U.S. patent application number 16/840903 was filed with the patent office on 2021-10-07 for three-component seismic data processing and interpretation method for seismic while fracking.
The applicant listed for this patent is Saudi Arabian Oil Company. Invention is credited to Yue Du, Tong Wang Fei, Yujin Liu, Yi Luo.
Application Number | 20210311216 16/840903 |
Document ID | / |
Family ID | 1000004796909 |
Filed Date | 2021-10-07 |
United States Patent
Application |
20210311216 |
Kind Code |
A1 |
Liu; Yujin ; et al. |
October 7, 2021 |
THREE-COMPONENT SEISMIC DATA PROCESSING AND INTERPRETATION METHOD
FOR SEISMIC WHILE FRACKING
Abstract
Systems and methods include a computer-implemented method for
presenting interpretation results of synchronized seismic data and
fracture treatment times. A standard format seismic dataset of
sensor readings obtained from a three-component sensor is
generated. Coordinates and recording times corresponding to the
sensor readings are added to the standard format seismic dataset.
Synchronized seismic data is generated from the standard format
seismic dataset by synchronizing seismic recording times with
fracture treatment times. Quality-controlled synchronized seismic
data is generated by removing dead traces and abnormal data samples
from the synchronized seismic data. A time-frequency analysis is
performed on the quality-controlled synchronized seismic data,
including performing short-time Fourier transforms to analyze
variations of Fourier spectra over time. Based on the
time-frequency analysis, resonance frequencies are extracted from
each frequency spectrum at different time samples. Interpretation
results based are presented to a user.
Inventors: |
Liu; Yujin; (Beijing,
CN) ; Du; Yue; (Beijing, CN) ; Fei; Tong
Wang; (Dhahran, SA) ; Luo; Yi; (Dhahran,
SA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Saudi Arabian Oil Company |
Dhahran |
|
SA |
|
|
Family ID: |
1000004796909 |
Appl. No.: |
16/840903 |
Filed: |
April 6, 2020 |
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G01V 1/345 20130101;
H04L 67/12 20130101; G01V 1/32 20130101 |
International
Class: |
G01V 1/32 20060101
G01V001/32; G01V 1/34 20060101 G01V001/34 |
Claims
1. A computer-implemented method, comprising: generating a standard
format seismic dataset of sensor readings obtained from a
three-component sensor comprising an x-component, a y-component,
and a z-component of wave motions of guided waves propagated along
a wellbore; adding, to the standard format seismic dataset, x/y/z
coordinates and recording times corresponding to the sensor
readings; generating, using the standard format seismic dataset of
sensor readings, synchronized seismic data from the standard format
seismic dataset by synchronizing seismic recording times with
fracture treatment times; generating quality-controlled
synchronized seismic data by removing, from the synchronized
seismic data, dead traces and abnormal data samples; performing a
time-frequency analysis on the quality-controlled synchronized
seismic data, including performing short-time Fourier transforms to
analyze variations of Fourier spectra over time; extracting, at
different time samples and based on the time-frequency analysis,
resonance frequencies from each frequency spectrum, including
increasing amplitudes of weak frequency components of the
quality-controlled synchronized seismic data using a slide
frequency window, including applying automatic gain control (AGC)
to frequency spectra, stacking the frequency spectra with different
intervals, and picking a frequency interval with a highest-stacking
energy as an estimated resonance frequency; and presenting, to a
user, interpretation results based on the extracting.
2. The computer-implemented method of claim 1, wherein the
three-component sensor is located outside of a wellhead.
3. The computer-implemented method of claim 1, wherein generating
the standard format seismic dataset includes: receiving raw data
corresponding to the sensor readings obtained by the
three-component sensor; and generating the standard format seismic
dataset by converting the raw data corresponding to the sensor
readings into a standard format.
4. The computer-implemented method of claim 3, wherein the standard
format is a Society of Exploration Geophysicists (SEG) Y (SEGY)
format.
5. The computer-implemented method of claim 4, wherein adding the
coordinates and the recording times includes updating SEGY headers
of the standard format seismic dataset with the coordinates and
recording times.
6. The computer-implemented method of claim 1, wherein presenting
the interpretation results based on the extracting includes
generating a histogram of fracture conductivity.
7. The computer-implemented method of claim 1, wherein the sensor
readings obtained from the three-component sensor include signals
less than 10 Hertz.
8. A non-transitory, computer-readable medium storing one or more
instructions executable by a computer system to perform operations
comprising: generating a standard format seismic dataset of sensor
readings obtained from a three-component sensor comprising an
x-component, a y-component, and a z-component of wave motions of
guided waves propagated along a wellbore; adding, to the standard
format seismic dataset, coordinates and recording times
corresponding to the sensor readings; generating, using the
standard format seismic dataset of sensor readings, synchronized
seismic data from the standard format seismic dataset by
synchronizing seismic recording times with fracture treatment
times; generating quality-controlled synchronized seismic data by
removing, from the synchronized seismic data, dead traces and
abnormal data samples; performing a time-frequency analysis on the
quality-controlled synchronized seismic data, including performing
short-time Fourier transforms to analyze variations of Fourier
spectra over time; extracting, at different time samples and based
on the time-frequency analysis, resonance frequencies from each
frequency spectrum, including increasing amplitudes of weak
frequency components of the quality-controlled synchronized seismic
data using a slide frequency window, including applying automatic
gain control (AGC) to frequency spectra, stacking the frequency
spectra with different intervals, and picking a frequency interval
with a highest-stacking energy as an estimated resonance frequency;
and presenting, to a user, interpretation results based on the
extracting.
9. The non-transitory, computer-readable medium of claim 8, wherein
the three-component sensor is located outside of a wellhead.
10. The non-transitory, computer-readable medium of claim 8,
wherein generating the standard format seismic dataset includes:
receiving raw data corresponding to the sensor readings obtained by
the three-component sensor; and generating the standard format
seismic dataset by converting the raw data corresponding to the
sensor readings into a standard format.
11. The non-transitory, computer-readable medium of claim 10,
wherein the standard format is a Society of Exploration
Geophysicists (SEG) Y (SEGY) format.
12. The non-transitory, computer-readable medium of claim 11,
wherein adding the coordinates and the recording times includes
updating SEGY headers of the standard format seismic dataset with
the coordinates and recording times.
13. The non-transitory, computer-readable medium of claim 8,
wherein presenting the interpretation results based on the
extracting includes generating a histogram of fracture
conductivity.
14. The non-transitory, computer-readable medium of claim 8,
wherein the sensor readings obtained from the three-component
sensor include signals less than 10 Hertz.
15. A computer-implemented system, comprising: one or more
processors; and a non-transitory computer-readable storage medium
coupled to the one or more processors and storing programming
instructions for execution by the one or more processors, the
programming instructions instructing the one or more processors to
perform operations comprising: generating a standard format seismic
dataset of sensor readings obtained from a three-component sensor
comprising an x-component, a y-component, and a z-component of wave
motions of guided waves propagated along a wellbore; adding, to the
standard format seismic dataset, coordinates and recording times
corresponding to the sensor readings; generating, using the
standard format seismic dataset of sensor readings, synchronized
seismic data from the standard format seismic dataset by
synchronizing seismic recording times with fracture treatment
times; generating quality-controlled synchronized seismic data by
removing, from the synchronized seismic data, dead traces and
abnormal data samples; performing a time-frequency analysis on the
quality-controlled synchronized seismic data, including performing
short-time Fourier transforms to analyze variations of Fourier
spectra over time; extracting, at different time samples and based
on the time-frequency analysis, resonance frequencies from each
frequency spectrum, including increasing amplitudes of weak
frequency components of the quality-controlled synchronized seismic
data using a slide frequency window, including applying automatic
gain control (AGC) to frequency spectra, stacking the frequency
spectra with different intervals, and picking a frequency interval
with a highest-stacking energy as an estimated resonance frequency;
and presenting, to a user, interpretation results based on the
extracting.
16. The computer-implemented system of claim 15, wherein the
three-component sensor is located outside of a wellhead.
17. The computer-implemented system of claim 15, wherein generating
the standard format seismic dataset includes: receiving raw data
corresponding to the sensor readings obtained by the
three-component sensor; and generating the standard format seismic
dataset by converting the raw data corresponding to the sensor
readings into a standard format.
18. The computer-implemented system of claim 17, wherein the
standard format is a Society of Exploration Geophysicists (SEG) Y
(SEGY) format.
19. The computer-implemented system of claim 18, wherein adding the
coordinates and the recording times includes updating SEGY headers
of the standard format seismic dataset with the coordinates and
recording times.
20. The computer-implemented system of claim 15, wherein presenting
the interpretation results based on the extracting includes
generating a histogram of fracture conductivity.
Description
BACKGROUND
[0001] The present disclosure applies to techniques for monitoring
fracturing (or fracking) processes.
[0002] Seismic While Fracking (SWF) is a seismic technique that is
used to evaluate the quality of hydraulic fractures during
fracking. Conventional SWF techniques can include microseismic
monitoring methods that may require many sensors. The conventional
techniques may also require significant processing time and
computing resources, and may be labor intensive.
SUMMARY
[0003] The present disclosure describes techniques that can be used
for generating interpretation results based on synchronized seismic
data and fracture treatment times.
[0004] In some implementations, a computer-implemented method
includes the following. A standard format seismic dataset of sensor
readings obtained from a three-component sensor is generated.
Coordinates and recording times corresponding to the sensor
readings are added to the standard format seismic dataset.
Synchronized seismic data is generated from the standard format
seismic dataset by synchronizing seismic recording times with
fracture treatment times. Quality-controlled synchronized seismic
data is generated by removing dead traces and abnormal data samples
from the synchronized seismic data. A time-frequency analysis is
performed on the quality-controlled synchronized seismic data,
including performing short-time Fourier transforms to analyze
variations of Fourier spectra over time. Based on the
time-frequency analysis, resonance frequencies are extracted from
each frequency spectrum at different time samples. Interpretation
results based are presented to a user.
[0005] The previously described implementation is implementable
using a computer-implemented method; a non-transitory,
computer-readable medium storing computer-readable instructions to
perform the computer-implemented method; and a computer-implemented
system including a computer memory interoperably coupled with a
hardware processor configured to perform the computer-implemented
method/the instructions stored on the non-transitory,
computer-readable medium.
[0006] The subject matter described in this specification can be
implemented in particular implementations, so as to realize one or
more of the following advantages. First, the techniques described
in the present disclosure can provide an improvement over
conventional techniques that use body waves that are scattered from
the fractures. Body waves can tend to be weak and thus can require
wide-azimuth and dense receiver arrays to reconstruct the wave
field. By comparison, the techniques described in the present
disclosure can instead use tube waves, which propagate within the
wellbore with less energy dissipation, thus requiring fewer
receivers. Second, one or a few three-component sensors can be
determined to be effective at recording the reflected tube waves.
Third, the techniques of the present disclosure can reduce
computational, manpower, and delivery costs. Fourth, the techniques
of the present disclosure can provide an efficient and reliable
evaluation of fracturing quality using reflected tube waves.
[0007] The details of one or more implementations of the subject
matter of this specification are set forth in the Detailed
Description, the accompanying drawings, and the claims. Other
features, aspects, and advantages of the subject matter will become
apparent from the Detailed Description, the claims, and the
accompanying drawings.
DESCRIPTION OF DRAWINGS
[0008] FIG. 1 is a map of a geometry of a well trajectory for a
seismic while fracturing test, according to some implementations of
the present disclosure.
[0009] FIGS. 2A and 2B are diagrams showing raw data for sensor
recordings, according to some implementations of the present
disclosure.
[0010] FIGS. 3A and 3B are plots showing a time-frequency analysis
on seismic data, according to some implementations of the present
disclosure.
[0011] FIGS. 4A-4C are diagrams showing an interpretation of
seismic data acquired at a 15th stage of fracturing, according to
some implementations of the present disclosure.
[0012] FIG. 5 is a flowchart of an example of a method for
generating interpretation results based on synchronized seismic
data and fracture treatment times, according to some
implementations of the present disclosure.
[0013] FIG. 6 is a block diagram illustrating an example computer
system used to provide computational functionalities associated
with described algorithms, methods, functions, processes, flows,
and procedures as described in the present disclosure, according to
some implementations of the present disclosure.
[0014] Like reference numbers and designations in the various
drawings indicate like elements.
DETAILED DESCRIPTION
[0015] The following detailed description describes techniques for
generating interpretation results based on synchronized seismic
data and fracture treatment times. Various modifications,
alterations, and permutations of the disclosed implementations can
be made and will be readily apparent to those of ordinary skill in
the art, and the general principles defined may be applied to other
implementations and applications, without departing from scope of
the disclosure. In some instances, details unnecessary to obtain an
understanding of the described subject matter may be omitted so as
to not obscure one or more described implementations with
unnecessary detail and inasmuch as such details are within the
skill of one of ordinary skill in the art. The present disclosure
is not intended to be limited to the described or illustrated
implementations, but to be accorded the widest scope consistent
with the described principles and features.
[0016] Some conventional hydraulic impedance testing or similar
techniques may use water hammer signals. However, these techniques
can be limited to wellhead pressure time series that are sampled no
faster than 1 Hertz (Hz). Other techniques can be used to analyze
wave reflections from fractures in the context of borehole
acoustics. High-frequency signals, for example above 1 kilohertz
(kHz), that are generated by borehole logging tools can be used to
image fractures and porous layers. In contrast, the techniques
described in the present disclosure can use low-frequency signals
less than approximately 10 Hz. Conventional techniques that are
used to infer the hydraulic fracture conductivity can rely on the
installation of one-component sensors on the surface. The sensors
can be installed near, at, or contacting the fluid inside the
wellhead to acquire the tube waves. In some implementations,
three-component sensors contacting the outside of the wellhead can
be installed. Since tube waves are guided waves propagating along
the wellbore, the wave motion includes x-, y-, and z-components.
These components can be fully captured by one or more
three-component sensors. As such, the techniques described in the
present disclosure can utilize more comprehensive data to infer
more accurate and robust subsurface fracture information as
compared with conventional acquisition techniques using
single-component sensors.
[0017] In some implementations, techniques can be used to infer
fracture connectivity using tube waves reflected from the hydraulic
fractures during the fracturing treatment. These techniques only
need to process and interpret several channels of seismic data
recorded by a three-component sensor contacting with the outside of
the wellhead, for example. The interpreted results can be shown to
provide a good match with fracturing treatment curves. The
techniques can be used in real-time monitoring of hydraulic
fracturing. The term real-time can correspond to events that occur
within a specified period of time, for example, within hours,
minutes, or seconds.
[0018] A main objective of Seismic While Fracking (SWF) systems is
to provide real-time hydraulic fracture information to aid in
decision-making during the fracking process. During conventional
fracking operations, engineers may mainly rely on previous fracking
information, ongoing fracking measurements, and well loggings that
are obtained during intervals of different stages of fracking. This
type of information is not available in real time, a situation that
prevents engineers from making prompt decisions. Typical
microseismic monitoring methods can require many sensors, which can
add significant cost, time, and labor needed to process and
interpret the data. The present disclosure presents cost-effective
techniques for processing and interpreting seismic data collected,
for example, by a single three-component sensor contacting the
outside of a wellhead. The output of these techniques can include
real-time conductivity parameters of hydraulic fractures.
Data Acquisition
[0019] FIG. 1 is a map of a geometry 100 of a well trajectory for a
seismic while fracturing test, according to some implementations of
the present disclosure. To obtain the geometry 100, a single
three-component sensor can be placed on the surface, contacting the
outside of the wellhead 102. The sensor can be connected with
devices for data storage and battery. Since the sensor has only
three channels, the data size can be small even though data
recording might last several days. In this way, data processing and
interpretation can be part of real-time monitoring of hydraulic
fractures. The geometry 100 depicted in FIG. 1 is relative to x-,
y-, and z-components given, for example, by an east direction 104,
a north direction 106, and a depth direction 108. The geometry 100
can include 26 sections 110 having a geometry midpoint 112. In an
example, the geometry midpoint 112 can be between the 13.sup.th and
14.sup.th segments of the 26 sections 110.
[0020] The three-component sensor can be designed to be broadband
sensitive. The incident tube waves can be stimulated by pressure
pulse in a wellbore, microseismic events, or a significant rapid
fluid flow rate change such as water hammer. A water hammer can be
caused, for example, by rapid injection or release of a slug of
fluid or a sudden flow. The resulting stimulated tube waves can
travel in the wellbore as guided waves (for example, as Stoneley
waves). These guided waves can be converted into Krauklis waves
when the waves encounter the boundary of the wellbore and
fractures. Within the fractures, the Krauklis waves can reflect
back and forth along major fracture connections, forming a standing
wave with low attenuation. The Krauklis waves can be converted back
into guided waves within the wellbore. Finally the guided waves can
be reflected back to the surface and recorded by the surface
sensor.
[0021] FIGS. 2A and 2B are diagrams showing raw data 200 for sensor
recordings, according to some implementations of the present
disclosure. FIG. 2A shows a three-component time series of the raw
data that includes traces from x-, y-, and z-components 200a, 200b,
and 200c, respectively. The components 200a-200c show signals
plotted in FIG. 2A relative to amplitude 202 and time 204, where
the signals correspond to sequential sections 206 of the wellbore
(for example, corresponding to the sections 110).
[0022] FIG. 2B shows corresponding Fourier spectra for sensor
recordings of x-, y-, and z-components 200a-200c, respectively, at
three channels. The spectra include features of equidistant spectra
lining up at a frequency 208 of 150 Hz. After overlaying the time
windows of fracturing stages, the data can show consistent patterns
at different stages. The plots for x-, y-, and z-components
200a-200c are plotted relative to amplitude 202, time 204 (hours),
frequency 208 (Hz), and amplitude 210.
Data Processing Workflow
[0023] To estimate the fracture conductivity from the reflected
tube waves, the raw data can be analyzed and processed. In some
implementations, a data processing workflow for estimating the
fracture conductivity can include the following. First, in a field
data decode step, raw data can be downloaded from the sensor and
converted to a standard format such as a Society of Exploration
Geophysicists (SEG) Y (SEGY) format. Second, in an SEGY header edit
step, SEGY headers including coordinates and recording times can be
added to SEGY files. Third, in a time synchronization step, seismic
recording times can be synchronized with the time of fracture
treatments. Fourth, in a data quality control step, dead traces and
abnormal data samples can be removed. Fifth, in a time-frequency
analysis step, short-time Fourier transforms can be used to analyze
the variation of the Fourier spectra over time. Sixth, an
extraction of resonance frequency step can occur. For example, at
every time sample, the resonance frequencies can be extracted from
a frequency spectrum by stacking the spectrum with different
frequency intervals. The resonance frequency is the frequency
interval which gives the strongest stacking power.
[0024] FIGS. 3A and 3B are plots 300a and 300b showing a
time-frequency analysis on seismic data, according to some
implementations of the present disclosure. The data processing
results are shown for the seismic data acquired at the 13th stage
of fracturing, for example. FIG. 3A shows three-component data,
including the x-, y- and z-component data at the 13th stage of
hydraulic fracturing, plotted relative to an amplitude axis 302 and
a time axis 304. The plots 300a can be obtained, for example, by
applying short-time Fourier transform to the three-component data
and stacking their Fourier spectra. The plot 300 includes
amplitudes for an x-component 306, a y-component 308, and a
z-component 310. FIG. 3B shows the final time-frequency spectrum
plotted relative to a frequency axis 312 and the time axis 304. The
information can be recorded at a high rate, but analysis can focus
on signals less than 10 Hz.
Data Interpretation
[0025] FIGS. 4A-4C are diagrams showing an interpretation of
seismic data acquired at a 15th stage of fracturing, according to
some implementations of the present disclosure. FIG. 4A shows a
time-frequency spectrum 400, including showing the data
interpretation results. The behavior of resonance frequencies 404
(for example, in Hz) plotted relative to a time axis 402 can be
consistent with the pressure curves. Since newly-generated
fractures release the stress in the stratum, the generation of
fractures can be indicated by the pressure curve, where the
pressure decreases rapidly with a stable injection of slurry. From
the time-frequency spectrum, it can be determined that new
fluid-filled cracks can generate new resonance frequencies. The
reason for this is that the resonances originate from
back-and-forth reflections of Krauklis waves within the space
trapped by the perforation point and fracture tips.
[0026] FIG. 4B shows an interpretation result 406 relative to a
time axis 408 and a fractures scale 410. For example, the resonance
frequencies can be extracted from the time-spectrum, and the
histogram of fracture conductivity can be calculated as shown in
FIG. 4B.
[0027] FIG. 4C shows fracturing treatment curves 412. The trend of
the histograms included in the fracturing treatment curves 412 is
consistent with the pressure curves. To explain the interpretation
result in detail, the 15th fracturing stage can be divided into
three phases.
[0028] During a perforation stage 414 (from time A 416 to time B
418), a slurry with a low sand concentration can be been pumped
into the coiled tubing. Sand can be injected into the target
reservoir through a nozzle. In this phase, there are mainly natural
fractures in the formations, thus the fracture conductivity is
relatively low.
[0029] During a fracturing phase 420 (from time B 418 to time C
422), the fracturing treatment can start at the time B 418, and the
pressure can increase with the slurry injection. The pressure
begins to decrease when some fractures are generated. To generate
more fractures, several rounds of slurry injections are often
needed. In this example, there are five injection times. The
interpretation result confirms that the fracture conductivity
increases gradually along with the injection procedure.
[0030] During a fracturing phase 424 (from time C 422 to time D
426), the drainage volume and the connecting pipe pressure
decreases, while the amount of sand concentration increases. The
interpretation result shows that the hydraulic fractures in the
formation gradually decrease when the fracturing pressure is
reduced even though the sand-carrying fluid is gradually injected.
Finally, the fracture conductivity tends to be stable as more and
more proppant is injected into the formation.
[0031] The fracturing treatment curves 412 include line plots for a
connecting pipe pressure 428, an annulus pressure 430, a slurry
rate 432, a sand concentration 434, and an added liquid 436.
Pressures such as the connecting pipe pressure 428 and the annulus
pressure 430 can be measured in megapascal (MPa), for example.
Slurry rates such as the slurry rate 432 can be measured in cubic
meters per minute (m.sup.3/min), for example. Sand concentrations
such as the sand concentration 434 can be measured in kilograms per
cubic meter (kg/m.sup.3), for example. The added liquid 436 can be
measured in liters per minute (L/min), for example. Line plots 428,
430, 432, 434, and 436 are plotted relative to their own units.
[0032] The interpretation results can show that the fracture
conductivity extracted from resonance frequencies has a high
correlation with the fracturing treatment curves, which can provide
valuable information about fracturing quality in real time.
Moreover, the fracturing pressure boosting time of section 13 can
be performed in a short period. The conductivity factor that is
calculated from the resonance frequencies can show stable fracture
distribution during the whole fracturing treatment. Conductivity
histograms at different stages can also be compared to provide an
evaluation of fracturing quality during the entire hydraulic
fracture treatment.
[0033] In some implementations, processing can be modified to
account for contamination. For example, during data acquisition,
the reflected tube waves may be contaminated by ambient noise (such
as traffic noise, human activity, and pump noise). These
contaminants can be accounted for in the calculations and the
resulting plots.
[0034] FIG. 5 is a flowchart of an example of a method 500 for
generating interpretation results based on synchronized seismic
data and fracture treatment times, according to some
implementations of the present disclosure. For clarity of
presentation, the description that follows generally describes
method 500 in the context of the other figures in this description.
However, it will be understood that method 500 can be performed,
for example, by any suitable system, environment, software, and
hardware, or a combination of systems, environments, software, and
hardware, as appropriate. In some implementations, various steps of
method 500 can be run in parallel, in combination, in loops, or in
any order.
[0035] At 502, a standard format seismic dataset of sensor readings
obtained from a three-component sensor is generated. The sensor
readings obtained from the three-component sensor include signals
can be less than 10 Hertz, for example. The three-component sensor
can be located outside of a wellhead, such as the wellhead 102. The
sensor readings can be obtained during fracturing that occurs in a
well according to the geometry 100 of the well trajectory for a
seismic while fracturing test. Generating the standard format
seismic dataset includes can include, for example, receiving raw
data corresponding to the sensor readings obtained by the
three-component sensor and generating the standard format seismic
dataset by converting the raw data corresponding to the sensor
readings into a standard format. The standard format can be a
Society of Exploration Geophysicists (SEG) Y (SEGY) format, for
example. From 502, method 500 proceeds to 504.
[0036] At 504, coordinates and recording times corresponding to the
sensor readings are added to the standard format seismic dataset.
As an example, adding the coordinates and the recording times can
include updating SEGY headers of the standard format seismic
dataset with the coordinates and recording times. From 504, method
500 proceeds to 506.
[0037] At 506, synchronized seismic data is generated from the
standard format seismic dataset by synchronizing seismic recording
times with fracture treatment times. Since the sensor is placed at
the surface, the synchronization process is simple and can be
performed by setting both the recording and fracturing time to be
GPS (Global Positioning System) time. From 506, method 500 proceeds
to 508.
[0038] At 508, quality-controlled synchronized seismic data is
generated by removing dead traces and abnormal data samples from
the synchronized seismic data. The anomalous data can be detected
automatically according to their statistics attributes, including
but not limited to the mean, variance, skewness, and kurtosis. From
508, method 500 proceeds to 510.
[0039] At 510, a time-frequency analysis is performed on the
quality-controlled synchronized seismic data, including performing
short-time Fourier transforms to analyze variations of Fourier
spectra over time. The procedure for computing short-time Fourier
transforms is to divide a longer time signal into shorter segments
of equal length and then compute the Fourier transform separately
on each shorter segment. Other time-frequency analysis tools, such
as Gabor transforms and S transforms, can be used. From 510, method
500 proceeds to 512.
[0040] At 512, based on the time-frequency analysis, resonance
frequencies are extracted at each time sample from the
time-frequency spectra. For each time sample, the procedure
includes applying Automatic Gain Control (AGC) to the frequency
spectra, stacking the frequency spectra with different intervals,
and finally picking the frequency interval with the
highest-stacking energy as the estimated resonance frequency, where
the AGC is applied to increase the amplitude of weak frequency
components using a slide frequency window. This procedure is
performed for all time samples. From 512, method 500 proceeds to
514.
[0041] At 514, interpretation results based on the extracting are
presented to a user. Presenting the interpretation results based on
the extracting can include generating a histogram of fracture
conductivity, for example. The information can be displayed to a
user (for example, an engineer associated with the fracking
operation) in a user interface. After 514, method 500 can stop.
[0042] FIG. 6 is a block diagram of an example computer system 600
used to provide computational functionalities associated with
described algorithms, methods, functions, processes, flows, and
procedures described in the present disclosure, according to some
implementations of the present disclosure. The illustrated computer
602 is intended to encompass any computing device such as a server,
a desktop computer, a laptop/notebook computer, a wireless data
port, a smart phone, a personal data assistant (PDA), a tablet
computing device, or one or more processors within these devices,
including physical instances, virtual instances, or both. The
computer 602 can include input devices such as keypads, keyboards,
and touch screens that can accept user information. Also, the
computer 602 can include output devices that can convey information
associated with the operation of the computer 602. The information
can include digital data, visual data, audio information, or a
combination of information. The information can be presented in a
graphical user interface (UI) (or GUI).
[0043] The computer 602 can serve in a role as a client, a network
component, a server, a database, a persistency, or components of a
computer system for performing the subject matter described in the
present disclosure. The illustrated computer 602 is communicably
coupled with a network 630. In some implementations, one or more
components of the computer 602 can be configured to operate within
different environments, including cloud-computing-based
environments, local environments, global environments, and
combinations of environments.
[0044] At a top level, the computer 602 is an electronic computing
device operable to receive, transmit, process, store, and manage
data and information associated with the described subject matter.
According to some implementations, the computer 602 can also
include, or be communicably coupled with, an application server, an
email server, a web server, a caching server, a streaming data
server, or a combination of servers.
[0045] The computer 602 can receive requests over network 630 from
a client application (for example, executing on another computer
602). The computer 602 can respond to the received requests by
processing the received requests using software applications.
Requests can also be sent to the computer 602 from internal users
(for example, from a command console), external (or third) parties,
automated applications, entities, individuals, systems, and
computers.
[0046] Each of the components of the computer 602 can communicate
using a system bus 603. In some implementations, any or all of the
components of the computer 602, including hardware or software
components, can interface with each other or the interface 604 (or
a combination of both) over the system bus 603. Interfaces can use
an application programming interface (API) 612, a service layer
613, or a combination of the API 612 and service layer 613. The API
612 can include specifications for routines, data structures, and
object classes. The API 612 can be either computer-language
independent or dependent. The API 612 can refer to a complete
interface, a single function, or a set of APIs.
[0047] The service layer 613 can provide software services to the
computer 602 and other components (whether illustrated or not) that
are communicably coupled to the computer 602. The functionality of
the computer 602 can be accessible for all service consumers using
this service layer. Software services, such as those provided by
the service layer 613, can provide reusable, defined
functionalities through a defined interface. For example, the
interface can be software written in JAVA, C++, or a language
providing data in extensible markup language (XML) format. While
illustrated as an integrated component of the computer 602, in
alternative implementations, the API 612 or the service layer 613
can be stand-alone components in relation to other components of
the computer 602 and other components communicably coupled to the
computer 602. Moreover, any or all parts of the API 612 or the
service layer 613 can be implemented as child or sub-modules of
another software module, enterprise application, or hardware module
without departing from the scope of the present disclosure.
[0048] The computer 602 includes an interface 604. Although
illustrated as a single interface 604 in FIG. 6, two or more
interfaces 604 can be used according to particular needs, desires,
or particular implementations of the computer 602 and the described
functionality. The interface 604 can be used by the computer 602
for communicating with other systems that are connected to the
network 630 (whether illustrated or not) in a distributed
environment. Generally, the interface 604 can include, or be
implemented using, logic encoded in software or hardware (or a
combination of software and hardware) operable to communicate with
the network 630. More specifically, the interface 604 can include
software supporting one or more communication protocols associated
with communications. As such, the network 630 or the interface's
hardware can be operable to communicate physical signals within and
outside of the illustrated computer 602.
[0049] The computer 602 includes a processor 605. Although
illustrated as a single processor 605 in FIG. 6, two or more
processors 605 can be used according to particular needs, desires,
or particular implementations of the computer 602 and the described
functionality. Generally, the processor 605 can execute
instructions and can manipulate data to perform the operations of
the computer 602, including operations using algorithms, methods,
functions, processes, flows, and procedures as described in the
present disclosure.
[0050] The computer 602 also includes a database 606 that can hold
data for the computer 602 and other components connected to the
network 630 (whether illustrated or not). For example, database 606
can be an in-memory, conventional, or a database storing data
consistent with the present disclosure. In some implementations,
database 606 can be a combination of two or more different database
types (for example, hybrid in-memory and conventional databases)
according to particular needs, desires, or particular
implementations of the computer 602 and the described
functionality. Although illustrated as a single database 606 in
FIG. 6, two or more databases (of the same, different, or
combination of types) can be used according to particular needs,
desires, or particular implementations of the computer 602 and the
described functionality. While database 606 is illustrated as an
internal component of the computer 602, in alternative
implementations, database 606 can be external to the computer
602.
[0051] The computer 602 also includes a memory 607 that can hold
data for the computer 602 or a combination of components connected
to the network 630 (whether illustrated or not). Memory 607 can
store any data consistent with the present disclosure. In some
implementations, memory 607 can be a combination of two or more
different types of memory (for example, a combination of
semiconductor and magnetic storage) according to particular needs,
desires, or particular implementations of the computer 602 and the
described functionality. Although illustrated as a single memory
607 in FIG. 6, two or more memories 607 (of the same, different, or
combination of types) can be used according to particular needs,
desires, or particular implementations of the computer 602 and the
described functionality. While memory 607 is illustrated as an
internal component of the computer 602, in alternative
implementations, memory 607 can be external to the computer
602.
[0052] The application 608 can be an algorithmic software engine
providing functionality according to particular needs, desires, or
particular implementations of the computer 602 and the described
functionality. For example, application 608 can serve as one or
more components, modules, or applications. Further, although
illustrated as a single application 608, the application 608 can be
implemented as multiple applications 608 on the computer 602. In
addition, although illustrated as internal to the computer 602, in
alternative implementations, the application 608 can be external to
the computer 602.
[0053] The computer 602 can also include a power supply 614. The
power supply 614 can include a rechargeable or non-rechargeable
battery that can be configured to be either user- or
non-user-replaceable. In some implementations, the power supply 614
can include power-conversion and management circuits, including
recharging, standby, and power management functionalities. In some
implementations, the power-supply 614 can include a power plug to
allow the computer 602 to be plugged into a wall socket or a power
source to, for example, power the computer 602 or recharge a
rechargeable battery.
[0054] There can be any number of computers 602 associated with, or
external to, a computer system containing computer 602, with each
computer 602 communicating over network 630. Further, the terms
"client," "user," and other appropriate terminology can be used
interchangeably, as appropriate, without departing from the scope
of the present disclosure. Moreover, the present disclosure
contemplates that many users can use one computer 602 and one user
can use multiple computers 602.
[0055] Described implementations of the subject matter can include
one or more features, alone or in combination.
[0056] For example, in a first implementation, a
computer-implemented method includes the following. A standard
format seismic dataset of sensor readings obtained from a
three-component sensor is generated. Coordinates and recording
times corresponding to the sensor readings are added to the
standard format seismic dataset. Synchronized seismic data is
generated from the standard format seismic dataset by synchronizing
seismic recording times with fracture treatment times.
Quality-controlled synchronized seismic data is generated by
removing dead traces and abnormal data samples from the
synchronized seismic data. A time-frequency analysis is performed
on the quality-controlled synchronized seismic data, including
performing short-time Fourier transforms to analyze variations of
Fourier spectra over time. Based on the time-frequency analysis,
resonance frequencies are extracted from each frequency spectrum at
different time samples. Interpretation results based are presented
to a user.
[0057] The foregoing and other described implementations can each,
optionally, include one or more of the following features:
[0058] A first feature, combinable with any of the following
features, where the three-component sensor is located outside of a
wellhead.
[0059] A second feature, combinable with any of the previous or
following features, where generating the standard format seismic
dataset includes: receiving raw data corresponding to the sensor
readings obtained by the three-component sensor; and generating the
standard format seismic dataset by converting the raw data
corresponding to the sensor readings into a standard format.
[0060] A third feature, combinable with any of the previous or
following features, where the standard format is a Society of
Exploration Geophysicists (SEG) Y (SEGY) format.
[0061] A fourth feature, combinable with any of the previous or
following features, where adding the coordinates and the recording
times includes updating SEGY headers of the standard format seismic
dataset with the coordinates and recording times.
[0062] A fifth feature, combinable with any of the previous or
following features, where presenting the interpretation results
based on the extracting includes generating a histogram of fracture
conductivity.
[0063] A sixth feature, combinable with any of the previous or
following features, where the sensor readings obtained from the
three-component sensor include signals less than 10 Hertz.
[0064] In a second implementation, a non-transitory,
computer-readable medium stores one or more instructions executable
by a computer system to perform operations including the following.
A standard format seismic dataset of sensor readings obtained from
a three-component sensor is generated. Coordinates and recording
times corresponding to the sensor readings are added to the
standard format seismic dataset. Synchronized seismic data is
generated from the standard format seismic dataset by synchronizing
seismic recording times with fracture treatment times.
Quality-controlled synchronized seismic data is generated by
removing dead traces and abnormal data samples from the
synchronized seismic data. A time-frequency analysis is performed
on the quality-controlled synchronized seismic data, including
performing short-time Fourier transforms to analyze variations of
Fourier spectra over time. Based on the time-frequency analysis,
resonance frequencies are extracted from each frequency spectrum at
different time samples. Interpretation results based are presented
to a user.
[0065] The foregoing and other described implementations can each,
optionally, include one or more of the following features:
[0066] A first feature, combinable with any of the following
features, where the three-component sensor is located outside of a
wellhead.
[0067] A second feature, combinable with any of the previous or
following features, where generating the standard format seismic
dataset includes: receiving raw data corresponding to the sensor
readings obtained by the three-component sensor; and generating the
standard format seismic dataset by converting the raw data
corresponding to the sensor readings into a standard format.
[0068] A third feature, combinable with any of the previous or
following features, where the standard format is a Society of
Exploration Geophysicists (SEG) Y (SEGY) format.
[0069] A fourth feature, combinable with any of the previous or
following features, where adding the coordinates and the recording
times includes updating SEGY headers of the standard format seismic
dataset with the coordinates and recording times.
[0070] A fifth feature, combinable with any of the previous or
following features, where presenting the interpretation results
based on the extracting includes generating a histogram of fracture
conductivity.
[0071] A sixth feature, combinable with any of the previous or
following features, where the sensor readings obtained from the
three-component sensor include signals less than 10 Hertz.
[0072] In a third implementation, a computer-implemented system
includes one or more processors and a non-transitory
computer-readable storage medium coupled to the one or more
processors and storing programming instructions for execution by
the one or more processors. The programming instructions instruct
the one or more processors to perform operations including the
following. A standard format seismic dataset of sensor readings
obtained from a three-component sensor is generated. Coordinates
and recording times corresponding to the sensor readings are added
to the standard format seismic dataset. Synchronized seismic data
is generated from the standard format seismic dataset by
synchronizing seismic recording times with fracture treatment
times. Quality-controlled synchronized seismic data is generated by
removing dead traces and abnormal data samples from the
synchronized seismic data. A time-frequency analysis is performed
on the quality-controlled synchronized seismic data, including
performing short-time Fourier transforms to analyze variations of
Fourier spectra over time. Based on the time-frequency analysis,
resonance frequencies are extracted from each frequency spectrum at
different time samples. Interpretation results based are presented
to a user.
[0073] The foregoing and other described implementations can each,
optionally, include one or more of the following features:
[0074] A first feature, combinable with any of the following
features, where the three-component sensor is located outside of a
wellhead.
[0075] A second feature, combinable with any of the previous or
following features, where generating the standard format seismic
dataset includes: receiving raw data corresponding to the sensor
readings obtained by the three-component sensor; and generating the
standard format seismic dataset by converting the raw data
corresponding to the sensor readings into a standard format.
[0076] A third feature, combinable with any of the previous or
following features, where the standard format is a Society of
Exploration Geophysicists (SEG) Y (SEGY) format.
[0077] A fourth feature, combinable with any of the previous or
following features, where adding the coordinates and the recording
times includes updating SEGY headers of the standard format seismic
dataset with the coordinates and recording times.
[0078] A fifth feature, combinable with any of the previous or
following features, where presenting the interpretation results
based on the extracting includes generating a histogram of fracture
conductivity.
[0079] Implementations of the subject matter and the functional
operations described in this specification can be implemented in
digital electronic circuitry, in tangibly embodied computer
software or firmware, in computer hardware, including the
structures disclosed in this specification and their structural
equivalents, or in combinations of one or more of them. Software
implementations of the described subject matter can be implemented
as one or more computer programs. Each computer program can include
one or more modules of computer program instructions encoded on a
tangible, non-transitory, computer-readable computer-storage medium
for execution by, or to control the operation of, data processing
apparatus. Alternatively, or additionally, the program instructions
can be encoded in/on an artificially generated propagated signal.
For example, the signal can be a machine-generated electrical,
optical, or electromagnetic signal that is generated to encode
information for transmission to a suitable receiver apparatus for
execution by a data processing apparatus. The computer-storage
medium can be a machine-readable storage device, a machine-readable
storage substrate, a random or serial access memory device, or a
combination of computer-storage mediums.
[0080] The terms "data processing apparatus," "computer," and
"electronic computer device" (or equivalent as understood by one of
ordinary skill in the art) refer to data processing hardware. For
example, a data processing apparatus can encompass all kinds of
apparatuses, devices, and machines for processing data, including
by way of example, a programmable processor, a computer, or
multiple processors or computers. The apparatus can also include
special purpose logic circuitry including, for example, a central
processing unit (CPU), a field-programmable gate array (FPGA), or
an application-specific integrated circuit (ASIC). In some
implementations, the data processing apparatus or special purpose
logic circuitry (or a combination of the data processing apparatus
or special purpose logic circuitry) can be hardware- or
software-based (or a combination of both hardware- and
software-based). The apparatus can optionally include code that
creates an execution environment for computer programs, for
example, code that constitutes processor firmware, a protocol
stack, a database management system, an operating system, or a
combination of execution environments. The present disclosure
contemplates the use of data processing apparatuses with or without
conventional operating systems, such as LINUX, UNIX, WINDOWS, MAC
OS, ANDROID, or IOS.
[0081] A computer program, which can also be referred to or
described as a program, software, a software application, a module,
a software module, a script, or code, can be written in any form of
programming language. Programming languages can include, for
example, compiled languages, interpreted languages, declarative
languages, or procedural languages. Programs can be deployed in any
form, including as stand-alone programs, modules, components,
subroutines, or units for use in a computing environment. A
computer program can, but need not, correspond to a file in a file
system. A program can be stored in a portion of a file that holds
other programs or data, for example, one or more scripts stored in
a markup language document, in a single file dedicated to the
program in question, or in multiple coordinated files storing one
or more modules, sub-programs, or portions of code. A computer
program can be deployed for execution on one computer or on
multiple computers that are located, for example, at one site or
distributed across multiple sites that are interconnected by a
communication network. While portions of the programs illustrated
in the various figures may be shown as individual modules that
implement the various features and functionality through various
objects, methods, or processes, the programs can instead include a
number of sub-modules, third-party services, components, and
libraries. Conversely, the features and functionality of various
components can be combined into single components as appropriate.
Thresholds used to make computational determinations can be
statically, dynamically, or both statically and dynamically
determined.
[0082] The methods, processes, or logic flows described in this
specification can be performed by one or more programmable
computers executing one or more computer programs to perform
functions by operating on input data and generating output. The
methods, processes, or logic flows can also be performed by, and
apparatus can also be implemented as, special purpose logic
circuitry, for example, a CPU, an FPGA, or an ASIC.
[0083] Computers suitable for the execution of a computer program
can be based on one or more of general and special purpose
microprocessors and other kinds of CPUs. The elements of a computer
are a CPU for performing or executing instructions and one or more
memory devices for storing instructions and data. Generally, a CPU
can receive instructions and data from (and write data to) a
memory. A computer can also include, or be operatively coupled to,
one or more mass storage devices for storing data. In some
implementations, a computer can receive data from, and transfer
data to, the mass storage devices including, for example, magnetic,
magneto-optical disks, or optical disks. Moreover, a computer can
be embedded in another device, for example, a mobile telephone, a
personal digital assistant (PDA), a mobile audio or video player, a
game console, a global positioning system (GPS) receiver, or a
portable storage device such as a universal serial bus (USB) flash
drive.
[0084] Computer-readable media (transitory or non-transitory, as
appropriate) suitable for storing computer program instructions and
data can include all forms of permanent/non-permanent and
volatile/non-volatile memory, media, and memory devices.
Computer-readable media can include, for example, semiconductor
memory devices such as random access memory (RAM), read-only memory
(ROM), phase change memory (PRAM), static random access memory
(SRAM), dynamic random access memory (DRAM), erasable programmable
read-only memory (EPROM), electrically erasable programmable
read-only memory (EEPROM), and flash memory devices.
Computer-readable media can also include, for example, magnetic
devices such as tape, cartridges, cassettes, and internal/removable
disks. Computer-readable media can also include magneto-optical
disks and optical memory devices and technologies including, for
example, digital video disc (DVD), CD-ROM, DVD+/-R, DVD-RAM,
DVD-ROM, HD-DVD, and BLU-RAY. The memory can store various objects
or data, including caches, classes, frameworks, applications,
modules, backup data, jobs, web pages, web page templates, data
structures, database tables, repositories, and dynamic information.
Types of objects and data stored in memory can include parameters,
variables, algorithms, instructions, rules, constraints, and
references. Additionally, the memory can include logs, policies,
security or access data, and reporting files. The processor and the
memory can be supplemented by, or incorporated into, special
purpose logic circuitry.
[0085] Implementations of the subject matter described in the
present disclosure can be implemented on a computer having a
display device for providing interaction with a user, including
displaying information to (and receiving input from) the user.
Types of display devices can include, for example, a cathode ray
tube (CRT), a liquid crystal display (LCD), a light-emitting diode
(LED), and a plasma monitor. Display devices can include a keyboard
and pointing devices including, for example, a mouse, a trackball,
or a trackpad. User input can also be provided to the computer
through the use of a touchscreen, such as a tablet computer surface
with pressure sensitivity or a multi-touch screen using capacitive
or electric sensing. Other kinds of devices can be used to provide
for interaction with a user, including to receive user feedback
including, for example, sensory feedback including visual feedback,
auditory feedback, or tactile feedback. Input from the user can be
received in the form of acoustic, speech, or tactile input. In
addition, a computer can interact with a user by sending documents
to, and receiving documents from, a device that the user uses. For
example, the computer can send web pages to a web browser on a
user's client device in response to requests received from the web
browser.
[0086] The term "graphical user interface," or "GUI," can be used
in the singular or the plural to describe one or more graphical
user interfaces and each of the displays of a particular graphical
user interface. Therefore, a GUI can represent any graphical user
interface, including, but not limited to, a web browser, a
touch-screen, or a command line interface (CLI) that processes
information and efficiently presents the information results to the
user. In general, a GUI can include a plurality of user interface
(UI) elements, some or all associated with a web browser, such as
interactive fields, pull-down lists, and buttons. These and other
UI elements can be related to or represent the functions of the web
browser.
[0087] Implementations of the subject matter described in this
specification can be implemented in a computing system that
includes a back-end component, for example, as a data server, or
that includes a middleware component, for example, an application
server. Moreover, the computing system can include a front-end
component, for example, a client computer having one or both of a
graphical user interface or a Web browser through which a user can
interact with the computer. The components of the system can be
interconnected by any form or medium of wireline or wireless
digital data communication (or a combination of data communication)
in a communication network. Examples of communication networks
include a local area network (LAN), a radio access network (RAN), a
metropolitan area network (MAN), a wide area network (WAN),
Worldwide Interoperability for Microwave Access (WIMAX), a wireless
local area network (WLAN) (for example, using 802.11 a/b/g/n or
802.20 or a combination of protocols), all or a portion of the
Internet, or any other communication system or systems at one or
more locations (or a combination of communication networks). The
network can communicate with, for example, Internet Protocol (IP)
packets, frame relay frames, asynchronous transfer mode (ATM)
cells, voice, video, data, or a combination of communication types
between network addresses.
[0088] The computing system can include clients and servers. A
client and server can generally be remote from each other and can
typically interact through a communication network. The
relationship of client and server can arise by virtue of computer
programs running on the respective computers and having a
client-server relationship.
[0089] Cluster file systems can be any file system type accessible
from multiple servers for read and update. Locking or consistency
tracking may not be necessary since the locking of exchange file
system can be done at application layer. Furthermore, Unicode data
files can be different from non-Unicode data files.
[0090] While this specification contains many specific
implementation details, these should not be construed as
limitations on the scope of what may be claimed, but rather as
descriptions of features that may be specific to particular
implementations. Certain features that are described in this
specification in the context of separate implementations can also
be implemented, in combination, in a single implementation.
Conversely, various features that are described in the context of a
single implementation can also be implemented in multiple
implementations, separately, or in any suitable sub-combination.
Moreover, although previously described features may be described
as acting in certain combinations and even initially claimed as
such, one or more features from a claimed combination can, in some
cases, be excised from the combination, and the claimed combination
may be directed to a sub-combination or variation of a
sub-combination.
[0091] Particular implementations of the subject matter have been
described. Other implementations, alterations, and permutations of
the described implementations are within the scope of the following
claims as will be apparent to those skilled in the art. While
operations are depicted in the drawings or claims in a particular
order, this should not be understood as requiring that such
operations be performed in the particular order shown or in
sequential order, or that all illustrated operations be performed
(some operations may be considered optional), to achieve desirable
results. In certain circumstances, multitasking or parallel
processing (or a combination of multitasking and parallel
processing) may be advantageous and performed as deemed
appropriate.
[0092] Moreover, the separation or integration of various system
modules and components in the previously described implementations
should not be understood as requiring such separation or
integration in all implementations. It should be understood that
the described program components and systems can generally be
integrated together in a single software product or packaged into
multiple software products.
[0093] Accordingly, the previously described example
implementations do not define or constrain the present disclosure.
Other changes, substitutions, and alterations are also possible
without departing from the spirit and scope of the present
disclosure.
[0094] Furthermore, any claimed implementation is considered to be
applicable to at least a computer-implemented method; a
non-transitory, computer-readable medium storing computer-readable
instructions to perform the computer-implemented method; and a
computer system including a computer memory interoperably coupled
with a hardware processor configured to perform the
computer-implemented method or the instructions stored on the
non-transitory, computer-readable medium.
* * * * *