U.S. patent application number 14/635425 was filed with the patent office on 2015-09-03 for integration of seismic data with downhole fluid analysis to predict the location of heavy hydrocarbon.
The applicant listed for this patent is Schlumberger Technology Corporation. Invention is credited to Joseph Carl Fiduk, Oliver Mullins, Andrew Emil Pomerantz, Kang Wang, Youxiang Zuo.
Application Number | 20150247941 14/635425 |
Document ID | / |
Family ID | 54006684 |
Filed Date | 2015-09-03 |
United States Patent
Application |
20150247941 |
Kind Code |
A1 |
Fiduk; Joseph Carl ; et
al. |
September 3, 2015 |
INTEGRATION OF SEISMIC DATA WITH DOWNHOLE FLUID ANALYSIS TO PREDICT
THE LOCATION OF HEAVY HYDROCARBON
Abstract
Various implementations directed to the integration of seismic
data with downhole fluid analysis to predict the location of heavy
hydrocarbon are provided. In one implementation, a method may
include receiving seismic data for a hydrocarbon reservoir of
interest. The method may also include identifying geological
features associated with a secondary gas charge from the seismic
data. The method may further include determining the proximity of
the geological features to the hydrocarbon reservoir of interest.
The method may additionally include receiving preliminary downhole
fluid analysis (DFA) data from formations at or near the
hydrocarbon reservoir of interest. The method may further include
analyzing the preliminary DFA data to determine the equilibrium
state of the hydrocarbon reservoir and to confirm the secondary gas
charge in the hydrocarbon reservoir. The method may also include
determining whether to perform one or more additional DFA's.
Inventors: |
Fiduk; Joseph Carl;
(Houston, TX) ; Wang; Kang; (Beijing, CN) ;
Zuo; Youxiang; (Burnaby, CA) ; Pomerantz; Andrew
Emil; (Lexington, MA) ; Mullins; Oliver;
(Houston, TX) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Schlumberger Technology Corporation |
Sugar Land |
TX |
US |
|
|
Family ID: |
54006684 |
Appl. No.: |
14/635425 |
Filed: |
March 2, 2015 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
61947258 |
Mar 3, 2014 |
|
|
|
Current U.S.
Class: |
702/11 |
Current CPC
Class: |
E21B 49/00 20130101;
G01V 1/50 20130101; G01V 2210/644 20130101; G01V 1/003 20130101;
G01V 2210/663 20130101; G01V 11/00 20130101 |
International
Class: |
G01V 1/40 20060101
G01V001/40; E21B 47/14 20060101 E21B047/14; E21B 49/08 20060101
E21B049/08 |
Claims
1. A method, comprising: receiving seismic data for a hydrocarbon
reservoir of interest; identifying geological features associated
with a secondary gas charge from the seismic data, wherein the
geological features are selected from a group consisting of one or
more gas chimneys, bright spots and salt welds; determining the
proximity of the geological features to the hydrocarbon reservoir
of interest; receiving preliminary downhole fluid analysis (DFA)
data from formations at or near the hydrocarbon reservoir of
interest; analyzing the preliminary DFA data to determine the
equilibrium state of the hydrocarbon reservoir and to confirm the
secondary gas charge in the hydrocarbon reservoir; and determining
whether to perform one or more additional DFA's.
2. The method of claim 1, wherein the determination of performing
the additional DFAs are based on the proximity of the geological
features and the analysis of the preliminary DFA data.
3. The method of claim 1, wherein analyzing the preliminary DFA
data comprises analyzing the preliminary DFA data for fluid markers
associated with the secondary gas charge in the hydrocarbon
reservoir.
4. The method of claim 1, wherein determining the proximity
comprises determining whether the geological features are within a
predetermined threshold spatial distance of the hydrocarbon
reservoir.
5. The method of claim 1, further comprising determining whether
the geological features are in fluid communication with the
hydrocarbon reservoir.
6. The method of claim 1, wherein analyzing the preliminary DFA
data comprises determining if the hydrocarbon reservoir is
equilibrated using one or more equations of state models of
thermodynamic behavior of reservoir fluid.
7. The method of claim 1 further comprising determining a
geological age of the hydrocarbon reservoir based on the analysis
of the equilibrium state of the hydrocarbon reservoir.
8. The method of claim 1, wherein the geological features are gas
chimneys and further comprising: determining the size of the gas
chimneys; performing the one or more additional DFAs near the top
of the hydrocarbon reservoir if the gas chimneys are classified as
large; and performing the one or more additional DFAs near the
bottom of the hydrocarbon reservoir if the gas chimneys are
classified as small.
9. The method of claim 8, wherein the gas chimneys are classified
as large if it is determined to be greater than one kilometer or
comparable in size to the hydrocarbon reservoir, and as small if it
is determined to be less than five hundred meters or less than
one-third the size of the hydrocarbon reservoir.
10. The method of claim 1, further comprising predicting locations
of one or more additional DFA stations based on the size of the gas
chimneys.
11. The method of claim 1, wherein the one or more additional DFAs
determine whether the hydrocarbon reservoir is in equilibrium or
determine the presence of heavy hydrocarbon associated with the
secondary gas charge.
12. The method of claim 1, wherein the additional DFAs are used to
determine the impact of heavy hydrocarbon for the purpose of flow
assurance, defining a production strategy or field development
planning.
13. The method of claim 1, further comprising identifying flow
barriers caused by precipitation of solid particles or asphaltene
from reservoir fluids.
14. The method of claim 1, further comprising processing the
seismic data to enhance the identification of one or more gas
chimneys.
15. A method, comprising: receiving seismic data for a hydrocarbon
reservoir of interest; identifying geological features associated
with a secondary gas charge from the seismic data, wherein the
geological features are selected from a group consisting of one or
more gas chimneys, bright spots and salt welds; receiving
preliminary downhole fluid analysis (DFA) data from formations at
or near the hydrocarbon reservoir of interest; analyzing the
preliminary DFA data for fluid markers associated with the
secondary gas charge in the hydrocarbon reservoir of interest;
determining whether secondary gas charge has occurred from the
analysis of the preliminary DFA data; and predicting the presence
of large disequilibrium gas-oil-ratio (GOR) gradients and
saturation pressure gradients in the hydrocarbon reservoir based on
the determination of the secondary gas charge.
16. A non-transitory computer readable medium having stored thereon
a plurality of computer-executable instructions which, when
executed by a computer, cause the computer to: receive seismic data
for a hydrocarbon reservoir of interest; identify geological
features in seismic data that are associated with a secondary gas
charge, wherein the geological features are selected from a group
consisting of one or more gas chimneys, bright spots and salt
welds; receive downhole fluid analysis (DFA) data from formations
at or near the hydrocarbon reservoir of interest; analyze the DFA
data to determine the equilibrium state of the hydrocarbon
reservoir and to confirm the secondary gas charge in the
hydrocarbon reservoir; and predict one or more locations of heavy
hydrocarbon within the hydrocarbon reservoir of interest based on
the identified geological features.
17. The non-transitory computer readable medium of claim 16,
wherein the program instructions which cause the computer to
analyze the DFA data comprise program instructions which cause the
computer to analyze the DFA data for fluid markers associated with
the secondary gas charge in the hydrocarbon reservoir.
18. The non-transitory computer readable medium of claim 16,
wherein the program instructions which cause the computer to
analyze the DFA data comprise program instructions which cause the
computer to determine whether the hydrocarbon reservoir is
equilibrated based on the DFA data.
19. The non-transitory computer readable medium of claim 16,
wherein the program instructions which, cause the computer to
determine whether the reservoir is equilibrated based on the DFA
data comprise program instructions which cause the processor to
determine the presence of large disequilibrium gas-oil-ratio (GOR)
gradients and saturation pressure gradients in the hydrocarbon
reservoir of interest.
20. The non-transitory computer readable medium of claim 16,
wherein the one or more locations of heavy hydrocarbon within the
hydrocarbon reservoir of interest are based on the size of the one
or more gas chimneys.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application claims priority to U.S. Provisional Patent
Application Ser. No. 61/947,258 filed on Mar. 3, 2014, which is
incorporated by reference herein in its entirety.
BACKGROUND
[0002] One of the primary goals of an oil and gas operating company
is to develop a reservoir asset in the most cost-efficient way. As
such, it would be desirable for the operating company to identify
and assess all the risks that may impair the drainage of this
hydrocarbon accumulation before production starts and as field
development progresses. For example, it would be desirable for the
operating company to identify the level of spatial connectivity
within reservoir units, i.e., to identify flow barriers caused
either by the geological deposition of sediments, or by deposition
of solid particles, heavy hydrocarbons, precipitated from reservoir
fluids.
[0003] Before a drilling operation commences, a seismic survey may
be performed whereby reflected seismology is used to explore, and
thereby determine the properties of Earth's subsurface for the
purpose of identifying features associated with hydrocarbon
deposits. The seismic survey may be performed on land or water.
[0004] During or after a drilling operation, evaluations may be
performed on the reservoir for various purposes, such as to manage
the production of hydrocarbons from the reservoir. In one scenario,
formation evaluation may involve drawing fluid from the reservoir
into a downhole tool for testing or sampling. Various devices, such
as probes or packers, may be extended from the downhole tool to
isolate a region of the wellbore wall, and thereby establish fluid
communication with the reservoir surrounding the wellbore. Fluid
may then be drawn into the downhole tool using the probe or packer.
Within the downhole tool, the fluid may be directed to one or more
fluid analyzers and sensors that may detect properties of the
fluid. The properties of the fluid may be used to determine
reservoir architecture, connectivity, compositional gradients or
the like.
SUMMARY
[0005] Various implementations directed to the integration of
seismic data with downhole fluid analysis to predict the location
of heavy hydrocarbon are provided. In one implementation, a method
may include receiving seismic data for a hydrocarbon reservoir of
interest. The method may also include identifying geological
features associated with a secondary gas charge from the seismic
data, wherein the geological features are selected from a group
consisting of one or more gas chimneys, bright spots and salt
welds. The method may further include determining the proximity of
the geological features to the hydrocarbon reservoir of interest.
The method may additionally include receiving preliminary downhole
fluid analysis (DFA) data from formations at or near the
hydrocarbon reservoir of interest. The method may further include
analyzing the preliminary DFA data to determine the equilibrium
state of the hydrocarbon reservoir and to confirm the secondary gas
charge in the hydrocarbon reservoir. The method may also include
determining whether to perform one or more additional DFA's.
[0006] In another implementation, a method may include receiving
seismic data for a hydrocarbon reservoir of interest. The method
may also include identifying geological features associated with a
secondary gas charge from the seismic data, wherein the geological
features are selected from a group consisting of one or more gas
chimneys, bright spots and salt welds. The method may further
include receiving preliminary downhole fluid analysis (DFA) data
from formations at or near the hydrocarbon reservoir of interest.
The method may additionally include analyzing the preliminary DFA
data for fluid markers associated with the secondary gas charge in
the hydrocarbon reservoir of interest. The method may further
include determining whether secondary gas charge has occurred from
the analysis of the preliminary DFA data. The method may also
include predicting the presence of large disequilibrium
gas-oil-ratio (GOR) gradients and saturation pressure gradients in
the hydrocarbon reservoir based on the determination of the
secondary gas charge.
[0007] Various implementations are also directed to a
non-transitory computer readable medium having stored thereon a
plurality of computer-executable instructions which, when executed
by a computer, cause the computer to receive seismic data for a
hydrocarbon reservoir of interest. The computer-executable
instructions may also cause the computer to identify geological
features in seismic data that are associated with a secondary gas
charge, wherein the geological features are selected from a group
consisting of one or more gas chimneys, bright spots and salt
welds. The computer-executable instructions may further cause the
computer to receive downhole fluid analysis (DFA) data from
formations at or near the hydrocarbon reservoir of interest. The
computer-executable instructions may further cause the computer to
analyze the DFA data to determine the equilibrium state of the
hydrocarbon reservoir and to confirm the secondary gas charge in
the hydrocarbon reservoir. The computer-executable instructions may
further cause the computer to predict one or more locations of
heavy hydrocarbon within the hydrocarbon reservoir of interest
based on the identified geological features.
[0008] The above referenced summary section is provided to
introduce a selection of concepts in a simplified form that are
further described below in the detailed description section. The
summary is not intended to be used to limit the scope of the
claimed subject matter. Furthermore, the claimed subject matter is
not limited to implementations that solve any disadvantages noted
in any part of this disclosure. Indeed, the systems, methods,
processing procedures, techniques, and workflows disclosed herein
may complement or replace conventional methods for identifying,
isolating, or processing various aspects of seismic signals or
other data that is collected from a subsurface region or other
multi-dimensional space, including time-lapse seismic data
collected in a plurality of surveys.
BRIEF DESCRIPTION OF THE DRAWINGS
[0009] Implementations of various techniques will hereafter be
described with reference to the accompanying drawings. However, it
should be understood, that the accompanying drawings illustrate the
various implementations described herein, and are not meant to
limit the scope of various techniques described herein.
[0010] FIG. 1.1 illustrates a simplified diagrammatical view of a
seismic survey operation being performed by a seismic truck to
measure properties of the subterranean formation in connection with
various implementations described herein.
[0011] FIG. 1.2 illustrates a simplified diagrammatical view of a
drilling operation being performed by drilling tools suspended by a
rig, and advanced into the subterranean formations to form a
wellbore in connection with various implementations described
herein.
[0012] FIG. 1.3 illustrates a simplified diagrammatical view of a
wireline operation being performed by a wireline tool suspended by
a rig, and lowered into the wellbore in connection with various
implementations described herein.
[0013] FIG. 1.4 illustrates a simplified diagrammatical view of a
production operation being performed by a production tool deployed
from a production unit, or Christmas tree into the wellbore to draw
fluid from the downhole reservoirs into surface facilities in
connection with various implementations described herein.
[0014] FIG. 2 illustrates a flow diagram of a method for the
integration of seismic data and downhole fluid analysis (DFA) to
predict the location of heavy hydrocarbon in accordance with
various implementations described herein.
[0015] FIG. 3 illustrates a diagrammatical view of a 2D seismic
data plot in accordance with various implementations described
herein.
[0016] FIG. 4 illustrates a rig with a downhole drilling tool in
accordance with various implementations described herein.
[0017] FIG. 5 illustrates a downhole wireline tool in accordance
with implementations of various technologies and techniques
described herein.
[0018] FIG. 6 illustrates a computing system in which various
implementations of various techniques described herein may be
implemented.
DETAILED DESCRIPTION
[0019] The discussion below is directed to certain specific
implementations. It is to be understood that the discussion below
is for the purpose of enabling a person with ordinary skill in the
art to make and use any subject matter defined now or later by the
patent "claims" found in any issued patent herein.
[0020] It is specifically intended that the claims not be limited
to the implementations and illustrations contained herein, but
include modified forms of those implementations including portions
of the implementations and combinations of elements of different
implementations as come within the scope of the following
claims.
[0021] Reference will now be made in detail to various
implementations, examples of which are illustrated in the
accompanying drawings and figures. In the following detailed
description, numerous specific details are set forth in order to
provide a thorough understanding of the present disclosure.
However, it will be apparent to one of ordinary skill in the art
that the present disclosure may be practiced without these specific
details. In other instances, well-known methods, procedures,
components, circuits and networks have not been described in detail
so as not to obscure aspects of the embodiments.
[0022] It will also be understood that, although the terms first,
second, etc. may be used herein to describe various elements, these
elements should not be limited by these terms. These terms are used
to distinguish one element from another. For example, a first
object could be termed a second object, and, similarly, a second
object could be termed a first object, without departing from the
scope of the claims. The first object and the second object are
both objects, respectively, but they are not to be considered the
same object.
[0023] The terminology used in the description of the present
disclosure herein is for the purpose of describing particular
implementations and is not intended to be limiting of the present
disclosure. As used in the description of the present disclosure
and the appended claims, the singular forms "a," "an" and "the" are
intended to include the plural forms as well, unless the context
clearly indicates otherwise. It will also be understood that the
term "and/or" as used herein refers to and encompasses one or more
possible combinations of one or more of the associated listed
items. It will be further understood that the terms "includes"
and/or "including," when used in this specification, specify the
presence of stated features, integers, operations, elements, and/or
components, but do not preclude the presence or addition of one or
more other features, integers, operations, elements, components
and/or groups thereof.
[0024] As used herein, the terms "up" and "down"; "upper" and
"lower"; "upwardly" and downwardly"; "below" and "above"; and other
similar terms indicating relative positions above or below a given
point or element may be used in connection with some
implementations of various technologies described herein. However,
when applied to equipment and methods for use in wells that are
deviated or horizontal, or when applied to equipment and methods
that when arranged in a well are in a deviated or horizontal
orientation, such terms may refer to a left to right, right to
left, or other relationships as appropriate.
[0025] It should also be noted that in the development of any such
actual implementation, numerous decisions specific to circumstance
may be made to achieve the developer's specific goals, such as
compliance with system-related and business-related constraints,
which will vary from one implementation to another. Moreover, it
will be appreciated that such a development effort might be complex
and time-consuming but would nevertheless be a routine undertaking
for those of ordinary skill in the art having the benefit of this
disclosure.
[0026] The terminology and phraseology used herein is solely used
for descriptive purposes and should not be construed as limiting in
scope. Language such as "having," "containing," or "involving," and
variations thereof, is intended to be broad and encompass the
subject matter listed thereafter, equivalents, and additional
subject matter not recited.
[0027] Furthermore, the description and examples are presented
solely for the purpose of illustrating the different embodiments,
and should not be construed as a limitation to the scope and
applicability. While any composition or structure may be described
herein as having certain materials, it should be understood that
the composition could optionally include two or more different
materials. In addition, the composition or structure may also
include some components other than the ones already cited. It
should also be understood that throughout this specification, when
a range is described as being useful, or suitable, or the like, it
is intended that any value within the range, including the end
points, is to be considered as having been stated. Furthermore,
respective numerical values should be read once as modified by the
term "about" (unless already expressly so modified) and then read
again as not to be so modified unless otherwise stated in context.
For example, "a range of from 1 to 10" is to be read as indicating
a respective possible number along the continuum between about 1
and about 10. In other words, when a certain range is expressed,
even if a few specific data points are explicitly identified or
referred to within the range, or even when no data points are
referred to within the range, it is to be understood that the
inventors appreciate and understand that any data points within the
range are to be considered to have been specified, and that the
inventors have possession of the entire range and points within the
range.
[0028] As used herein, the term "if" may be construed to mean
"when" or "upon" or "in response to determining" or "in response to
detecting," depending on the context. Similarly, the phrase "if it
is determined" or "if [a stated condition or event] is detected"
may be construed to mean "upon determining" or "in response to
determining" or "upon detecting [the stated condition or event]" or
"in response to detecting [the stated condition or event],"
depending on the context.
[0029] One or more implementations of various techniques for the
integration of seismic data and downhole fluid analysis (DFA) to
predict the location of heavy hydrocarbon will now be described in
more detail with reference to FIGS. 1-6 in the following
paragraphs.
Production Environment
[0030] FIGS. 1.1-1.4 illustrate simplified views of a production
field 100 having a subterranean formation 102 containing reservoir
104 therein in connection with various implementations described
herein. The production field 100 may be an oilfield, a gas field,
or the like, and may be on land, water or sea.
[0031] FIG. 1.1 illustrates a diagrammatical view of a seismic
survey operation being performed by a survey tool, such as a
seismic truck 106.1, or marine seismic vessel (not shown), to
measure properties of the subterranean formation 102 in connection
with various implementations described herein.
[0032] The survey operation may be a seismic survey operation for
producing sound vibrations or acoustic signals. In FIG. 1.1, one
such sound vibration, e.g., sound vibration 112 generated by source
110, may reflect off horizons 114 in earth formation 116. A set of
sound vibrations may be received by sensors, such as
geophone-receivers 118, situated on the earth's surface, or
hydrophones (not shown) deployed beneath the surface of the water
as part of a streamer array. The data received 120 may be
digitized, and provided as input data to a computer 122.1 of a
seismic truck 106.1, or marine vessel (not shown), and responsive
to the input data, computer 122.1 generates seismic data output
124. This seismic data output 124 may be stored, transmitted, or
further processed as desired, for example, by data reduction.
[0033] FIG. 1.2 illustrates a diagrammatical view of a drilling
operation being performed by drilling tools 106.2 suspended by a
rig 128, and advanced into the subterranean formations 102 to form
a wellbore 136 in connection with various implementations described
herein. Mud pit 130 may be used to draw drilling mud into the
drilling tools via flow line 132 for circulating drilling mud down
through the drilling tools, then up wellbore annulus 136 and back
to the surface. The drilling mud may be filtered and returned to
the mud pit. A circulating system may be used for storing,
controlling, or filtering the flowing drilling mud. The drilling
tools may be advanced into subterranean formations 102 to reach
reservoir 104. Each well may target one or more reservoirs. The
drilling tools may be adapted for measuring downhole properties
using logging while drilling (LWD) tools. The LWD tools may also be
adapted for taking core sample 133 as shown.
[0034] Computer facilities may be positioned at various locations
about the production field 100 (e.g., the surface unit 134), or at
remote locations. Surface unit 134 may be used to communicate with
the LWD tools, or offsite operations, as well as with other surface
or downhole sensors. Surface unit 134 may be capable of
communicating with the LWD tools to send commands to the LWD tools,
and to receive data therefrom. Surface unit 134 may also collect
data generated during the drilling operation and produce data
output 135, which may then be stored or transmitted.
[0035] Sensors (S), such as gauges, may be positioned about
production field 100 to collect data relating to various production
field operations as described previously. As shown, sensor (S) may
be positioned in one or more locations in the drilling tools,
and/or at rig 128 to measure drilling parameters, such as weight on
bit, torque on bit, pressures, temperatures, flow rates,
compositions, rotary speed, or other parameters of the field
operation. Sensors (S) may also be positioned in one or more
locations in the circulating system.
[0036] Drilling tools 106.2 may include a bottom hole assembly
(BHA) (not shown), generally referenced, near the drill bit (e.g.,
within several drill collar lengths from the drill bit). The BHA
may include capabilities for measuring, processing, and storing
information, as well as communicating with surface unit 134. The
BHA may further include drill collars for performing various other
measurement functions.
[0037] The BHA may include a communication subassembly that
communicates with surface unit 134. The communication subassembly
may be adapted to send signals to, and receive signals from the
surface using a communications channel, such as mud pulse
telemetry, electro-magnetic telemetry, or wired drill pipe
communications. The communication subassembly may include, for
example, a transmitter that generates a signal, such as an acoustic
or electromagnetic signal, which is representative of the measured
drilling parameters. It may be appreciated by one of skill in the
art that a variety of telemetry systems may be employed, such as
wired drill pipe, electromagnetic or other known telemetry
systems.
[0038] The wellbore may be drilled according to a drilling plan
that is established prior to drilling. The drilling plan may set
forth equipment, pressures, trajectories and/or other parameters
that define the drilling process for the well site. The drilling
operation may then be performed according to the drilling plan.
However, as information is gathered, the drilling operation may
need to deviate from the drilling plan. Additionally, as drilling
or other operations are performed, the subsurface conditions may
change. The earth model may also need adjustment as new information
is collected.
[0039] The data gathered by sensors (S) may be collected by surface
unit 134 and/or other data collection sources for analysis or other
processing. The data collected by sensors (S) may be used alone or
in combination with other data. The data may be collected in one or
more databases, or transmitted on or offsite. The data may be
historical data, real time data, or combinations thereof. The real
time data may be used in real time, or stored for later use. The
data may also be combined with historical data or other inputs for
further analysis. The data may be stored in separate databases, or
combined into a single database.
[0040] Surface unit 134 may include transceiver 137 to allow
communications between surface unit 134, and various portions of
the production field 100 or other locations. Surface unit 134 may
also be provided with or functionally connected to one or more
controllers (not shown) for actuating mechanisms at production
field 100. Surface unit 134 may then send command signals to
production field 100 in response to data received. Surface unit 134
may receive commands via transceiver 137, or may itself execute
commands to the controller. A processor may be provided to analyze
the data (locally or remotely), make decisions, or actuate the
controller. In this manner, production field 100 may be selectively
adjusted based on the data collected. This technique may be used to
optimize portions of the field operation, such as controlling
drilling, weight on bit, pump rates, or other parameters. These
adjustments may be made automatically based on computer protocol,
or manually by an operator. In some cases, well plans may be
adjusted to select optimum operating conditions, or to avoid
problems.
[0041] FIG. 1.3 illustrates a diagrammatical view of a wireline
operation being performed by a wireline tool 106.3, suspended by a
rig 128, and lowered into the wellbore 136 in connection with
various implementations described herein. Wireline tool 106.3 may
be adapted for deployment into wellbore 136 for generating well
logs, performing downhole tests or collecting samples. Wireline
tool 106.3 may be used to provide another method and apparatus for
performing a seismic survey operation. Wireline tool 106.3 may, for
example, have an explosive, radioactive, electrical, or acoustic
energy source 144 that sends and/or receives electrical signals to
surrounding subterranean formations 102 and fluids therein.
[0042] Wireline tool 106.3 may be operatively connected to, for
example, geophones 118 and a computer 122.1 of a seismic truck
106.1 of FIG. 1.1. Wireline tool 106.3 may also provide data to
surface unit 134. Surface unit 134 may collect data generated
during the wireline operation, and may produce data output 135,
which may be stored or transmitted. Wireline tool 106.3 may be
positioned at various depths in the wellbore 136 to provide a
survey, or other information relating to the subterranean formation
102.
[0043] Sensors, such as gauges, may be positioned about production
field 100 to collect data relating to various field operations as
described previously. Sensors may be positioned in wireline tool
106.3 to measure downhole parameters which relate to, for example
porosity, permeability, fluid composition, and other parameters of
the field operation.
[0044] FIG. 1.4 illustrates a simplified diagrammatical view of a
production operation being performed by a production tool 106.4,
deployed from a production unit, or Christmas tree 129, into the
completed wellbore 136 to draw fluid from the downhole reservoirs
into surface facilities 142 in connection with various
implementations described herein. The fluid flows from reservoir
104 through perforations in the casing (not shown), and into
production tool 106.4 in wellbore 136, and to surface facilities
142, via gathering network 146.
[0045] Sensors, such as gauges, may be positioned about production
field 100 to collect data relating to various field operations as
described previously. Sensors may be positioned in production tool
106.4, or associated equipment, such as Christmas tree 129,
gathering network 146, surface facility 142, or the production
facility, to measure fluid parameters, such as fluid composition,
flow rates, pressures, temperatures, and other downhole parameters
of the production operation.
[0046] Production may also include injection wells for added
recovery. One or more gathering facilities may be operatively
connected to one or more of the well sites for selectively
collecting downhole fluids from the well site(s).
[0047] While FIGS. 1.2-1.4 illustrate tools used to measure
properties of a production field, such as an oilfield or gas field,
it may be appreciated that the tools may be used in connection with
other operations, such as mines, aquifers, storage, or other
subterranean facilities. Also, while certain data acquisition tools
are depicted, it may be appreciated that various measurement tools
capable of sensing parameters, such as seismic two-way travel time,
density, resistivity, production rate, etc., of the subterranean
formation and/or its geological formations may be used. Various
sensors may be located at various positions along the wellbore,
and/or the monitoring tools to collect, and/or monitor the desired
data. Other sources of data may also be provided from offsite
locations.
[0048] The field configurations of FIGS. 1.1-1.4 may be an example
of a field usable with oilfield or gas field application
frameworks. At least part of the production field 100 may be on
land, water or sea. Also, while a single field measured at a single
location may be depicted, oilfield or gas field applications may be
utilized with any combination of one or more oilfields, and/or gas
fields, one or more processing facilities, and one or more well
sites.
[0049] The data collected from various sources, such as the data
acquisition tools of FIGS. 1.1-1.4, respectively, or others not
depicted, may then be processed and/or evaluated. The seismic data
from the data acquisition tool 106.1 of FIG. 1.1 may be used by a
geophysicist to determine characteristics of the subterranean
formations, and identify features associated with oil and/or gas
deposits. The core and/or log data from data acquisition tool 106.2
of FIG. 1.2, and/or data acquisition tool 106.3 of FIG. 1.3, may be
used by a geologist to determine various characteristics of the
subterranean formation. The production data from data acquisition
tool 106.4 of FIG. 1.4 may be used by the reservoir engineer to
determine fluid flow reservoir characteristics. The data analyzed
by the geologist, geophysicist and the reservoir engineer may be
analyzed to determine reservoir fluid geodynamics (RFG) for the
purpose of flow assurance. The data analyzed by the geologist,
geophysicist, and the reservoir engineer may be analyzed using
modeling techniques.
[0050] Attention is now directed to methods, techniques, and
workflows for processing, and/or transforming collected data that
are in accordance with some implementations. Some operations in the
processing procedures, methods, techniques, and workflows disclosed
herein may be combined, and/or the order of some operations may be
changed. In the geosciences and other multi-dimensional data
processing disciplines, various interpretations, sets of
assumptions, or domain models such as velocity models, may be
refined in an iterative fashion. This iterative refinement can
include use of feedback loops executed on an algorithmic basis,
such as via a computing system, as discussed later, and/or through
manual control by a user who may make determinations regarding
whether a given action, template, or model has become accurate.
Analyzing a Reservoir
[0051] As mentioned above, a reservoir disposed in a subterranean
formation may contain hydrocarbons. In particular, the hydrocarbons
may develop from the thermal cracking of organic matter deposited
in source rocks as they are buried deeper in the earth's crust by
the deposition of newer sediments. Fluids containing these
hydrocarbons may eventually be expelled from the source rock and
migrate, such as through faults and fractures, until they are
trapped in a reservoir rock. Such migration of hydrocarbons may be
referred to as a primary charge. In particular, reservoir fluids
disposed in these reservoirs may contain the hydrocarbons, where
the hydrocarbons may take the form of oil, gas condensate, and/or
the like.
[0052] In one scenario, if the migration of fluids ceases and the
reservoirs behave as a closed system, then the reservoir fluids may
eventually reach a state of chemical and thermodynamic equilibrium.
Gravity may act as a force on the reservoir. In addition, depending
on the length of the hydrocarbon column and the hydrocarbon
composition, there may be composition gradients within the
reservoir. However, some reservoirs may not behave as an ideal
closed system as described above. Instead, one or a combination of
the following situations may occur: geologic events may alter the
reservoir structure after the primary charge, more thermally mature
fluids, such as gas, may arrive to the reservoir, this may be
referred to as a secondary or late charge, hydrocarbons may escape
via flow channels or a compromised cap seal, biodegradation at
sufficiently low temperature and mixing with biogenic methane,
biogenic methane arriving at the reservoir, water washing or the
like. Such reservoirs may have reservoir fluids which exist in a
state of non-equilibrium, and the fluid composition may not be
homogeneous.
[0053] In another scenario, the primary and secondary charge may
result in a mixing of the reservoir fluids, and the nature of the
mixing may be such that instability, and precipitation and/or
concentration of the solid hydrocarbon fraction, or asphaltene may
occur. Asphaltenes are solids that precipitate when an excess of
n-heptane or pentane is added to crude oil. Precipitation may also
occur during oil production, as a result of destabilization, which
may be the result of changes in temperature, pressure and/or the
chemical composition of the crude. Such precipitation may result in
the creation of heavy hydrocarbon. For example, an asphaltene layer
may be deposited up-structure where it coats grain surfaces forming
bitumen, which may not preclude permeability and the flow of
hydrocarbons. Alternatively, the asphaltene may be deposited
up-structure as a layer of solid hydrocarbon, which may preclude
permeability and therefore the flow of hydrocarbons. Further, the
precipitation may be deposited near the base of the reservoir as a
tar mat and/or heavy and viscous oil, which may form a thick
impermeable layer of asphaltene material.
[0054] The presence of heavy hydrocarbons may diminish fluid
mobility within a reservoir. For example, heavy hydrocarbons may
seal the reservoir from adjacent aquifers, thereby reducing aquifer
support. Heavy hydrocarbons may also reduce the production index by
flowing simultaneously with light hydrocarbons contained in the
reservoir formations. In addition, mobile heavy hydrocarbon may
further reduce the production index by depositing a coating of
thick tar on production tubular. However, distinguishing heavy
hydrocarbon from light hydrocarbon using data obtained from seismic
surveys, and/or downhole tool logs by traditional methods may be
difficult due to their low seismic velocity contrast and small
relatively size.
[0055] In yet another scenario, the reservoir may be
compartmentalized such that it lacks a level of spatial
connectivity within reservoir units (i.e., parts of the reservoir).
A compartmentalized reservoir may consist of two or more
compartments that effectively are not in hydraulic communication.
Two types of reservoir compartmentalization may include vertical
and lateral compartmentalization. Lateral compartmentalization may
occur as a result of faulting or stratigraphic changes in the
reservoir, while vertical compartmentalization may occur from
sealing barriers such as shale.
[0056] The presence of heavy hydrocarbons, reservoir
compartmentalization and non-equilibrium hydrocarbon distribution
can significantly hinder production, and may make a difference
between an economically-viable field and an economically-nonviable
field. Techniques aimed at understanding reservoir fluid
geodynamics for the purpose of flow assurance may allow an operator
to factor into a well development program the economic risks
associated with the presence of these features, and may ultimately
raise production.
Integration of Seismic Data and Downhole Fluid Analysis (DFA)
[0057] In one implementation, and as further described below, an
integration of seismic analysis and DFA may be used to provide
information that may be used to accurately identify heavy
hydrocarbons and their distribution in the reservoir of interest.
In particular, seismic analysis and downhole fluid analysis may be
used to identify subsurface features and fluid markers that may be
associated with secondary (or late) gas charging in the
reservoir.
[0058] FIG. 2 illustrates a flow diagram of a method 200 for the
integration of seismic data with DFA to predict the location of
heavy hydrocarbon in accordance with various implementations
described herein. In one scenario, method 200 uses seismic data in
combination with DFA to understand reservoir fluid geodynamics
(RFG). Understanding of RFG may help predict the presence of heavy
hydrocarbon layers, and their location within the reservoir. An
operator of reservoir may wish to obtain this information for many
reasons, for example to take into account the economic risk
associated with the presence of these heavy hydrocarbons in a well
development program, or for flow assurance purposes.
[0059] In one implementation, method 200 may be performed by one or
more computer applications, where the computer applications may
implement one or more of the electronics and processing system,
controller of the fluid analysis module, and/or the computer system
described below. It should be understood that while method 200
indicates a particular order of execution of operations, in some
implementations, certain portions of the operations might be
executed in a different order. Further, in some implementations,
additional operations or blocks may be added to the method.
Likewise, some operations or blocks may be omitted.
[0060] At block 210, seismic data may be received from one or more
seismic survey operations performed by a survey tool, such as the
seismic truck 106.1 of FIG. 1.1, or marine seismic vessel. In one
implementation, the land and/or marine seismic data may have been
acquired as part of a 2D or 3D survey exploration process to
identify subterranean geological formations associated with
hydrocarbon deposits in connection with various implementations
described herein. In a further implementation, the seismic data may
be time-lapse, or 4D seismic data obtained from repeated seismic
production surveys over a producing hydrocarbon reservoir, which
may be used to determine changes within the reservoir that may be
the result of hydrocarbon production, or injection of water, and/or
gas into reservoir as part of a well development program. In yet
another implementation, seismic data may have been acquired as part
of method 200. An example of a simplified diagrammatical view of a
2D seismic data plot in accordance with various implementation
described herein is depicted in FIG. 3.
[0061] At block 220, the seismic data may be processed to identify
subterranean geological features associated with secondary gas
charging into the hydrocarbon filled reservoir. In one scenario,
these subterranean geological features may include gas pockets, gas
chimneys or salt deposits. Referring to the 2D seismic data plot of
FIG. 3, bright spots in the seismic data may indicate the presence
of gas pockets. A gas chimney may be associated with a subsurface
leakage of gas from a poorly sealed hydrocarbon accumulation, and
may result in secondary gas charging of a hydrocarbon reservoir as
described herein. Referring to FIG. 3, gas chimneys may be visible
in the seismic data as areas of poor data quality, or push-downs.
In one implementation, the seismic data may be processed to enhance
the identification of gas chimneys.
[0062] Seismic data may also indicate the presence of salt
formations in communication with the reservoir. Associated with
these salt formations may be salt welds, the boundary between the
salt formation and reservoir formation, which may act as conduits
for secondary gas charging. The resolution, or bucket (bin) size of
the seismic survey may be insufficient to identify the presence of
a salt weld directly, and gas (bright spots) within it, unless the
salt weld is sizeable. However, the presence of the salt weld and
secondary gas charging may be inferred if there are bright spots in
the seismic data proximate to the salt reservoir boundary.
[0063] At block 230, the seismic data may be analyzed to determine
if the proximity of the identified subterranean geological feature
to the hydrocarbon reservoir indicates that it may be in gas
communication (or in connectivity) with the hydrocarbon reservoir.
In some implementations, the analysis at block 230 may be
applicable to a wellbore or a subterranean associated with a
hydrocarbon reservoir. In another implementation, since salt
deposits are frequently associated with, and in close proximity to
hydrocarbon reservoirs, the determining factor may be the analysis
at block 220, i.e., whether the salt weld has bright spots
associated with it. In yet another implementation, whether gas
chimneys are in communication with a hydrocarbon reservoir may be
determined by a predetermined threshold spatial distance. The
predetermined threshold spatial distance may depend on the size of
the gas chimney, and/or hydrocarbon reservoir. In yet another
implementation, geological proximity may be inferred by the
presence of permeable sedimentary formations, which may act as a
conduit. It should be understood that other techniques known to a
person of ordinary skill in the art for determining the proximity
may be used herein.
[0064] At block 240, preliminary DFA data may be received from one
or more DFA measurement stations of a wellbore, at different
locations within the reservoir. The preliminary DFA data may be
determined during drilling or thereafter. In one implementation,
the preliminary sample may be obtained using a downhole tool, such
as those described below with respect to FIGS. 4 and 5. Further, as
described below with respect to FIGS. 4 and 5, a computing
application associated with a fluid communication module, and/or
fluid analysis module may be used to determine the preliminary DFA
data in substantially real time. In a further implementation, the
computing application associated with the fluid communication
module and/or fluid analysis module may operate in conjunction with
a surface computing application, such as the electronics and
processing system 506, to determine the first DFA data. The details
of DFA are provided below in a section labeled Downhole Fluid
Analysis.
[0065] The preliminary first DFA data may include one or more
measurements of optical density, fluid fluorescence, fluid
composition, fluid color, the gas-oil ratio (GOR), temperature,
pressure, viscosity, density, resistivity, pH or H.sub.2S levels,
concentrations of several alkane components and groups in the first
fluid sample (e.g., fractional amounts of C.sub.1, C.sub.2,
C.sub.3-C.sub.5, C.sub.6+, CO.sub.2, H.sub.2O, and the like),
and/or the like.
[0066] At block 250, the preliminary DFA data may be analyzed to
determine whether a reservoir may be in disequilibrium. In one
implementation, the preliminary DFA data may be analyzed to
determine whether the GORs can be matched to cubic equations of
state (EOS), and thereby determine whether any secondary gas charge
has had time to equilibrate. In one scenario, the amount of
available preliminary DFA data may only allow an inference that the
reservoir is in disequilibrium.
[0067] Further, the preliminary DFA data may be analyzed for fluid
markers that may be associated with secondary gas charging. These
fluid markers may include the asphaltene content of the hydrocarbon
reservoir and GOR. Secondary gas charging may be inferred from the
organic solid deposition, asphaltene content, and the presence of
solution gas. For example, a high asphaltene level at the bottom of
the reservoir or high GOR at the top of the reservoir may be
associated with secondary gas charging. The DFA data may be
analyzed by optical, photoacoustic, or other techniques known to a
person of ordinary skill in the art.
[0068] In particular, one or more EOS models of the thermodynamic
behavior of the reservoir fluid may be used to predict the
reservoir DFA data at different locations within the reservoir.
Although various techniques described herein are with reference to
a reservoir, it should be understood that in some implementations
the techniques may be applied to a wellbore. In comparing the
preliminary DFA data to the predicted DFA data, it may be assumed
that there is connectivity between the spatial locations within the
reservoir and thermodynamic equilibrium. Thus, the predicted DFA
data may be used to confirm that they correspond to the expected
reservoir architecture. In particular, connectivity (i.e.,
non-compartmentalization) and equilibration of the reservoir can be
indicated by a moderate decrease of GOR values with increasing
depth, a continuous increase of asphaltene content as a function of
depth, a continuous increase of fluid density and/or fluid
viscosity as a function of depth, and/or the like. Accordingly, the
use of the EOS models to determine predicted DFA data may offer a
baseline for the reservoir against which the preliminary DFA data
can be compared, and thereby verification of whether the reservoir
is in equilibrium. Agreement between the preliminary DFA data and
the predicted DFA data may imply connectivity between the spatial
locations. On the other hand, disagreement between the preliminary
DFA data and the predicted DFA may be the result of geologic events
that may alter the reservoir structure after the primary charge,
such as thermally mature fluids from secondary gas charging
migrating into the reservior and/or geolgical events that may have
caused compartmentalization.
[0069] If the preliminary DFA data differs from the predicted DFA
data by a threshold amount, it may then be determined that the
reservoir is in a non-equilibrium state and/or compartmentalized.
For example, non-equilibrium and/or compartmentalization can be
indicated by a reversing trend in GOR (such as if lower GOR is
found higher in the column), discontinuous asphaltene content (or
if higher asphaltene content is found higher in the column),
discontinuous fluid density and/or fluid viscosity (or if higher
fluid density and/or fluid viscosity is found higher in the
column), variations in fluid composition, fluid properties
indicated by the preliminary DFA data that are larger than those of
the predicted DFA data, and/or the like. In one implementation, the
threshold amount may be equal to an amount greater than or equal to
a monotonic variation between the preliminary DFA data and the
predicted DFA data.
[0070] In one implementation, a surface computing system, such as
the electronics and processing system, may estimate the fluid
properties and/or fluid behavior using the EOS models. The
estimated fluid properties of the wellbore may include: GOR,
condensate-gas ratio (CGR), fluid color, density of each phase,
volumetric factors and compressibility, heat capacity, saturation
pressure (i.e., bubble or dew point), optical density, the
distribution of a solid fraction of the reservoir fluid (e.g.,
asphaltenes, resins, and/or the like), viscosity, and/or the like.
In one implementation, the EOS models may estimate the fluid
properties and/or fluid behavior as a function of depth, such that
the fluid properties and/or fluid behavior are predicted for one or
more additional measurement stations in the wellbore.
[0071] In such an implementation, the surface computing system may
perform the estimations based on the preliminary DFA data. The
surface computing system may perform the estimations based on DFA
data from multiple measurement stations.
[0072] In another implementation, the equilibrate analysis may be
used to infer the geological age of the hydrocarbon reservoir, and
thereby obtain a better understanding the reservoir fluid
geodynamics. For example, the analysis may be used to determine
whether the geological age of the hydrocarbon reservoir is young,
1-3 million years, or old, 100 million years. At block 260, a risk
assessment may be performed to determine whether heavy hydrocarbon
may be present within the hydrocarbon reservoir, which is the
result of secondary gas charging, and whether there is
disequilibrium. The risk assessment may be for flow assurance
purposes, and/or to determine whether additional DFA measurement
stations are needed to locate, test and monitor heavy hydrocarbon
and/or further support a determination of whether the wellbore,
reservoir is equilibrated.
[0073] In one implementation, the risk assessment may be determined
by any indication of secondary gas charging, such as the proximity
of subterranean geological features associated with gas charging,
as determined by seismic analysis at block 230, and fluid markers
obtained from preliminary DFA data, which may infer gas charging
and/or wellbore and/or reservoir disequilibrium as determine at
block 250.
[0074] If the analysis at block 260 determines that additional DFA
data is needed from additional downhole fluid samples then
additional fluid samples may be obtained in a similar manner as the
preliminary fluid samples, and the additional DFA data may be
determined in a similar manner as the preliminary DFA data
described herein. Further, in the case of the identified geological
feature being a gas chimney, it may be possible to infer the
location of the additional DFA measurement stations based on the
size of the gas chimney.
[0075] At block 270, the size of a gas chimney identified at block
220 is determined. In one implementation, a gas chimney may be
classified as large if its physical size is determined to be
greater than one kilometer (1 km). A gas chimney may also be
classified as large if its size is comparable to, or greater than
that of the hydrocarbon reservoir. A gas chimney may be classified
as small if its physical size is about four to five hundred meters
(4-500 m), or if its size is about one third (1/3) or less of the
hydrocarbon reservoir, with the relative size with respect to the
hydrocarbon reservoir being the determining factor.
[0076] If the analysis at block 270 classifies the gas chimney as
large, then at block 280 the additional DFA measurement stations,
from which additional DFA fluid samples and data may be obtained,
may be located at the top of the wellbore and/or reservoir. In one
scenario, a large gas chimney may be associated with a high rate of
gas charging into the reservoir. The high rate of gas charging may
result in a GOR that rapidly increases. The rapidly increasing GOR
may cause asphaltenes to destabilize before they can migrate away.
The high rate of gas charging, which may be associated with a large
gas chimney, may therefore result in a phase-separated bitumen
layer up-structure, or substantially near the top of the wellbore
and/or reservoir as described herein.
[0077] The presence of a bitumen zone may be determined by analysis
of fluid formation samples obtained from coring, sidewall coring
and whole core. Further, the bitumen zone may be inferred if the
DFA data identifies low asphaltene content mobile oil, whose
asphaltene onset pressure, as measured by a pressure volume
temperature (PVT) laboratory, is substantially the same, as the
reservoir pressure, as measured by a modular formation dynamics
tester (MDT).
[0078] If the analysis at block 270 classifies the gas chimney as
small, then at block 290, the additional DFA measurement stations
may be located at the base of the wellbore and/or reservoir. In one
scenario, a small gas chimney may be associated with a low rate of
gas charging into the reservoir. This process may cause asphaltenes
to aggregate. Further, the aggregated asphaltenes may form
clusters, which may be described by a model, such as the
Yen-Mullins model.
[0079] In one scenario, gravity may act upon the relatively large
and dense asphaltene clusters causing them to migrate predominantly
towards the base of the reservoir. In another, the migration
towards the base of the reservoir may be due the effect of
solubility, whereby the secondary gas charge may result in high
(GOR) gas content oils. The energy cost associated with these high
gas content oils mixing with the asphaltenes may cause phase
separation of the gas and asphaltenes. As more gas enters the top
of the reservoir, a descending gas-rich front may be created. This
descending gas-rich front may push the asphaltenes substantially
towards the base of the reservoir. Therefore, a tar mat may form at
the base of the reservoir as a result of a low rate gas charge
associated with a small gas chimney. In yet another scenario, an
insufficient amount of gas may entered the reservoir to form a tar
mat, however sufficient asphaltenes may still be concentrated at
the base of the reservoir to form a layer of heavy hydrocarbon
oil.
[0080] A tar mat may be too heavy to be sampled by a modular
formation dynamics tester (MFT); therefore its presence may have to
be determined by Ultraviolet (UV) illumination of fluid formation
samples obtained from coring, sidewall coring and whole core. Under
UV illumination the tar may appear dark, and below light oil, which
may appear bright under UV illumination.
[0081] The presence of heavy oil may be determined by the high
asphaltene content of fluid formation samples, which may be
obtained by a MFT and/or coring, sidewall coring and whole core.
Further, the presence of heavy oil may be determined by optical
density or photoacoustic analysis or other DFA techniques known to
a person of ordinary skill in the art.
[0082] If the analysis at block 270 is unable to classify the gas
chimney as either large or small, or the subterranean geological
feature is determined to be a salt welt at block 220, then
additional DFA measurement stations may be located, and additional
DFA fluid samples and data, may have to be obtained substantially
throughout the reservoir.
[0083] In one scenario, the additional DFA data may also include
one or more measurements of optical density, fluid color, fluid
fluorescence, fluid composition, GOR, temperature, pressure,
viscosity, fluid density, resistivity, pH or H.sub.2S levels,
concentrations of several alkane components and fractional amounts
of C.sub.1, C.sub.2, C.sub.3-C.sub.5, C.sub.6+, CO.sub.2, H.sub.2O,
and/or the like.
[0084] In one implementation, DFA may be further combined with core
analyses, mud logging analyses of drilled rock cuttings, basic
petrophysical logs (gamma-ray, resistivity, and neutron-density),
advanced petrophysical logs (elemental analysis logs, magnetic
resonance logs, and porosity logs), and mobility measurements from
a formation tester to further identify heavy hydroncarbons.
[0085] In one example, DFA data may be integrated with such
analysis to provide information of field-wide or localized fluid
instabilities, which may give rise to departures from the baseline
thermodynamic equilibrium state and may provide information for
field development planning. In another example, this may provided
information for developing a fluid model of the hydrocarbon
reservoir in real time. The fluid model may be used to understand
the properties and distribution of hydrocarbon fluids in a
reservoir formation.
[0086] In one implementation, the additional DFA fluid samples may
be in the same wellbore as the preliminary DFA fluid samples, such
that the additional DFA samples are at a different depth than the
preliminary DFA fluid samples. Thus, the additional DFA data may
correspond to the same wellbore as the preliminary DFA data. In
another implementation, the additional DFA fluid samples may be in
a different wellbore than the preliminary DFA fluid samples. Thus,
the additional DFA data may correspond to a different wellbore than
the preliminary DFA data in what is presumed to be the same
reservoir unit.
[0087] In sum, analyzing a reservoir using seismic data and DFA, as
described above, may provide information that can be used to
determine reservoir fluid geodynamics for a reservoir of interest.
For example, reservoir fluid geodynamics may be used to determine
whether there has been a geological occurrence associated with the
formation of heavy hydrocarbon, such as secondary gas charging, and
whether the reservoir has had time to equilibrate. In particular,
the integration of seismic data and DFA may be used to identify the
presence and location of heavy hydrocarbons.
[0088] As will be understood by a person of ordinary skill in the
art, combing the analysis of seismic data with DFA to identify gas
charging has many applications. For example, gas charging may be
associated with significant GOR gradients. Accordingly, this method
may be used to assess when large disequilibrium GOR gradients and
saturation pressure gradients may be present within the reservoir
and/or wellbore.
[0089] FIG. 3 illustrates a diagrammatical view of a 2D seismic
data plot in accordance with various implementations described
herein. The 2D seismic data may have been acquired before drilling
operations commenced as part of a 2D survey exploration process to
identify subterranean geological formations associated with
hydrocarbon deposits. Alternatively, the seismic data may have been
acquired as time-lapse seismic data. This time lapsed seismic data
may have been obtained from repeated seismic production surveys
over a producing hydrocarbon reservoir, and may be used to
determine changes within the reservoir. These changes may be the
result of hydrocarbon production, or injection of water and/or gas
into reservoir as part of a well development program. In one
implementation, the 2D seismic data may have been acquired as part
of the method 300 described herein.
[0090] The horizontal axis of the 2D seismic data plot represents
distance. The horizontal axis is further subdivided into
increments. The increments may make it easier for a user to
visualize the size of geological features depicted in the seismic
data, and/or may be representative of the seismic survey bucket or
bin size. The vertical axis represents the time it takes for the
reflections from a controlled energy source to reach a plurality of
receivers, from which it may be possible to estimate the depth of
the geological feature causing the reflections. The vertical axis
is also subdivided into increments, which may make it easier for a
user to visualize the depth of geological features depicted in the
seismic data.
[0091] As shown in FIG. 3, the seismic data plot may indicate the
presence of geological features associated with hydrocarbon
deposits. For example, the seismic data may contain bright spots,
which may indicate deposits of hydrocarbons or the presence of gas.
The bright spots may be the result of gas collecting in porous rock
formations, which may result in stronger seismic reflections
(contrast), than porous rock filled with a fluid such as water
and/or the adjacent rock formations. The acoustic contrast may be
the result of the reduced velocity of sound passing through porous
rock formations containing gas.
[0092] FIG. 3 further illustrates a gas chimney, the mixing of gas
with sedimentary layers and gas migration. The gas may migrate into
a reservoir already filled with black oil, which may have been
generated earlier as a result of a primary charge. As disclosed
herein, this may be referred to as secondary gas charging, and may
impact the distribution of asphaltenes within the reservoir
resulting in the formation of a bitumen zone, or a tar mat and/or
heavy oil. A gas chimney may be associated with a subsurface
migration (leakage) of gas from a poorly sealed hydrocarbon
accumulation. A gas chimney may be visible in seismic data as an
area of poor data quality, or may be visible as a push-down. A
push-down may be visible in the seismic data result due to the
rock-formations beneath the gas-bearing rock appearing deeper than
they are due to relatively low velocity of sound through these
gas-bearing rock formations above them.
Downhole Fluid Analysis
[0093] As mentioned above, DFA may be used in conjunction with
seismic analysis to identify variations in fluid properties of the
reservoir, which may in turn be used to detect heavy hydrocarbons,
compartmentalization and/or non-equilibrium hydrocarbon
distribution in the reservoir. In particular and as further
described below, DFA may provide, in real time or substantially
real time, geochemical information used to identify fluid
generation pathways, biodegradation, reservoir tops, fault, and cap
rock sealing properties, reservoir compartmentalization, fluid
associations, and/or the like for the reservoir of interest. In
such an implementation, DFA may be used to identify whether the
reservoir contains considered biogenic or thermogenic material.
[0094] As will be described with respect to FIGS. 5-6, DFA and may
provide hydrocarbon and non-hydrocarbon (CO.sub.2) composition
information to generate one or more models of reservoir fluid in
the reservoir of interest.
[0095] For example, measurements obtained using DFA at different
spatial locations in the reservoir may be contrasted with a
prediction model derived from these measurements. In one
implementation, agreement between the measurements and the model
may imply connectivity between the spatial locations, provided that
the fluid samples obtained from the spatial locations are in
thermodynamic equilibrium.
[0096] On the other hand, disagreement between the measurements and
the model may be further investigated to identify possible causes
of instability that preclude thermodynamic equilibrium. As noted
above, such causes may include geologic events that may alter the
reservoir structure after the primary charge, thermally mature
fluids that may arrive to the reservoir (secondary gas charging),
hydrocarbons that may escape via flow channels or a compromised cap
seal, ongoing and/or prior biodegradation at sufficiently low
temperature and mixing with biogenic methane, biogenic methane
arriving at the reservoir, water washing, and/or the like. In
addition, analyzed data from the DFA, and seismic surveys could be
used better understand RFG, and thereby to ascertain information
relating to migration of the reservoir fluids, origin of the
fluids, composition of the fluids, and/or the like.
[0097] Various implementations of well site systems described
herein may be used to employ an integration of DFA and Seismic
survey data, including a well site system that combines one or more
implementations discussed below with respect to FIGS. 5 and 6
beneath.
[0098] After conducting the DFA of one or more reservoir fluid
samples, the results of the DFA may be related to one or more
equation of state (EOS) models of the thermodynamic behavior of the
reservoir fluid in order to characterize the reservoir fluid at
different locations within the reservoir. In particular,
computer-based modeling and simulation techniques may use the EOS
models to estimate the fluid properties and/or behavior of
reservoir fluid within the reservoir. In one implementation, a
surface computing system, such as the electronics and processing
system 506 described below, may estimate the fluid properties
and/or fluid behavior using the EOS models. In such an
implementation, the surface computing system may perform the
estimations based on received DFA data. The received DFA data may
include measurements and/or calculations for optical density, fluid
fluorescence, fluid composition, the GOR, pressure, volume,
temperature, fluid density, fluid viscosity, and/or the like.
[0099] The EOS models may represent the phase behavior of the
reservoir fluid, and can be used to compute fluid properties, such
as: GOR, condensate-gas ratio (CGR), density of each phase,
volumetric factors and compressibility, heat capacity and
saturation pressure (bubble or dew point). Thus, the EOS models can
be solved to obtain saturation pressure at a given temperature.
Moreover, GOR, CGR, phase densities, and volumetric factors may be
byproducts of the EOS models. Transport properties, such as heat
capacity or viscosity, can be derived from properties obtained from
the EOS models, such as fluid composition.
[0100] Further, the EOS models can be extended with other reservoir
evaluation techniques for compositional simulation of flow and
production behavior of the petroleum fluid of the reservoir, as is
known in the art.
[0101] Further, an EOS that describes the distribution of a solid
fraction of the reservoir fluid (e.g., asphaltenes, resins, and/or
the like), may be used. In one implementation, such EOS may include
the Flory-Huggins-Zuo EOS, which may be used with the Yen-Mullins
model, which describes the physical nature of asphaltenes in crude.
Such a combination may be used to provide a description of a
baseline thermodynamic equilibrium state of a hydrocarbon column
that includes gas, liquid, and solid petroleum components.
[0102] In one implementation, an EOS model may predict
compositional gradients with depth that take into account the
impacts of gravitational forces, chemical forces, temperature
gradient, and/or the like. To calculate compositional gradients
with depth in a hydrocarbon reservoir, it may be assumed that the
reservoir fluids are connected (i.e., there is a lack of
compartmentalization) and in thermodynamic equilibrium. In
particular, it may be assumed that the reservoir fluids are in
thermodynamic equilibrium with substantially little adsorption
phenomena, addition of matter to the reservoir, pressure gradients
other than gravity, heat fluxes across system boundaries, and/or
chemical reactions in the reservoir.
[0103] Further, in order to identify variations in fluid properties
of the reservoir via a downhole fluid analysis (DFA), one or more
in situ reservoir fluid samples may be withdrawn using a downhole
tool, or formation tester disposed within a wellbore. In
particular, the reservoir fluid samples may be withdrawn from one
or more reference points disposed in the wellbore. A reference
point in the wellbore may be referred to as a measurement
station.
[0104] As further discussed above, the DFA may then be performed at
one or more measurement stations to determine one or more fluid
properties of the reservoir fluid, including, but not limited to,
gas-oil ratio (GOR), fluid composition (e.g., fractional amounts of
C.sub.1, C.sub.2, C.sub.3-C.sub.5, C.sub.6+, CO.sub.2, and the
like), acidity of the fluids (e.g., pH), fluorescence, optical
density, fluid resistivity, fluid density, and fluid viscosity. The
downhole tool may also provide measurements of pressure,
temperature, and mobility of the reservoir rock. As noted above,
variations in such fluid properties may indicate the presence of
heavy hydrocarbons, compartmentalization, and non-equilibrium
hydrocarbon distribution in the reservoir.
[0105] The DFA may be performed on the reservoir fluid samples
during drilling or thereafter. In one implementation, the reservoir
fluid samples may be analyzed downhole during a pause in drilling
operations, during which the downhole tool may acquire the fluid
samples and transmit results of the DFA to an acquisition unit at
the surface. In another implementation, the reservoir fluid samples
may be analyzed on the surface after the drilling operations have
finished, where the downhole tool may acquire the fluid samples and
subsequently transmit the fluid samples to the surface for other
fluid analysis to be performed. In yet another implementation, the
DFA may be performed in real-time or substantially real-time.
Downhole Fluid Analysis Systems
[0106] FIGS. 4 and 5 illustrate various implementations of well
site systems that may employ DFA systems and techniques. In one
implementation, FIG. 4 illustrates a rig 400 with a downhole tool
402 in accordance with implementations of various technologies and
techniques described herein. In particular, FIG. 4 depicts the
downhole tool 402 as being suspended from the rig 400 and into a
wellbore 404 via a drill string 406. The rig 400 may be similar to
the rig 128 of FIGS. 1.2-1.3. The downhole tool 400 may have a
drill bit 408 at its lower end that may be used to advance the
downhole tool 400 into the formation, and may also be used to form
the wellbore 404. The drill string 406 may be rotated by a rotary
table 410 energized by a powering means (not shown), where the
rotary table 410 may engage a Kelly joint 412 at the upper end of
the drill string 406. The drill string 406 may be suspended from a
hook 414 attached to a traveling block (not shown). In particular,
the drill string 406 may be suspended through the Kelly joint 412
and a rotary swivel 416 that permits rotation of the drill string
406 relative to the hook 414. The rig 400 may be a land-based
platform and derrick assembly used to form the wellbore 404 by
rotary drilling. However, in other implementations, the rig 400 may
be an offshore platform.
[0107] Drilling fluid or mud 418 may be stored in a pit 420 formed
at the well site. A pump 422 may deliver the drilling fluid 418 to
the interior of the drill string 406 via a port in the swivel 416,
inducing the drilling fluid to flow downwardly through the drill
string 406 as indicated by a directional arrow 424. The drilling
fluid may exit the drill string 406 via ports in the drill bit 408,
and then circulate upwardly through the region between the outside
of the drill string and the wall of the wellbore, called the
annulus, as indicated by directional arrows 426. The drilling fluid
may lubricate the drill bit 408 and carry formation cuttings up to
the surface as the fluid is returned to the pit 420 for
recirculation.
[0108] The downhole tool 402 may sometimes be referred to as a
bottom hole assembly (BHA), where the downhole tool 402 may be
positioned near the drill bit 408. The BHA of FIG. 4 may be similar
to the BHA of FIG. 1.2. The downhole tool 402 may include various
components with capabilities, such as measuring, processing, and
storing information, as well as communicating with the surface. A
telemetry device (not shown) also may be provided for communicating
with a surface unit (not shown).
[0109] The downhole tool 402 may also include a sampling system
428, where the sampling system 428 includes a fluid communication
module 430 and a sampling module 432. The modules may be housed in
a drill collar for performing various formation evaluation
functions, such as pressure testing, sampling, and/or the like. As
shown in FIG. 4, the fluid communication module 430 may be
positioned adjacent to the sampling module 432. However, the
position of the fluid communication module 430, as well as other
modules, may vary in other implementations. Additional devices,
such as pumps, gauges, sensor, monitors, and/or other devices
usable in downhole sampling and/or testing may also be used. The
additional devices may be incorporated into modules 430 and 432 or
disposed within separate modules included within the sampling
system 428.
[0110] The fluid communication module 430 may include a probe 434,
where the probe 434 may be positioned in a stabilizer blade or rib
436. The probe 434 may include one or more inlets for receiving
reservoir fluid and one or more flow lines (not shown) extending
into the downhole tool for passing fluids through the tool. In
another implementation, the probe 434 may include a single inlet
designed to direct reservoir fluid into a flow line within the
downhole tool. In yet another implementation, the probe may include
multiple inlets that may be used for focused sampling. In such
implementations, the probe may be connected to a sampling flow
line, as well as to guard flow lines. The probe 434 may be movable
between extended and retracted positions for selectively engaging a
wall 403 of the wellbore 404 and acquiring fluid samples from a
formation F. One or more setting pistons 438 may be provided to
assist in positioning the fluid communication module 430 against
the wellbore wall.
[0111] In another implementation, FIG. 5 illustrates a wireline
downhole tool 500 in accordance with implementations of various
technologies and techniques described herein. The downhole tool 500
may be suspended in a wellbore 502 from the lower end of a
multi-conductor cable 504 that is spooled on a winch at the
surface. The cable 504 may be communicatively coupled to an
electronics and processing system 506. The downhole tool 500 may
include an elongated body 508 that houses modules 510, 512, 514,
522, and 524. The modules 510, 512, 514, 522, and 524 may provide
various functionalities, including, but not limited to, fluid
sampling, pressure transient testing, fluid testing, operational
control, communication, and/or the like. The modules 510 and 512
may provide additional functionality, for example resistivity
measurements, operational control, communications, coring, imaging,
fluid analysis, and/or the like.
[0112] As shown in FIG. 5, the module 514 may be a communication
module and/or fluid analysis module 514 that has a selectively
extendable probe 516 and backup pistons 518 that are arranged on
opposite sides of the elongated body 508. The extendable probe 516
may be configured to selectively seal off or isolate selected
portions of the wall 503 of the wellbore 502 to fluidly couple to
the adjacent formation 520 and/or to draw fluid samples from the
formation 520. The probe 516 may include a single inlet or multiple
inlets designed for guarded or focused sampling. The reservoir
fluid may be expelled to the wellbore through a port in the body
508, or the reservoir fluid may be sent to one or more fluid
sampling modules 522 and 524. The fluid sampling modules 522 and
524 may include sample chambers that store the reservoir fluid. In
addition, the electronics and processing system 506 and/or a
downhole control system may be configured to control the extendable
probe assembly 516 and/or the drawing of a fluid sample from the
formation 520.
[0113] In yet another implementation, fluid from the reservoir of
interest may be passed by means of a primary flow line (not shown)
to the fluid analyzer module 514 for analysis. The fluid analyzer
module 514 may be employed to provide DFA measurements. For
example, the fluid analyzer module 514 may include an optical
spectrometer and/or a gas analyzer designed to measure properties
such as, optical density, fluid fluorescence, fluid composition,
the GOR, and/or the like. In particular, the spectrometer may
employ one or more optical filters to identify the color (i.e., the
optical density) of the reservoir fluid. Such color measurements
may be used for fluid identification, determination of asphaltene
content, and/or pH measurement. The reservoir fluids may exhibit
different colors because they have varying amounts of aromatics,
resins, and asphaltenes, each of which absorb light in the visible
and near-infrared ("NIR") spectra. Heavy oils may have higher
concentrations of aromatics, resins, and asphaltenes, which give
them dark colors. Light oils and condensate, on the other hand, may
have lighter, yellowish or bluish colors because they have lower
concentrations of aromatics, resins, and asphaltenes.
[0114] One or more additional measurement devices, such as
temperature sensors, pressure sensors, viscosity sensors, density
sensors, resistivity sensors, chemical sensors (e.g., for measuring
pH or H.sub.2S levels), and gas chromatographs may also be included
within the fluid analyzer module 514. In one implementation, the
fluid analyzer module 514 may measure absorption spectra and
translate such measurements into concentrations of several alkane
components and groups in the fluid sample. For example, the fluid
analyzer module 514 may determine the concentrations (e.g., weight
percentages) of carbon dioxide (CO.sub.2), methane (CH.sub.4),
ethane (C.sub.2H.sub.6), the C.sub.3-C.sub.5 alkane group, and the
lump of hexane and heavier alkane components (C.sub.6+).
[0115] The fluid analysis module 514 may also include a controller
(not shown), such as a microprocessor or control circuitry,
designed to calculate certain fluid properties based on the sensor
measurements. For example, the controller may calculate the GOR.
Further, the controller may govern sampling operations based on the
fluid measurements or properties. Moreover, the controller may be
disposed within another module of the downhole tool 500.
[0116] The downhole tools described above with respect to FIGS. 4
and 5 may also be referred to as formation testers. Besides the
implementations disclosed in FIGS. 4 and 5, other implementations
of well site systems employing DFA systems and techniques known to
those skilled in the art may be used. One example of a downhole
tool which may be used to employ such systems and techniques may
include the Modular Formation Dynamics Tester (MDT.RTM.), which is
a registered trademark of Schlumberger Technology Corporation.
Further, examples of a fluid communication module and/or fluid
analysis module may include the Composition Fluid Analyzer
(CFA.RTM.), Live Fluid Analyzer (LFA.RTM.), or the In Situ Fluid
Analyzer (IFA.RTM.), which are registered trademarks of
Schlumberger Technology Corporation.
[0117] In one implementation, a computing system associated with
the fluid communication module and/or fluid analysis module as
described above, such as the controller, may be used to determine
the properties of the reservoir fluid (e.g., optical color and
density and thereby asphaltene content, GOR, etc.) in substantially
real time. In another implementation, the computing system
associated with the fluid communication module and/or fluid
analysis module may operate in conjunction with a surface computing
system, such as the electronics and processing system 506 described
above.
[0118] Further, other well logging instruments may be used in
conjunction with the downhole tools described above, including
those used to measure electrical resistivity, compressional and
shear acoustic velocity, naturally occurring gamma radiation,
gamma-gamma Compton scatter formation density, formation neutron
hydrogen index (related to the fluid filled fractional volume of
pore space of the rock formations), and/or nuclear magnetic
resonance transverse and longitudinal relaxation time distribution
and diffusion constant. In such an implementation, the well logging
instruments, such as those that measure gamma radiation, may assist
in identifying potential areas of interest in the subterranean
formation. In particular, measurement stations may be assigned to
these potential areas for the withdrawal of reservoir fluid
samples.
[0119] As discussed above, a method for the integration of seismic
data with downhole fluid analysis to predict the location of heavy
hydrocarbon may be provided. The method may receive seismic data
for a hydrocarbon reservoir of interest. The method may identify
geological features associated with a secondary gas charge from the
seismic data, wherein the geological features are selected from a
group consisting of one or more gas chimneys, bright spots and salt
welds. The method may determine the proximity of the geological
features to the hydrocarbon reservoir of interest. The method may
receive preliminary downhole fluid analysis (DFA) data from
formations at or near the hydrocarbon reservoir of interest. The
method may analyze the preliminary DFA data to determine the
equilibrium state of the hydrocarbon reservoir and to confirm the
secondary gas charge in the hydrocarbon reservoir. The method may
determine whether to perform one or more additional DFA's.
[0120] In some implementations, the method may make a determination
of performing additional DFAs based on the proximity of the
geological features and the analysis of the preliminary DFA data.
The method may analyze the preliminary DFA data for fluid markers
associated with the secondary gas charge in the hydrocarbon
reservoir. The method may determine the proximity by determining
whether the geological features are within a predetermined
threshold spatial distance of the hydrocarbon reservoir. The method
may further comprise determining whether the geological features
are in fluid communication with the hydrocarbon reservoir. The
method may analyze the preliminary DFA data to determine if the
hydrocarbon reservoir is equilibrated using one or more equations
of state models of thermodynamic behavior of reservoir fluid. The
method may determine a geological age of the hydrocarbon reservoir
based on the analysis of the equilibrium state of the hydrocarbon
reservoir. The geological features may be gas chimneys and the
method may further comprise a determination of the size of the gas
chimneys. The method may perform one or more additional DFAs near
the top of the hydrocarbon reservoir if the gas chimneys are
classified as large. The method may perform one or more additional
DFAs near the bottom of the hydrocarbon reservoir if the gas
chimneys are classified as small. The method may determine the
classification of a gas chimney as large if it is greater than one
kilometer or comparable in size to the hydrocarbon reservoir, and
as small if it is determined to be less than five hundred meters or
less than one-third the size of the hydrocarbon reservoir. The
method may further comprise predicting locations of one or more
additional DFA stations based on the size of the gas chimneys. The
method may use one or more additional DFAs to determine whether the
hydrocarbon reservoir is in equilibrium or determine the presence
of heavy hydrocarbon associated with the secondary gas charge. The
method may use additional DFAs to determine the impact of heavy
hydrocarbon for the purpose of flow assurance, defining a
production strategy or field development planning. The method may
further comprise identifying flow barriers caused by precipitation
of solid particles or asphaltene from reservoir fluids. The method
may comprise processing the seismic data to enhance the
identification of one or more gas chimneys.
[0121] In some implementations, an information processing apparatus
for use in a computing system is provided, and includes various
means for receiving seismic data for a hydrocarbon reservoir of
interest; identifying geological features associated with a
secondary gas charge from the seismic data, wherein the geological
features are selected from a group consisting of one or more gas
chimneys, bright spots and salt welds; determining the proximity of
the geological features to the hydrocarbon reservoir of interest;
receiving preliminary downhole fluid analysis (DFA) data from
formations at or near the hydrocarbon reservoir of interest;
analyzing the preliminary DFA data to determine the equilibrium
state of the hydrocarbon reservoir and to confirm the secondary gas
charge in the hydrocarbon reservoir; and determining whether to
perform one or more additional DFA's.
[0122] In some implementations, a computing system is provided that
includes at least one processor, at least one memory, and one or
more programs stored in the at least one memory, wherein the
programs may include instructions, which when executed by the at
least one processor cause the computing system to receive seismic
data for a hydrocarbon reservoir of interest; identify geological
features associated with a secondary gas charge from the seismic
data, wherein the geological features are selected from a group
consisting of one or more gas chimneys, bright spots and salt
welds; determine the proximity of the geological features to the
hydrocarbon reservoir of interest; receive preliminary downhole
fluid analysis (DFA) data from formations at or near the
hydrocarbon reservoir of interest; analyze the preliminary DFA data
to determine the equilibrium state of the hydrocarbon reservoir and
to confirm the secondary gas charge in the hydrocarbon reservoir;
and determine whether to perform one or more additional DFA's.
[0123] In some implementations, a method may receive seismic data
for a hydrocarbon reservoir of interest. The method may identify
geological features associated with a secondary gas charge from the
seismic data, wherein the geological features are selected from a
group consisting of one or more gas chimneys, bright spots and salt
welds. The method may receive preliminary downhole fluid analysis
(DFA) data from formations at or near the hydrocarbon reservoir of
interest. The method may analyze the preliminary DFA data for fluid
markers associated with the secondary gas charge in the hydrocarbon
reservoir of interest. The method may further determine whether
secondary gas charge has occurred from the analysis of the
preliminary DFA data. The method may predict the presence of large
disequilibrium gas-oil-ratio (GOR) gradients and saturation
pressure gradients in the hydrocarbon reservoir based on the
determination of the secondary gas charge.
[0124] In some implementations, a non-transitory computer readable
medium having stored thereon a plurality of computer-executable
instructions which, when executed by a computer, cause the computer
to receive seismic data for a hydrocarbon reservoir of interest.
The computer-executable instructions may also cause the computer to
identify geological features in seismic data that are associated
with a secondary gas charge, wherein the geological features are
selected from a group consisting of one or more gas chimneys,
bright spots and salt welds. The computer-executable instructions
may further cause the computer to receive downhole fluid analysis
(DFA) data from formations at or near the hydrocarbon reservoir of
interest. The computer-executable instructions may further cause
the computer to analyze the DFA data to determine the equilibrium
state of the hydrocarbon reservoir and to confirm the secondary gas
charge in the hydrocarbon reservoir. The computer-executable
instructions may further cause the computer to predict one or more
locations of heavy hydrocarbon within the hydrocarbon reservoir of
interest based on the identified geological features.
[0125] The computer-executable instructions may also cause the
computer to analyze the DFA data for fluid markers associated with
the secondary gas charge in the hydrocarbon reservoir. Wherein, the
computer-executable instructions may also cause the computer to
determine whether the hydrocarbon reservoir is equilibrated based
on the DFA data. The computer-executable instructions may cause the
computer to determine the presence of large disequilibrium
gas-oil-ratio (GOR) gradients and saturation pressure gradients in
the hydrocarbon reservoir of interest. The computer-executable
instructions may also cause the computer to determine one or more
locations of heavy hydrocarbon within the hydrocarbon reservoir of
interest based on the size of the one or more gas chimneys.
Computing Systems
[0126] Implementations of various technologies described herein may
be operational with numerous general purpose or special purpose
computing system environments or configurations. Examples of
well-known computing systems, environments, or configurations that
may be suitable for use with the various technologies described
herein include, but are not limited to, personal computers, server
computers, hand-held or laptop devices, multiprocessor systems,
microprocessor-based systems, set top boxes, programmable consumer
electronics, network PCs, minicomputers, mainframe computers, smart
phones, smart watches, personal wearable computing systems
networked with other computing systems, tablet computers, and
distributed computing environments that include any of the above
systems or devices, and the like.
[0127] The various technologies described herein may be implemented
in the general context of computer-executable instructions, such as
program modules, being executed by a computer. Generally, program
modules include routines, programs, objects, components, data
structures, etc. that performs particular tasks or implement
particular abstract data types. While program modules may execute
on a single computing system, it should be appreciated that, in
some implementations, program modules may be implemented on
separate computing systems or devices adapted to communicate with
one another. A program module may also be some combination of
hardware and software where particular tasks performed by the
program module may be done either through hardware, software, or
both.
[0128] The various technologies described herein may also be
implemented in distributed computing environments where tasks are
performed by remote processing devices that are linked through a
communications network, e.g., by hardwired links, wireless links,
or combinations thereof. The distributed computing environments may
span multiple continents and multiple vessels, ships or boats. In a
distributed computing environment, program modules may be located
in both local and remote computer storage media including memory
storage devices.
[0129] FIG. 6 illustrates a schematic diagram of a computing system
600 in which the various technologies described herein may be
incorporated and practiced. Although the computing system 600 may
be a conventional desktop or a server computer, as described above,
other computer system configurations may be used.
[0130] The computing system 600 may include a central processing
unit (CPU) 630, a system memory 626, a graphics processing unit
(GPU) 631 and a system bus 628 that couples various system
components including the system memory 626 to the CPU 630. Although
one CPU is illustrated in FIG. 6, it should be understood that in
some implementations the computing system 600 may include more than
one CPU. The GPU 631 may be a microprocessor specifically designed
to manipulate and implement computer graphics. The CPU 630 may
offload work to the GPU 631. The GPU 631 may have its own graphics
memory, or may have access to a portion of the system memory 626.
As with the CPU 630, the GPU 631 may include one or more processing
units, and the processing units may include one or more cores. The
system bus 628 may be any of several types of bus structures,
including a memory bus or memory controller, a peripheral bus, and
a local bus using any of a variety of bus architectures. By way of
example, and not limitation, such architectures include Industry
Standard Architecture (ISA) bus, Micro Channel Architecture (MCA)
bus, Enhanced ISA (EISA) bus, Video Electronics Standards
Association (VESA) local bus, and Peripheral Component Interconnect
(PCI) bus also known as Mezzanine bus. The system memory 626 may
include a read-only memory (ROM) 612 and a random access memory
(RAM) 646. A basic input/output system (BIOS) 614, containing the
basic routines that help transfer information between elements
within the computing system 1300, such as during start-up, may be
stored in the ROM 612.
[0131] The computing system 600 may further include a hard disk
drive 650 for reading from and writing to a hard disk, a magnetic
disk drive 652 for reading from and writing to a removable magnetic
disk 656, and an optical disk drive 654 for reading from and
writing to a removable optical disk 658, such as a CD ROM or other
optical media. The hard disk drive 650, the magnetic disk drive
652, and the optical disk drive 654 may be connected to the system
bus 628 by a hard disk drive interface 656, a magnetic disk drive
interface 658, and an optical drive interface 650, respectively.
The drives and their associated computer-readable media may provide
nonvolatile storage of computer-readable instructions, data
structures, program modules and other data for the computing system
600.
[0132] Although the computing system 600 is described herein as
having a hard disk, a removable magnetic disk 656 and a removable
optical disk 658, it should be appreciated by those skilled in the
art that the computing system 600 may also include other types of
computer-readable media that may be accessed by a computer. For
example, such computer-readable media may include computer storage
media and communication media. Computer storage media may include
volatile and non-volatile, and removable and non-removable media
implemented in any method or technology for storage of information,
such as computer-readable instructions, data structures, program
modules or other data. Computer storage media may further include
RAM, ROM, erasable programmable read-only memory (EPROM),
electrically erasable programmable read-only memory (EEPROM), flash
memory or other solid state memory technology, CD-ROM, digital
versatile disks (DVD), or other optical storage, magnetic
cassettes, magnetic tape, magnetic disk storage or other magnetic
storage devices, or any other medium which can be used to store the
desired information and which can be accessed by the computing
system 600. Communication media may embody computer readable
instructions, data structures, program modules or other data in a
modulated data signal, such as a carrier wave or other transport
mechanism and may include any information delivery media. The term
"modulated data signal" may mean a signal that has one or more of
its characteristics set or changed in such a manner as to encode
information in the signal. By way of example, and not limitation,
communication media may include wired media such as a wired network
or direct-wired connection, and wireless media such as acoustic,
RF, infrared and other wireless media. The computing system 600 may
also include a host adapter 633 that connects to a storage device
635 via a small computer system interface (SCSI) bus, a Fiber
Channel bus, an eSATA bus, or using any other applicable computer
bus interface. Combinations of any of the above may also be
included within the scope of computer readable media.
[0133] A number of program modules may be stored on the hard disk
650, magnetic disk 656, optical disk 658, ROM 612 or RAM 616,
including an operating system 618, one or more application programs
620, program data 624, and a database system 648. The application
programs 620 may include various mobile applications ("apps") and
other applications configured to perform various methods and
techniques described herein. The operating system 618 may be any
suitable operating system that may control the operation of a
networked personal or server computer, such as Windows XP, Mac OS
X, Unix-variants (e.g., Linux and BSD), and the like.
[0134] A user may enter commands and information into the computing
system 600 through input devices such as a keyboard 662 and
pointing device 660. Other input devices may include a microphone,
joystick, game pad, satellite dish, scanner, or the like. These and
other input devices may be connected to the CPU 630 through a
serial port interface 642 coupled to system bus 628, but may be
connected by other interfaces, such as a parallel port, game port
or a universal serial bus (USB). A monitor 634 or other type of
display device may also be connected to system bus 628 via an
interface, such as a video adapter 632. In addition to the monitor
634, the computing system 600 may further include other peripheral
output devices such as speakers and printers.
[0135] Further, the computing system 600 may operate in a networked
environment using logical connections to one or more remote
computers 674. The logical connections may be any connection that
is commonplace in offices, enterprise-wide computer networks,
intranets, and the Internet, such as local area network (LAN) 656
and a wide area network (WAN) 666. The remote computers 674 may be
another a computer, a server computer, a router, a network PC, a
peer device or other common network node, and may include many of
the elements describes above relative to the computing system 600.
The remote computers 674 may also each include application programs
670 similar to that of the computer action function.
[0136] When using a LAN networking environment, the computing
system 600 may be connected to the local network 676 through a
network interface or adapter 644. When used in a WAN networking
environment, the computing system 600 may include a router 664,
wireless router or other means for establishing communication over
a wide area network 666, such as the Internet. The router 664,
which may be internal or external, may be connected to the system
bus 628 via the serial port interface 652. In a networked
environment, program modules depicted relative to the computing
system 600, or portions thereof, may be stored in a remote memory
storage device 672. It will be appreciated that the network
connections shown are merely examples and other means of
establishing a communications link between the computers may be
used.
[0137] The network interface 644 may also utilize remote access
technologies (e.g., Remote Access Service (RAS), Virtual Private
Networking (VPN), Secure Socket Layer (SSL), Layer 2 Tunneling
(L2T), or any other suitable protocol). These remote access
technologies may be implemented in connection with the remote
computers 674.
[0138] It should be understood that the various technologies
described herein may be implemented in connection with hardware,
software or a combination of both. Thus, various technologies, or
certain aspects or portions thereof, may take the form of program
code (i.e., instructions) embodied in tangible media, such as
floppy diskettes, CD-ROMs, hard drives, or any other
machine-readable storage medium wherein, when the program code is
loaded into and executed by a machine, such as a computer, the
machine becomes an apparatus for practicing the various
technologies. In the case of program code execution on programmable
computers, the computing device may include a processor, a storage
medium readable by the processor (including volatile and
non-volatile memory and/or storage elements), at least one input
device, and at least one output device. One or more programs that
may implement or utilize the various technologies described herein
may use an application programming interface (API), reusable
controls, and the like. Such programs may be implemented in a high
level procedural or object oriented programming language to
communicate with a computer system. However, the program(s) may be
implemented in assembly or machine language, if desired. In any
case, the language may be a compiled or interpreted language, and
combined with hardware implementations. Also, the program code may
execute entirely on a user's computing device, on the user's
computing device, as a stand-alone software package, on the user's
computer and on a remote computer or entirely on the remote
computer or a server computer.
[0139] The system computer 600 may be located at a data center
remote from the survey region. The system computer 600 may be in
communication with the receivers (either directly or via a
recording unit, not shown), to receive signals indicative of the
reflected seismic energy. These signals, after conventional
formatting, and other initial processing, may be stored by the
system computer 600 as digital data in the disk storage for
subsequent retrieval and processing in the manner described above.
In one implementation, these signals and data may be sent to the
system computer 600 directly from sensors, such as geophones,
hydrophones and the like. When receiving data directly from the
sensors, the system computer 600 may be described as part of an
in-field data processing system. In another implementation, the
system computer 600 may process seismic data already stored in the
disk storage. When processing data stored in the disk storage, the
system computer 600 may be described as part of a remote data
processing center, separate from data acquisition. The system
computer 600 may be configured to process data as part of the
in-field data processing system, the remote data processing system
or a combination thereof.
[0140] Those with skill in the art will appreciate that any of the
listed architectures, features or standards discussed above with
respect to the example computing system 1300 may be omitted for use
with a computing system used in accordance with the various
embodiments disclosed herein because technology and standards
continue to evolve over time.
[0141] Of course, many processing techniques for collected data,
including one or more of the techniques and methods disclosed
herein, may also be used successfully with collected data types
other than seismic data. While certain implementations have been
disclosed in the context of seismic data collection and processing,
those with skill in the art will recognize that one or more of the
methods, techniques, and computing systems disclosed herein can be
applied in many fields and contexts where data involving structures
arrayed in a three-dimensional space or subsurface region of
interest may be collected and processed, e.g., medical imaging
techniques such as tomography, ultrasound, MRI and the like for
human tissue; radar, sonar, and LIDAR imaging techniques; and other
appropriate three-dimensional imaging problems.
[0142] While the foregoing is directed to implementations of
various technologies described herein, other and further
implementations may be devised without departing from the basic
scope thereof. Although the subject matter has been described in
language specific to structural features or methodological acts, it
is to be understood that the subject matter defined in the appended
claims is not limited to the specific features or acts described
above. Rather, the specific features and acts described above are
disclosed as example forms of implementing the claims.
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