computers,
workstations, tablets, application servers, storage devices, or any
type of computing or electronic device.
[0066] FIG. 1B is a diagram of the example computing subsystem 110
of FIG. 1A. The example computing subsystem 110 can be located at
or near one or more wells of the well system 100 or at a remote
location. All or part of the computing subsystem 110 may operate
independent of the well system 100 or independent of any of the
other components shown in FIG. 1A. The example computing subsystem
110 includes a processor 160, a memory 150, and input/output
controllers 170 communicably coupled by a bus 165. The memory can
include, for example, a random access memory (RAM), a storage
device (e.g., a writable read-only memory (ROM) or others), a hard
disk, or another type of storage medium. The computing subsystem
110 can be preprogrammed or it can be programmed (and reprogrammed)
by loading a program from another source (e.g., from a CD-ROM, from
another computer device through a data network, or in another
manner). The input/output controller 170 is coupled to input/output
devices (e.g., a monitor 175, a mouse, a keyboard, or other
input/output devices) and to a communication link 180. The
input/output devices receive and transmit data in analog or digital
form over communication links such as a serial link, a wireless
link (e.g., infrared, radio frequency, or others), a parallel link,
or another type of link.
[0067] The communication link 180 can include any type of
communication channel, connector, data communication network, or
other link. For example, the communication link 180 can include a
wireless or a wired network, a Local Area Network (LAN), a Wide
Area Network (WAN), a private network, a public network (such as
the Internet), a WiFi network, a network that includes a satellite
link, or another type of data communication network.
[0068] The memory 150 can store instructions (e.g., computer code)
associated with an operating system, computer applications, and
other resources. The memory 150 can also store application data and
data objects that can be interpreted by one or more applications or
virtual machines running on the computing subsystem 110. As shown
in FIG. 1B, the example memory 150 includes microseismic data 151,
geological data 152, fracture data 153, other data 155, and
applications 156. In some implementations, a memory of a computing
device includes additional or different information.
[0069] The microseismic data 151 can include information on the
locations of microseisms in a subterranean zone. For example, the
microseismic data can include information based on acoustic data
detected at the observation well 104, at the surface 106, at the
treatment well 102, or at other locations. The microseismic data
151 can include information collected by sensors 112. In some
cases, the microseismic data 151 has been combined with other data,
reformatted, or otherwise processed. The microseismic event data
may include any suitable information relating to microseismic
events (locations, magnitudes, uncertainties, times, etc.). The
microseismic event data can include data collected from one or more
fracture treatments, which may include data collected before,
during, or after a fluid injection.
[0070] The geological data 152 can include information on the
geological properties of the subterranean zone 121. For example,
the geological data 152 may include information on the subsurface
layers 122, information on the well bores 101, 111, or information
on other attributes of the subterranean zone 121. In some cases,
the geological data 152 includes information on the lithology,
fluid content, stress profile, pressure profile, spatial extent, or
other attributes of one or more rock formations in the subterranean
zone. The geological data 152 can include information collected
from well logs, rock samples, outcroppings, microseismic imaging,
or other data sources.
[0071] The fracture data 153 can include information on fracture
planes in a subterranean zone. The fracture data 153 may identify
the locations, sizes, shapes, and other properties of fractures in
a model of a subterranean zone. The fracture data 153 can include
information on natural fractures, hydraulically-induced fractures,
or any other type of discontinuity in the subterranean zone 121.
The fracture data 153 can include fracture planes calculated from
the microseismic data 151. For each fracture plane, the fracture
data 153 can include information (e.g., strike angle, dip angle,
etc.) identifying an orientation of the fracture, information
identifying a shape (e.g., curvature, aperture, etc.) of the
fracture, information identifying boundaries of the fracture, or
any other suitable information.
[0072] The applications 156 can include software applications,
scripts, programs, functions, executables, or other modules that
are interpreted or executed by the processor 160. Such applications
may include machine-readable instructions for performing one or
more of the operations represented in FIG. 4. The applications 156
may include machine-readable instructions for generating a user
interface or a plot, such as, for example, those represented in
FIGS. 2A, 2B, 3A, 3B, 3C, 3D, 3E, and 3F. The applications 156 can
obtain input data, such as microseismic data, geological data, or
other types of input data, from the memory 150, from another local
source, or from one or more remote sources (e.g., via the
communication link 180). The applications 156 can generate output
data and store the output data in the memory 150, in another local
medium, or in one or more remote devices (e.g., by sending the
output data via the communication link 180).
[0073] The processor 160 can execute instructions, for example, to
generate output data based on data inputs. For example, the
processor 160 can run the applications 156 by executing or
interpreting the software, scripts, programs, functions,
executables, or other modules contained in the applications 156.
The processor 160 may perform one or more of the operations
represented in FIG. 4 or generate one or more of the interfaces or
plots shown in FIGS. 2A, 2B, 3A, 3B, 3C, 3D, 3E, and 3F. The input
data received by the processor 160 or the output data generated by
the processor 160 can include any of the microseismic data 151, the
geological data 152, the fracture data 153, or the other data
155.
[0074] FIGS. 2A and 2B are plots showing example fracture planes.
FIG. 2A includes a plot 200a showing an initial fracture plane
208a, an updated fracture plane 208b, and a microseismic event
206a. The plot 200a shows the effect of updating the parameters of
the initial fracture plane 208a based on the new microseismic event
206a. In particular, updating the parameters of the initial
fracture plane 208a generates the updated fracture plane 208b.
[0075] A fracture plane can be represented in any suitable
coordinate system (e.g., spherical coordinates, rectangular
coordinates, etc.). The plot 200a shows the fracture planes in a
three-dimensional rectilinear coordinate system. In the plot 200a,
the coordinate system is represented by the vertical axis 204a and
two horizontal axes 204b and 204c. The vertical axis 204a
represents a range of depths in a subterranean zone; the horizontal
axis 204b represents a range of East-West coordinates; and the
horizontal axis 204c represents a range of North-South coordinates
(all in units of feet).
[0076] The initial fracture plane 208a and the updated fracture
plane 208b are both represented by rectangular, two-dimensional
bodies extending through three-dimensional space. A fracture plane
can have any other suitable geometry, such as, for example,
triangular, ellipsoidal, trapezoidal, an irregular geometry, or
another type of geometry.
[0077] The plot 200a shows one example of how the parameters of a
fracture plane can be updated based on a single microseismic event.
As shown by comparing the two fracture planes in FIG. 2A, updating
the initial fracture plane 208a based on the microseismic event
206a causes the fracture plane to grow in height and length; the
updated fracture plane 208b has a greater vertical and horizontal
extent than the initial fracture plane 208a. Consequently, the
updated fracture plane 208b has a larger area than the initial
fracture plane 208a. In some instances, updating a fracture plane
changes the fracture plane in another manner.
[0078] FIG. 2B includes another plot 200b showing an initial
fracture plane 208c, an updated fracture plane 208d, and a
microseismic event 206b. The plot 200b shows the effect of updating
the parameters of the initial fracture plane 208c based on the new
microseismic event 206b. In particular, updating the parameters of
the initial fracture plane 208c generates the updated fracture
plane 208d.
[0079] The plot 200b shows the fracture planes in a
three-dimensional rectilinear coordinate system represented by the
vertical axis 204d and two horizontal axes 204e and 204f. The axes
in the plot 200b represent the same parameters as the axes in the
plot 200a, on a different scale. The initial fracture plane 208c
and the updated fracture plane 208d are both represented by
rectangular, two-dimensional areas extending in the
three-dimensional coordinate system.
[0080] As shown by comparing the two fracture planes in FIG. 2B,
updating the initial fracture plane 208c based on the microseismic
event 206b causes the fracture plane to rotate to a new
orientation. For example, the updated fracture plane 208d has a
different orientation than the initial fracture plane 208c, with
respect to the vertical and horizontal axes in the plot 200b.
Accordingly, the updated fracture plane 208d and the initial
fracture plane 208c define normal vectors having different
orientations (i.e., pointing in non-parallel directions in
space).
[0081] FIGS. 3A-3F are plots showing updates for an example
fracture plane. The plots show an example time sequence for the
fracture plane. FIG. 3A shows a plot 300a of an initial fracture
plane 308a; each subsequent plot in the time sequence shows the
fracture plane as updated based on a new microseismic data point.
FIG. 3B shows a plot 300b of a first updated fracture plane 308b;
FIG. 3C shows a plot 300c of a second updated fracture plane 308c;
FIG. 3D shows a plot 300d of a third updated fracture plane 308d;
FIG. 3E shows a plot 300e of a fourth updated fracture plane 308e;
and FIG. 3F shows a plot 300f of a fifth updated fracture plane
308f. In each plot, the previous version of the fracture plane is
shown for comparison. The plots in FIGS. 3A-3F also show the well
bore 310 and microseismic events 306.
[0082] Each of the plots 300a, 300b, 300c, 300d, 300e, and 300f
shows the respective fracture planes in a three-dimensional
rectilinear coordinate system represented by the vertical axis 304a
and two horizontal axes 304b and 304c. The vertical axis 304a
represents a range of depths in a subterranean zone; the horizontal
axis 304b represents a range of East-West coordinates; and the
horizontal axis 304c represents a range of North-South coordinates
(all in units of feet). As shown in the figures, the axes are
scaled for each respective plot. In the examples shown in FIGS.
3A-3F, the fracture planes are represented by two-dimensional,
rectangular areas extending in the three-dimensional coordinate
system. Fracture planes can have other spatial geometries.
[0083] The initial fracture plane 308a and the updated fracture
planes 308b, 308c, 308d, 308e, and 308f represent the growth and
evolution of an individual fracture over time. In the example
shown, the initial fracture plane 308a is identified when the
40.sup.th microseismic event is received; the 87.sup.th
microseismic event triggers an update algorithm. For example, the
process 430 shown in FIG. 4 (or another process) can be used to
update a fracture plane based on a new microseismic event. FIG. 3B
shows that updating the fracture plane based on the 87.sup.th
microseismic event changes the fracture plane's orientation. In
particular, updating the initial fracture plane 308a based on the
87.sup.th microseismic event causes the fracture plane to rotate to
a new orientation, and the first updated fracture plane 308b has a
different orientation than the initial fracture plane 308a. The
remaining updates shown in FIGS. 3C-3F cause the fracture plane to
propagate, and the plots show how the fracture plane's area
increases as time progresses.
[0084] FIG. 3C shows an update based on the 89.sup.th microseismic
event received. Updating the first updated fracture plane 308b
based on the 89.sup.th microseismic event causes the fracture plane
to grow vertically, and the second updated fracture plane 308c is
taller than the first updated fracture plane 308b. FIG. 3D shows an
update based on the 130.sup.th microseismic event received.
Updating the second updated fracture plane 308c based on the
130.sup.th microseismic event causes the fracture plane to grow
vertically, and the third updated fracture plane 308d is taller
than the second updated fracture plane 308c. FIG. 3E shows an
update based on the 152.sup.nd microseismic event received.
Updating the third updated fracture plane 308d based on the
152.sup.nd microseismic event causes the fracture plane to grow
horizontally (toward the left in the figure), and the fourth
updated fracture plane 308e is longer than the third updated
fracture plane 308d. FIG. 3F shows an update based on the
157.sup.th microseismic event received. Updating the third updated
fracture plane 308d based on the 157.sup.th microseismic event
causes the fracture plane to grow horizontally (toward the right in
the figure) and vertically, and the fifth updated fracture plane
308f is longer and taller than the fourth updated fracture plane
308e.
[0085] FIG. 4 is a flow chart of an example process 430 for
analyzing microseismic data. Some or all of the operations in the
process 430 can be implemented by one or more computing devices. In
some implementations, the process 430 may include additional,
fewer, or different operations performed in the same or a different
order. Moreover, one or more of the individual operations or
subsets of the operations in the process 430 can be performed in
isolation or in other contexts. Output data generated by the
process 430, including output generated by intermediate operations,
can include stored, displayed, printed, transmitted, communicated
or processed information.
[0086] In some implementations, some or all of the operations in
the process 430 are executed in real time during a fracture
treatment. An operation can be performed in real time, for example,
by performing the operation in response to receiving data (e.g.,
from a sensor or monitoring system) without substantial delay. An
operation can be performed in real time, for example, by performing
the operation while monitoring for additional microseismic data
from the fracture treatment. Some real time operations can receive
an input and produce an output during a fracture treatment; in some
instances, the output is made available to a user within a time
frame that allows an operator to respond to the output, for
example, by modifying the fracture treatment.
[0087] In some cases, some or all of the operations in the process
430 are executed dynamically during a fracture treatment. An
operation can be executed dynamically, for example, by iteratively
or repeatedly performing the operation based on additional inputs,
for example, as the inputs are made available. In some instances,
dynamic operations are performed in response to receiving data for
a new microseismic event (or in response to receiving data for a
certain number of new microseismic events, etc.).
[0088] At 400, microseismic data for a new microseismic event are
received. For example, the microseismic data can be obtained by
reading the microseismic data from memory, by receiving the
microseismic data from a remote device, or in a different manner.
The microseismic data may include information on the measured
location of the new microseismic event, information on a measured
magnitude of the new microseismic event, information on an
uncertainty associated with the new microseismic event, or
information on a time associated with the new microseismic event,
etc. The microseismic data are collected from a fracture treatment.
For example, the microseismic event data may include microseismic
data collected at an observation well, at a treatment well, at the
surface, or at other locations in a well system. Microseismic data
from a fracture treatment can include data for microseismic events
detected before, during, or after the fracture treatment is
applied. For example, in some instances, microseismic monitoring
begins before the fracture treatment is applied, ends after the
fracture treatment is applied, or both.
[0089] At 401, a previously-generated fracture plane is selected.
In this example, the fracture plane is "previously-generated" in
the sense that it was generated before the data for the new
microseismic event was received. In some implementations,
parameters of a previously-generated fracture plane are the
parameters that were identified from microseismic data collected
before the new microseismic event was detected. The prior
microseismic event data and the new microseismic event can be part
of a microseismic data set from the same fracture treatment of a
subterranean zone. In some instance, the prior microseismic event
data and the new microseismic event are from different fracture
treatments.
[0090] Fracture planes (e.g., the previously-generated fracture
plane selected at 401) can be identified from microseismic data by
any suitable operation, process or algorithm. A fracture plane can
be identified by computing the parameters of the fracture plane,
for example, from the locations and other parameters of the
measured microseismic events. In some cases, the fracture planes
are identified in real time during the fracture treatment. Example
techniques for identifying fracture planes from microseismic data
are described in U.S. Provisional Application Ser. No. 61/710,582,
filed on Oct. 5, 2012.
[0091] In some instances, when the data are received at 400,
several fracture planes have already been generated. For example,
tens or hundreds of fracture planes may have already been
identified from previously-received microseismic data. As such, in
some cases, a particular fracture plane is selected from multiple
previously-generated fracture planes at 401. For example, the
particular fracture plane can be selected from a list of
previously-generated fracture planes based on an index, selection
criteria, or other information.
[0092] At 402, the distance between the new microseismic event and
the selected fracture plane is calculated. The distance can be
calculated, for example, based on the spatial coordinates of the
new microseismic event and the parameters of the selected fracture
plane. In some instance, the distance calculation can account for
uncertainty in the location of the microseismic event, uncertainty
in the location of the fracture plane, or both. Other information
can be accounted for in calculating the distance.
[0093] At 403, the distance between the new microseismic event and
the selected fracture plane is compared to a control parameter. The
control parameter can be a threshold value for determining whether
the selected fracture plane is close enough to the new microseismic
event, for example, to consider the new microseismic event as a
supporting event for the selected fracture plane. The control
parameter can be a previously-designated threshold value (e.g., a
system constant). The control parameter can be a dynamically
computed value. For example, the control parameter can be computed
based on the parameters of the selected fracture plane, parameters
of other previously-generated fracture planes, or based on other
information.
[0094] If the distance between the new microseismic event and the
selected fracture plane is not less than the control parameter, the
process 430 progresses to operation 450. At 450, if there are other
previously-generated fracture planes that have not been selected,
the process 430 progresses to operation 401. Accordingly, in some
cases, the operations 400, 402, 403, 450, and 401 cause the process
430 to sequentially select multiple different previously-generated
fracture planes.
[0095] The process 430 can use any suitable algorithm or technique
to systematically progress through previously-generated fracture
planes. For example, an indexed list of the previously-generated
fracture planes can be created. The list can be sorted, for
example, based on size, confidence, time, or other parameters of
the fracture planes, or the list can be unsorted. A stored index
can be used to systematically select a different
previously-generated fracture plane from the list each time
operation 401 is executed.
[0096] In some cases, the previously-generated fracture planes are
selected in sequence until all the previously-generated fracture
planes have been selected. At 450, if all the previously-generated
fracture planes have been selected, the new microseismic event is
designated as an unassociated event at 460. As such, the new
microseismic event can be labeled, tagged, or otherwise designated
as not supporting any fracture plane.
[0097] In some cases, the previously-generated fracture planes are
selected in sequence until the distance between a selected fracture
plane and the new microseismic event is less than the control
parameter. At 403, if the distance between the new microseismic
event and the selected fracture plane is not less than the control
parameter, the process 430 progresses to operation 415. At 415, the
selected fracture plane is updated based on the new microseismic
event. The operations in the dashed box in FIG. 4 represent an
example technique for updating a fracture plane based on a new
microseismic event. Other techniques can be used.
[0098] At 404, parameters of the selected fracture plane are
computed. In the example shown, the orientation, area, and distance
residual of the fracture plane are calculated. The area of the
fracture plane indicates the fracture plane's two-dimensional size.
The distance residual of a fracture plane indicates the average
distance between the fracture plane and the fracture plane's
supporting events.
[0099] The orientation of the fracture plane indicates the fracture
plane's angle, for example, in a specified coordinate system. The
orientation can be specified, for example, by particular values of
the dip angle and strike angle. New strike and dip values can be
calculated at 404 using a Chi-square fitting technique or other
techniques. In some cases, the change in orientation is small, for
example, due to the conditional control of the distance.
[0100] The parameters of the selected fracture plane can be
calculated based on the new microseismic event and other
microseismic events. For example, the other microseismic events can
be prior microseismic events that occurred or were detected (or
both) before the new microseismic event. In some cases, the other
microseismic events are the set of supporting microseismic events
that were used to compute the previously-generated fracture plane
(i.e., the fracture plane that was selected at 401).
[0101] At 405, the distance residual is compared to a tolerance
value. The tolerance value can be a threshold value for determining
whether the microseismic events that were used to update the
fracture plane are (on average) close enough to the updated
fracture plane, for example, to consider the new microseismic event
as a supporting event for the updated fracture plane. The tolerance
value can be a previously-designated threshold value (e.g., a
system constant). The tolerance value can be a dynamically computed
value.
[0102] At 405, if the distance residual is less than the control
parameter, the process 430 progresses to operation 410. At 410, the
updated fracture plane can be stored, and the new microseismic
event is associated with the updated fracture plane.
[0103] At 405, if the distance residual is not less than the
control parameter, the process 430 progresses to operation 406. At
406, the distance residual can be reduced by disassociating one or
more microseismic events from the selected fracture plane. For
example, one or more microseismic events that are the greatest
distance from the updated version of the selected fracture plane
can be disassociated from the fracture plane.
[0104] At 407, new fracture plane parameters are calculated from
the microseismic events remaining after one or more microseismic
events were disassociated at 406. If the distance residual has not
been reduced or if the distance residual has not been reduced by an
acceptable amount (e.g., less than the tolerance value or some
other threshold), then the process 430 progresses to operation 460.
At 460, the new microseismic event is designated as an unassociated
event at 460. As such, the microseismic event can be labeled,
tagged, or otherwise designated as not supporting any fracture
plane. In some instances, the selected fracture plane can be
restored to its previously-generated parameters. In other words, if
the new microseismic event is designated as unassociated, the
updated parameters for the fracture plane calculated at 404 can be
discarded.
[0105] In some cases, the process 430 improves or optimizes the
distance residual and area when the selected fracture plane is
updated at 415. For example, when the updated fracture plane's
distance residual is less than the tolerance value at 405, the new
microseismic event becomes associated with the fracture plane at
410. Otherwise, other microseismic events in the supporting set can
be disassociated until the distance residual falls within the
threshold value. In some cases, the change of the fracture plane's
orientation or size causes some microseismic events to be
disassociated from the fracture plane. In some cases, the change of
the fracture plane's orientation or size causes some microseismic
events to be associated to the fracture plane. In some instances, a
microseismic event can be associated with multiple fracture planes.
The association of a microseismic event with multiple fracture
planes can indicate that the fracture planes intersect.
[0106] If the distance residual has been reduced by an acceptable
amount at 407, then the process 430 progresses to operation 408. At
408, the area of the updated fracture plane (after disassociating
one or more microseismic events at 406) is computed. The area can
be the size of the fracture plane generated from the microseismic
events still associated with the fracture plane after the events
were disassociated at 406. If the size of the fracture plane is not
greater than the prior area of the fracture plane, then the process
430 progresses to operation 460 (described above). As such, the
check performed at 408 can ensure that associating the new
microseismic event to the fracture plane does not cause the
fracture plane to shrink. This check can be performed, for example,
to incorporate physical or geological constraints in a fracture
matching algorithm. For example, the check can be performed to
reflect knowledge that fractures tend to grow (rather than shrink)
during a fracture treatment. Experience shows that new microseismic
events are typically associated with a fracture propagating in
length or growing in height. As such, the non-decreasing area
condition can be imposed to ensure that the an updated fracture
plane's area is larger than or equal to that of the original plane.
Other assumptions are used in some environments.
[0107] At 408, if the size of the fracture plane is greater than
the prior area of the fracture plane, then the process 430
progresses to operation 410. At 410, the new microseismic event is
associated with the fracture plane. If any microseismic events were
disassociated at 406, those microseismic events can be designated
as unassociated, or they may be handled in a different manner.
Example techniques for handling disassociated microseismic events
are described in U.S. Provisional Application Ser. No. 61/710,582,
filed on Oct. 5, 2012. In some instances, the updated fracture
plane parameters (i.e., the fracture plane parameters based on the
microseismic events that remain associated after 406) are stored as
the updated fracture plane.
[0108] The example process 430 includes checks that can improve the
accuracy of a fracture matching algorithm. For example, some or all
of the comparisons at 403, 405, 407, and 408 can help to improve
confidence that the updated fracture plane corresponds to a
physical fracture in the subterranean zone. The comparisons can be
adjusted for a particular environment, as appropriate. In some
cases, additional or different comparisons can be made. For
example, in some cases, an accuracy confidence value is used to
determine whether to associated a new microseismic event to a
plane. Example techniques for calculating an accuracy confidence
value for a fracture plane are described in U.S. Provisional
Application Ser. No. 61/710,582, filed on Oct. 5, 2012.
[0109] In some implementations, a graphical representation of the
updated fracture planes is generated. The graphical representation
can be displayed, for example, to present the updated fracture
plane in real time during the fracture treatment. The graphical
representation can include a single fracture plane or multiple
fracture planes. The graphical representation can include a
three-dimensional representation of the fracture plane, a
three-dimensional representation of the microseismic events
associated with the fracture plane, or a combination of these and
other features. Examples of a graphical representation of a
fracture plane are shown in FIGS. 2A, 2B, 3A, 3B, 3C, 3D, 3E, and
3F. Other types of graphical representations can be used.
[0110] The graphical representation can be displayed on a monitor,
screen, or other type of display device. In some instances, the
display is updated. For example, the displayed graphical
representation can be updated based on additional microseismic
event data from the fracture treatment. Displaying (and in some
cases, updating) the graphical representation can allow a user to
view dynamic behavior associated with a fracture treatment. In some
cases, a fracture plane can be updated as additional microseismic
data is accumulated, and the updates may cause the fracture plane
to grow or change orientation.
[0111] Some embodiments of subject matter and operations described
in this specification can be implemented in digital electronic
circuitry, or in computer software, firmware, or hardware,
including the structures disclosed in this specification and their
structural equivalents, or in combinations of one or more of them.
Some embodiments of subject matter described in this specification
can be implemented as one or more computer programs, i.e., one or
more modules of computer program instructions, encoded on computer
storage medium for execution by, or to control the operation of,
data processing apparatus. A computer storage medium can be, or can
be included in, a computer-readable storage device, a
computer-readable storage substrate, a random or serial access
memory array or device, or a combination of one or more of them.
Moreover, while a computer storage medium is not a propagated
signal, a computer storage medium can be a source or destination of
computer program instructions encoded in an artificially generated
propagated signal. The computer storage medium can also be, or be
included in, one or more separate physical components or media
(e.g., multiple CDs, disks, or other storage devices).
[0112] The term "data processing apparatus" encompasses all kinds
of apparatus, devices, and machines for processing data, including
by way of example a programmable processor, a computer, a system on
a chip, or multiple ones, or combinations, of the foregoing. The
apparatus can include special purpose logic circuitry, e.g., an
FPGA (field programmable gate array) or an ASIC (application
specific integrated circuit). The apparatus can also include, in
addition to hardware, code that creates an execution environment
for the computer program in question, e.g., code that constitutes
processor firmware, a protocol stack, a database management system,
an operating system, a cross-platform runtime environment, a
virtual machine, or a combination of one or more of them. The
apparatus and execution environment can realize various different
computing model infrastructures, such as web services, distributed
computing and grid computing infrastructures.
[0113] A computer program (also known as a program, software,
software application, script, or code) can be written in any form
of programming language, including compiled or interpreted
languages, declarative or procedural languages. A computer program
may, but need not, correspond to a file in a file system. A program
can be stored in a portion of a file that holds other programs or
data (e.g., one or more scripts stored in a markup language
document), in a single file dedicated to the program in question,
or in multiple coordinated files (e.g., files that store one or
more modules, sub programs, or portions of code). A computer
program can be deployed to be executed on one computer or on
multiple computers that are located at one site or distributed
across multiple sites and interconnected by a communication
network.
[0114] Some of the processes and logic flows described in this
specification can be performed by one or more programmable
processors executing one or more computer programs to perform
actions by operating on input data and generating output. The
processes and logic flows can also be performed by, and apparatus
can also be implemented as, special purpose logic circuitry, e.g.,
an FPGA (field programmable gate array) or an ASIC (application
specific integrated circuit).
[0115] Processors suitable for the execution of a computer program
include, by way of example, both general and special purpose
microprocessors, and processors of any kind of digital computer.
Generally, a processor will receive instructions and data from a
read only memory or a random access memory or both. A computer
includes a processor for performing actions in accordance with
instructions and one or more memory devices for storing
instructions and data. A computer may also include, or be
operatively coupled to receive data from or transfer data to, or
both, one or more mass storage devices for storing data, e.g.,
magnetic, magneto optical disks, or optical disks. However, a
computer need not have such devices. Devices suitable for storing
computer program instructions and data include all forms of
non-volatile memory, media and memory devices, including by way of
example semiconductor memory devices (e.g., EPROM, EEPROM, flash
memory devices, and others), magnetic disks (e.g., internal hard
disks, removable disks, and others), magneto optical disks , and CD
ROM and DVD-ROM disks. The processor and the memory can be
supplemented by, or incorporated in, special purpose logic
circuitry.
[0116] To provide for interaction with a user, operations can be
implemented on a computer having a display device (e.g., a monitor,
or another type of display device) for displaying information to
the user and a keyboard and a pointing device (e.g., a mouse, a
trackball, a tablet, a touch sensitive screen, or another type of
pointing device) by which the user can provide input to the
computer. Other kinds of devices can be used to provide for
interaction with a user as well; for example, feedback provided to
the user can be any form of sensory feedback, e.g., visual
feedback, auditory feedback, or tactile feedback; and input from
the user can be received in any form, including acoustic, speech,
or tactile input. In addition, a computer can interact with a user
by sending documents to and receiving documents from a device that
is used by the user; for example, by sending web pages to a web
browser on a user's client device in response to requests received
from the web browser.
[0117] A client and server are generally remote from each other and
typically interact through a communication network. Examples of
communication networks include a local area network ("LAN") and a
wide area network ("WAN"), an inter-network (e.g., the Internet), a
network comprising a satellite link, and peer-to-peer networks
(e.g., ad hoc peer-to-peer networks). The relationship of client
and server arises by virtue of computer programs running on the
respective computers and having a client-server relationship to
each other.
[0118] In some aspects of what is described here, dominant
orientations embedded in sets of fractures associated with
microseismic events can be dynamically identified during a fracture
treatment. For example, fracture planes can be extracted from real
time microseismic events collected from the field. The fracture
planes can be identified based on microseismic event information
including: event locations, event location measurement
uncertainties, event moment magnitudes, event occurrence times, and
others. At each point in time, data can be associated with
previously-computed basic planes, including the microseismic
supporting set of events.
[0119] In some aspects of what is described here, a probability
histogram or distribution of basic planes can be constructed from
the microseismic events collected, and the histogram or
distribution can be used for deriving the dominant fracture
orientations. Fractures extracted along the dominant orientations
can, in some instances, provide an optimal match to the real time
microseismic events. The histogram or distribution and the dominant
orientations can have non-negligible sensitivity to the new
incoming microseismic event. As such, some planes identified during
the time microseismic data are assimilated may not be accurate when
comparing to the post microseismic event data results. Example
techniques for generating, updating, and using histograms based on
microseismic data are described in U.S. Provisional Application
Ser. No. 61/710,582, filed on Oct. 5, 2012.
[0120] In some aspects of what is described here, an accuracy
confidence parameter can provide a measure for the accuracy of
real-time identified planes. Factors impacting a plane's accuracy
confidence can include an event's intrinsic properties, the
relationship between support events and the plane, and the weight
reflecting the fracture orientation trends of post microseismic
event data. In some instances, fracture planes with high confidence
at the end of hydraulic fracturing treatment that were identified
in real time fashion are consistent with those obtained from the
post event data.
[0121] In some aspects, some or all of the features described here
can be combined or implemented separately in one or more software
programs for real-time automated fracture mapping. The software can
be implemented as a computer program product, an installed
application, a client-server application, an Internet application,
or any other suitable type of software. In some cases, a real-time
automated fracture mapping program can dynamically show users
spatial and temporal evolution of identified fracture planes in
real-time as microseismic events gradually accumulate. The dynamics
may include, for example, the generation of new fractures, the
propagation and growth of existing fractures, or other dynamics. In
some cases, a real-time automated fracture mapping program can
provide users the ability to view the real-time identified fracture
planes in multiple confidence levels. In some instances, users may
observe spatial and temporal evolution of the high confidence level
fractures, which may exhibit the dominant trends of overall
microseismic event data. In some cases, a real-time automated
fracture mapping program can evaluate fracture accuracy confidence,
for example, to measure the certainty of identified fracture
planes. The accuracy confidence values may, for example, help users
better understand and analyze changes in a probability histogram or
orientation distribution, which may continuously vary with the
real-time accumulation of microseismic events. In some cases, a
real-time automated fracture mapping program can provide results
that are consistent with post data fracture mapping. For example,
at the end of the hydraulic fracture treatment, the results
produced by the real-time automated fracture mapping program can be
statistically consistent with those obtained by a post data
automated fracture mapping program operating on the same data. Such
features may allow field engineers, operators and analysts, to
dynamically visualize and monitor spatial and temporal evolution of
hydraulic fractures, to analyze the fracture complexity and
reservoir geometry, to evaluate the effectiveness of hydraulic
fracturing treatment and to improve the well performance.
[0122] While this specification contains many details, these should
not be construed as limitations on the scope of what may be
claimed, but rather as descriptions of features specific to
particular examples. Certain features that are described in this
specification in the context of separate implementations can also
be combined. Conversely, various features that are described in the
context of a single implementation can also be implemented in
multiple embodiments separately or in any suitable
subcombination.
[0123] A number of embodiments have been described. Nevertheless,
it will be understood that various modifications can be made.
Accordingly, other embodiments are within the scope of the
following claims.
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