Note : Les descriptions sont présentées dans la langue officielle dans laquelle elles ont été soumises.
85950322
1
High-angle Fracture Prediction Method, Computer Device and Computer-
readable Storage Medium
Technical Field
The invention relates to the technical field of oil and gas exploration, in
particular to a
high-angle fracture prediction method, a computer device and a computer-
readable storage
medium.
Background
At present, sweet spot parameters such as fracture distribution density,
fracture direction
and the like which are very important for shale gas exploration and
development are still not
available. Only a point estimation can be performed based on drilling
information, and it is
impossible to perform a quantitative fracture prediction in the whole region.
With the
application of wide azimuth seismic data, the study on seismic anisotropy is
forwarded, which
can effectively solve the problem of quantitative prediction of HTI
(Horizontal Transverse
Isotropy, which is an anisotropic medium model for describing a set of
parallel oriented vertical
cracks distributed in isotropic media. It belongs to azimuthal anisotropy, and
these is mic wave
propagates in this kind of medium with characteristics of velocity changing
with direction not
only shown as being changed with a phase angle, but also being changed with an
observation
azimuth. It is generally believed that azimuthal anisotropy is caused by
stress and oriented
vertical fractures) medium fractures and plays an important role in the
specific exploration and
development of shale gas.
At the present stage, there are many methods for predicting fractures by using
wide
azimuth seismic data, and the result of prediction of azimuth amplitude
variation with offset
(AVAz) is used to reflect interface information, but not suitable for
prediction of reservoir
internal fracture information. P-wave fast and slow velocity anisotropy
analysis (VVAz) is
based on velocity difference information of wide azimuth seismic processing,
belongs to
stratum horizon data information, produces a too low resolution, and can only
well control the
distribution law of fractures. The method suitable for prediction of reservoir
internal fractures
Date Regue/Date Received 2021-07-26
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is an anisotropic inversion, and the result of fractures prediction in this
method reflects the
information of fractures within the intervals of reservoir. This method is
applicable to the
quantitative study of fractures in the intervals of reservoir, but in this
method, it is not reasonable
to use an isotropic low-frequency model in the process of azimuthal anisotropy
inversion
fracture prediction, and the source of low-frequency information is limited.
It is easy to cause
the regularity of the result of fracture prediction to be weak, so that the
anisotropic information
of azimuth seismic data is suppressed.
Summary of the Invention
Embodiments of the present invention provide therein a high-angle fracture
prediction
method, a computer device and a computer-readable storage medium, in which the
information
of the anisotropic difference of the fast velocity and slow velocity of P-wave
is fused into a low-
frequency model to acquire anisotropic information of a formation, so as to
predict the required
fracture information, and solve the technical problem of the prior art that it
is impossible to
provide a reasonable low-frequency model in the process of azimuthal
anisotropy inversion
fracture prediction.
An embodiment of the present invention provides a high-angle fracture
prediction method
applied in oil and gas exploration and implemented by a computer device
comprising an input
unit, a processor and a memory, the method comprising the following steps of:
performing a
log measurement to acquire logging data of a target region; acquiring wide
azimuth seismic
data of the target region according to the logging data; performing, by the
processor, a first
azimuthal anisotropy inversion on the wide azimuth seismic data of the target
region based on
a constructed isotropic low-frequency model, to acquire a first anisotropy
intensity; performing,
by the processor, P-wave fast and slow velocity anisotropy analysis on the
wide azimuth seismic
data of the target region, to acquire anisotropy of P-wave fast and slow
velocity difference and
a fast P-wave velocity direction; fitting, by the processor, the first
anisotropy intensity and the
anisotropy of P-wave fast and slow velocity difference, to acquire a P-wave
fast and slow
velocity difference-based anisotropy intensity; establishing, by the
processor, an azimuthal P-
wave anisotropic low-frequency model according to the P-wave fast and slow
velocity
difference-based anisotropy intensity and the fast P-wave velocity direction;
performing, by the
Date Regue/Date Received 2022-06-10
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processor, a second azimuthal anisotropy inversion on the wide azimuth seismic
data of the
target region based on the azimuthal P-wave anisotropic low-frequency model,
to acquire a
second anisotropy intensity and a second anisotropy direction; and analyzing,
by the processor,
the second anisotropy intensity and the second anisotropy direction, to
acquire a fracture
prediction result.
An embodiment of the invention further provides a computer device applied in
oil and gas
exploration, comprising a memory having stored thereon a computer program, a
processor and
an input unit, wherein when executing the computer program, the processor
implements the
following steps of: performing a log measurement to acquire logging data of a
target region;
acquiring wide azimuth seismic data of the target region according to the
logging data;
performing a first azimuthal anisotropy inversion on the wide azimuth seismic
data of the target
region based on a constructed isotropic low-frequency model, to acquire a
first anisotropy
intensity; performing P-wave fast and slow velocity anisotropy analysis on the
wide azimuth
seismic data of the target region, to acquire anisotropy of P-wave fast and
slow velocity
difference and a fast P-wave velocity direction; fitting the first anisotropy
intensity and the
anisotropy of P-wave fast and slow velocity difference, to acquire a P-wave
fast and slow
velocity difference-based anisotropy intensity; establishing an azimuthal P-
wave anisotropic
low-frequency model according to the P-wave fast and slow velocity difference-
based
anisotropy intensity and the fast P-wave velocity direction; performing a
second azimuthal
anisotropy inversion on the wide azimuth seismic data of the target region
based on the
azimuthal P-wave anisotropic low-frequency model, to acquire a second
anisotropy intensity
and a second anisotropy direction; and analyzing the second anisotropy
intensity and the second
anisotropy direction, to acquire a fracture prediction result.
An embodiment of the present invention further provides a computer-readable
storage
medium applied in oil and gas exploration, wherein the computer-readable
storage medium, a
processor and an input unit are comprised in a computer device, the computer-
readable storage
medium stores a computer program for implementing the following steps of:
performing a log
measurement to acquire logging data of a target region; acquiring wide azimuth
seismic data of
the target region according to the logging data; performing, by the processor,
a first azimuthal
anisotropy inversion on the wide azimuth seismic data of the target region
based on a
Date Regue/Date Received 2022-06-10
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constructed isotropic low-frequency model, to acquire a first anisotropy
intensity and;
performing, by the processor, P-wave fast and slow velocity anisotropy
analysis on the wide
azimuth seismic data of the target region, to acquire anisotropy of P-wave
fast and slow velocity
difference and a fast P-wave velocity direction; fitting, by the processor,
the first anisotropy
intensity and the anisotropy of P-wave fast and slow velocity difference, to
acquire a P-wave
fast and slow velocity difference-based anisotropy intensity; establishing, by
the processor, an
azimuthal P-wave anisotropic low-frequency model according to the P-wave fast
and slow
velocity difference-based anisotropy intensity and the fast P-wave velocity
direction;
performing, by the processor, a second azimuthal anisotropy inversion on the
wide azimuth
seismic data of the target region based on the azimuthal P-wave anisotropic
low-frequency
model, to acquire a second anisotropy intensity and a second anisotropy
direction; and
analyzing, by the processor, the second anisotropy intensity and the second
anisotropy direction,
to acquire a fracture prediction result.
In the embodiments of the present invention, a first azimuthal anisotropy
inversion is
performed on wide azimuth seismic data of a target region based on a
constructed isotropic low-
frequency model, to acquire a first anisotropy intensity; then P-wave fast and
slow velocity
anisotropy analysis is performed on the wide azimuth seismic data of the
target region, to
acquire anisotropy of P-wave fast and slow velocity difference and a fast P-
wave velocity
direction, the first anisotropy intensity is fitted with the anisotropy of P-
wave fast and slow
velocity difference, to acquire a P-wave fast and slow velocity difference-
based anisotropy
intensity; an azimuthal P-wave anisotropic low-frequency model is established
according to the
P-wave fast and slow velocity difference-based anisotropy intensity and the
fast P-wave
velocity direction, to achieve that results of anisotropy analysis of P-wave
velocity difference
can be fused into the establishment process of the azimuth anisotropy low-
frequency, thereby
solving the technical problem of the prior art that it is impossible to
provide a reasonable low-
frequency model in the process of azimuthal anisotropy inversion fracture
prediction. Then a
second azimuthal anisotropy inversion is performed on the wide azimuth seismic
data of the
target region based on the azimuthal P-wave anisotropic low-frequency model,
to acquire a
second anisotropy intensity and a second anisotropy direction; and the second
anisotropy
intensity and the second anisotropy direction are analyzed, to acquire a
fracture prediction result
Date Regue/Date Received 2022-06-10
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4a
and realize the quantitative prediction of the fractures, which not only has
the overall rationality
of fracture distribution, but also ensures the accuracy of the fracture
prediction.
Brief Description of the Drawings
In order to more clearly explain the embodiments of the invention or the
technical solution
in the prior art, drawings that need to be used in the description of
embodiments or the prior art
will be simply introduced below, obviously the drawings in the following
description are merely
some examples of the invention, for persons ordinarily skilled in the art, it
is also possible to
acquire other drawings according to these drawings without making creative
efforts.
FIG. 1 is a flowchart of a high-angle fracture prediction method according to
an
embodiment of the present invention.
FIG. 2 is a process flowchart of a specific high-angle fracture prediction
method according
Date Regue/Date Received 2022-06-10
5
to an embodiment of the present invention.
FIG. 3 is a schematic diagram of an optimized logging interpretation result
according to an
embodiment of the present invention.
FIG. 4 is a schematic diagram of a seismic petrophysical interpretation
template for a
fracture-type reservoir according to an embodiment of the present invention.
FIG. 5 is a schematic diagram of an isotropic low-frequency model profile
according to an
embodiment of the present invention.
FIG. 6 is a schematic diagram of a fast P-wave velocity profile (indicated by
a) and a slow
P-wave velocity profile (indicated by b) according to an embodiment of the
present invention.
FIG. 7 is a schematic diagram of a fracture azimuthal angle from a fracture
azimuthal
angle statistical analysis acquired by fast and slow P-wave velocity analysis
according to an
embodiment of the present invention, which is considered to be perpendicular
to an anisotropic
direction.
FIG. 8 is a schematic diagram showing a fitting relationship between
anisotropy of the
P-wave fast and slow velocity difference and a first anisotropy intensity
according to an
embodiment of the present invention.
FIG. 9 is a schematic diagram of an anisotropy intensity contrast profile
according to an
embodiment of the present invention (the upper graph a is: an anisotropy (J)
profile acquired
by fast and slow P-wave velocity analysis; b is an anisotropy intensity ( kv )
profile based on
the P-wave fast and slow velocity difference, that is acquired after fitting J
to the first
anisotropy intensity ( k ) and after correction.
FIG. 10 is a schematic diagram of an azimuthal anisotropic low-frequency model
according to an embodiment of the present invention.
FIG. 11 is an anisotropy intensity profile according to an embodiment of the
present
invention (the upper graph is: the first anisotropy intensity ( b1) acquired
by the first azimuthal
anisotropy inversion; the middle graph is: the anisotropy intensity ( bh, )
after the fast and slow
P-wave velocity analysis and correction; the lower graph is: the second
anisotropy intensity (
k2) acquired by the second anisotropy inversion).
FIG. 12 is a plan view of a fracture comprehensive analysis according to an
embodiment
of the present invention (a: the fracture density and direction acquired by
the first anisotropy
inversion; b: the fracture density and direction acquired after thefast and
slow P-wave velocity
analysis and correction; c: the fracture density and direction acquired by the
second anisotropy
inversion).
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6
FIG. 13 is a schematic diagram of fracture azimuthal angle statistical
analysis according to
an embodiment of the present invention (a: a histogram of fracture azimuthal
angle statistical
analysis acquired by the first anisotropy inversion; b: a histogram of
fracture azimuthal angle
statistical analysis acquired by fast and slow P-wave velocity analysis; c: a
histogram of
fracture azimuthal angle statistical analysis acquired by the second
anisotropy inversion).
FIG. 14 is a schematic block diagram of a system configuration of a computer
device
according to an embodiment of the present invention.
Detailed Description of the Preferred Embodiment
Hereinafter the technical solution in the embodiments of the present invention
will be
described clearly and integrally in combination with the accompanying drawings
in the
embodiments of the present invention, and obviously the described embodiments
are merely
part of the embodiments, rather than all of the embodiments. Based on the
embodiments of the
present invention, all other embodiments that are acquired by persons skilled
in the art without
making creative efforts fall within the protection scope of the present
invention.
In an embodiment of the present invention, a high-angle fracture prediction
method is
provided, as shown in FIG. 1, the method comprising:
step 101: performing a first azimuthal anisotropy inversion on wide azimuth
seismic data
of a target region based on a constructed isotropic low-frequency model, to
acquire a first
anisotropy intensity;
step 102: performing P-wave fast and slow velocity anisotropy analysis on the
wide
azimuth seismic data of the target region, to acquire anisotropy of P-wave
fast and slow
velocity difference and a fast P-wave velocity direction;
step 103: fitting the first anisotropy intensity and the anisotropy of P-wave
fast and slow
velocity difference, to acquire a P-wave fast and slow velocity difference-
based anisotropy
intensity;
step 104: establishing an azimuthal P-wave anisotropic low-frequency model
according to
the P-wave fast and slow velocity difference-based anisotropy intensity and
the fast P-wave
velocity direction;
step 105: performing a second azimuthal anisotropy inversion on the wide
azimuth seismic
data of the target region based on the azimuthal P-wave anisotropic low-
frequency model, to
acquire a second anisotropy intensity and a second anisotropy direction;
step 106: analyzing the second anisotropy intensity and the second anisotropy
direction, to
acquire a fracture prediction result.
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7
In an embodiment of the present invention, as shown in FIG. 2, the step 101 is
implemented specifically as follows:
(1) Acquiring logging data of a target region, including logging P-wave and S-
wave
curves, a density curve, P-wave and S-wave impedances, a P-wave and S-wave
velocity ratio
and a rock mineral composition curve, a porosity curve, a water saturation
curve and drilling
stratification data, as shown in the FIG. 3. Logging evaluation and analysis
of a fracture-type
reservoir are completed according to the logging data, there servoir fracture
will lead to the
anisotropy of the formation, so that it is necessary to establish a
petrophysical model based on
the fracture, and determine the sensitive elastic parameters of the
anisotropic reservoir caused
by the fracture. This process selects a P-wave and S-wave velocity ratio as
the sensitive elastic
parameter of this type of reservoir fracture. As shown in FIG.4, with a slight
change in fracture
porosity, the P-wave and S-wave velocity ratio of the formation features a
greater change,
wherein, (1) frac denotes a porosity of the fracture, Swt denotes a saturation
of water, and 4) t
denotes a stratum total porosity.
(2) Acquiring seismic horizon data of the target region, establishing a
structural frame
model by using the structural interpretation results (mainly the seismic
horizon data), and
establishing an isotropic low-frequency model based on the logging data, as
shown in FIG. 5.
(3) Acquiring wide azimuth seismic data of the target region, and quality of
the wide
azimuth seismic data is directly related to the subsequent inversion effect,
so that it is necessary
to evaluate the quality of the wide azimuth seismic data, with the focus on
the distribution
characteristics of azimuth and offset of the wide azimuth seismic data and the
formulation of
the most favorable principles of azimuth and offset division. Specifically,
the wide azimuth
seismic data of the target region is divided and stacked in a manner of
dividing the azimuthal
angle at first and then dividing the offset, to form multiple partial angle
stacked seismic data
with different azimuths.
(4) Performing a multi-azimuth pre-stack anisotropy inversion on the multiple
partial angle
stacked seismic data of different azimuths based on the constructed isotropic
low-frequency
model, and performing a pre-stack inversion on each azimuth, to acquire the
sensitive elastic
parameter data (P-wave and S-wave velocity ratio data) of the divided azimuth
fracture.
(5) Determining a first anisotropy intensity according to the divided
azimuthal P-wave and
S-wave velocity ratio.
Herein, the first anisotropy intensity is determined according to the
following formula:
CA 3069442 2020-01-23
, .
, .
. .
8
. .
(v.
log --21 =b0 + li. 'cos [2 ( co ¨ On + b2scos [4 ( 00-- 45)]
, , j .
V
i, z)1
wherein, Vp denotes a P-wave velocity, Vs denotes an S-wave velocity, k
denotes a
first anisotropy intensity, to denotes an azimuthal angle of the seismic data,
i.e., an azimuthal
angle of a work area survey network, 0 denotes a first anisotropy direction,
namely an
azimuthal angle of the seismic data, bo denotes an isotropic background, b2
denotes
anisotropy of the influence of high-order noise in the first azimuthal
anisotropy inversion ,
('2
,
v ' denotes an P-wave and S-wave velocity ratio acquired after the first
azimuthal
511
anisotropy inversion based on isotropic low-frequency models.
In an embodiment of the present invention, as shown in FIG. 2, the step 102 is
implemented specifically as follows:
(1) Processing the wide azimuth seismic data of the target region to acquire a
fast P-wave
velocity, a slow P-wave velocity and a fast P-wave velocity direction, which
are P-wave fast
and slow velocity profiles as shown by a and b in FIG. 6.
(2) Performing a P-wave anisotropy analysis to acquire anisotropy of P-wave
fast and slow
velocity difference and the direction of fast P-wave velocity. In terms of
fast and slow P-waves,
the fast P-wave propagates along the isotropic direction of the formation, and
it is generally
considered that the direction of fast P-wave propagation corresponds to the
direction of fracture
growth, and the direction of anisotropy may be perpendicular to the direction
of fracture. FIG. 7
is a statistical analysis diagram of the fracture azimuthal angle acquired
from fast P-wave
velocity direction analysis.
Herein, the anisotropy of the P-wave fast and slow velocity difference is
determined
according to the following formula:
Vpfaut ¨ Viriznienv
j= ________________________________________________________
Vificifost ;
wherein, J denotes anisotropy of the P-wave fast and slow velocity difference,
VpNwfast denotes a fast P-wave velocity, VpNwstow denotes a slow P-wave
velocity. It is
considered here that the direction of fast P-wave propagation corresponds to
the direction of
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9
"
fracture growth.
(3) Analyzing the anisotropy parameters acquired from the P-wave velocity
anisotropy
analysis, and analyzing the histogram of fast P-wave velocity in the horizon
data, the main
azimuthal angle in which anisotropy occurs in the horizon data can be
acquired, as shown in
FIG. 7, and the determined azimuth is used as an input to establish an
anisotropic
low-frequency model.
In an embodiment of the present invention, as shown in FIG. 2, the step 103 is
implemented specifically as follows.
The result of the first azimuthal anisotropy inversion in the step 101 is
compared with the
result of the P-wave fast and slow velocity difference anisotropy analysis in
the step 102.Firstly,
analysis is performed on the result of the first anisotropy inversion and the
result of the P-wave
fast and slow velocity difference anisotropy analysis that represents fracture
intensity. Since the
two results are different in the range of values reflecting the fracture
intensity, it is necessary to
correct the range of the anisotropy (J) of the P-wave fast and slow velocity
difference in the
result of the P-wave fast and slow velocity difference anisotropy analysis to
have the same
range of the first anisotropy intensity ( )acquired from the first azimuthal
anisotropy
inversion, and a relationship between the two is acquired by fitting the two
using the
intersection analysis method, in which the anisotropy (J) of the P-wave fast
and slow velocity
difference is converted into an anisotropy intensity ( bh, ) based on the P-
wave fast and slow
velocity difference having the same range as the first anisotropy intensity (
k ), as shown in
FIG. 8. "a" in FIG. 9 shows the anisotropy (J) caused by the fast and slow P-
wave velocity
difference, and "b" in FIG. 9 is a schematic diagram showing comparison and
analysis of the
anisotropy intensity ( bh, ) based on the P-wave fast and slow velocity
difference that is formed
after the anisotropy caused by the fast and slow P-wave velocity difference is
corrected to be
within the range of the first anisotropy intensity (b1).
The fitting formula is as follows:
biv = -0,23 x..f - 0,005.
In an embodiment of the present invention, as shown in FIG. 2, the step 104 is
implemented specifically as follows:
fusing the anisotropy intensity ( bh, ) based on the P-wave fast and slow
velocity difference
and the fast P-wave velocity direction into the constructed isotropic low-
frequency models. An
azimuthal P-wave anisotropic low-frequency model is established by fitting an
approximate
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. .
. .
. .
. .
relationship (the following formula) of the anisotropic P-wave and S-wave
velocity ratio, as
shown in FIG. 10.
Herein, the approximate relationship of the anisotropic low-frequency model of
the
azimuthal P-wave is shown as follows:
( V )
P _ emb,ftes2(6-11.) ,a; P
5
V
k 'lo
Wherein, V7, denotes a P-wave velocity, Vs denotes an S-wave velocity, bh,
denotes
P-wave fast and slow velocity difference-based anisotropy intensity, co
denotes an azimuthal
angle of the seismic data, 0, denotes a direction perpendicular to the fast P-
wave velocity,
P
v denotes the anisotropic low-frequency model of the
azimuthal P-wave, and
' =5 01.
Kr, "N
10 . v denotes an isotropic low-frequency model.
X `i io
, .
In an embodiment of the present invention, the step 105 is implemented
specifically as
follows:
performing a second azimuthal anisotropy inversion on the wide azimuth seismic
data of
the target region in accordance with the following formula, based on the
azimuthal P-wave
anisotropic low-frequency model, to acquire a second anisotropy intensity and
a second
anisotropy direction:
f V j
P _
log ¨ ¨k +b,ficos[2(co¨ 02 )] k2 *CO S[4(CO ¨ b2)];
wherein, Vp denotes a P-wave velocity, Vs denotes an S-wave velocity, k
denotes an
isotropic background, A2 denotes a second anisotropy intensity, CO denotes an
azimuthal
angle of the seismic data, 02 denotes a second anisotropy direction, b22
denotes anisotropy
V 1
_
of the influence of high-order noise in the second azimuthal anisotropy
inversion; 1
(
ror
-,s,i2
denotes an P-wave and S-wave velocity ratio acquired after the second
azimuthal anisotropy
CA 3069442 2020-01-23
11
inversion.
In an embodiment of the present invention, the step 106 is implemented
specifically as
follows:
analyzing the second anisotropy intensity and the second anisotropy direction
to acquire a
fracture prediction result, wherein the anisotropy intensity reflects the
density of the fractures to
some extent, and the anisotropy direction is approximately perpendicular to
the direction of the
fracture in azimuth, so that the fracture density and the fracture direction
are acquired.
Hereinafter, the advantage of the method of the present invention will be
explained by
comparing the data acquired by the first anisotropy inversion with the data
acquired by the
second anisotropy inversion.
FIG. 11 is an anisotropy intensity profile according to an embodiment of the
present
invention (the above graph is: the first anisotropy intensity (4 ) acquired by
the first azimuthal
anisotropy inversion; the middle graph is: the anisotropy intensity (4, )
after the fast and slow
P-wave velocity analysis and correction; the lower graph is: the second
anisotropy intensity (
42) acquired by the second anisotropy inversion).
FIG. 12 is a plan view of a fracture comprehensive analysis according to an
embodiment
of the present invention (a: the fracture density and direction acquired by
the first anisotropy
inversion; b: the fracture density and direction acquired after the fast and
slow P-wave velocity
analysis and correction; c: the fracture density and direction acquired by the
second anisotropy
inversion).From FIG. 12, the fracture direction acquired by the first
anisotropy inversion is
relatively scattered, and the regularity of predicting fracture is not strong;
after the anisotropy
correction based on the P-wave fast and slow velocity, the acquired fracture
direction only =
reflects the general regularity, but the resolution is low, and the fracture
azimuth regularity
acquired after the second anisotropy inversion is strong, and the resolution
for predicting
.. fractures is improved.
FIG. 13 is a schematic diagram of fracture azimuthal angle statistical
analysis according to
an embodiment of the present invention (a: a histogram of fracture azimuthal
angle statistical
analysis acquired by the first anisotropy inversion; b: a histogram of
fracture azimuthal angle
statistical analysis acquired by fast and slow P-wave velocity analysis; c: a
histogram of
fracture azimuthal angle statistical analysis acquired by the second
anisotropy inversion).From
FIG. 13, the fracture direction acquired by the first anisotropy inversion is
relatively scattered,
after the anisotropy correction based on the P-wave fast and slow velocity,
the acquired fracture
direction only reflects the general regularity; and the fracture azimuth
regularity acquired after
CA 3069442 2020-01-23
12
the second anisotropy inversion is strong.
The present invention further provides a computer device, which may be a
desktop
computer, a tablet computer and a mobile terminal, and etc., and the present
embodiment is not
limited thereto. In the embodiment, the computer device may complete the
implementation of
the high-angle fracture prediction method.
FIG. 14 is a schematic block diagram of a system composition of a computer
device 500
according to an embodiment of the present invention. As shown in FIG. 14, the
computer
device 500 may include a processor 100 and a memory 140, wherein the memory
140 is
coupled to the processor 100. It is worth noting that this figure is
exemplary; other types of
structures may also be used in addition to or instead of the structure to
implement
telecommunications functions or other functions.
In an embodiment, a computer program implementing a high-angle fracture
prediction
function may be integrated into the processor 100. Wherein the processor 100
may be
configured to perform the following controls:
performing a first azimuthal anisotropy inversion on wide azimuth seismic data
of a target
region based on a constructed isotropic low-frequency model, to acquire a
first anisotropy
intensity;
performing P-wave fast and slow velocity anisotropy analysis on the wide
azimuth seismic
data of the target region, to acquire anisotropy of P-wave fast and slow
velocity difference and
a fast P-wave velocity direction;
fitting the first anisotropy intensity and the anisotropy of P-wave fast and
slow velocity
difference, to acquire a P-wave fast and slow velocity difference-based
anisotropy intensity;
establishing an azimuthal P-wave anisotropic low-frequency model according to
the
P-wave fast and slow velocity difference-based anisotropy intensity and the
fast P-wave
velocity direction;
performing a second azimuthal anisotropy inversion on the wide azimuth seismic
data of
the target region based on the azimuthal P-wave anisotropic low-frequency
model, to acquire a
second anisotropy intensity and a second anisotropy direction; and
analyzing the second anisotropy intensity and the second anisotropy direction,
to acquire a
fracture prediction result.
In an embodiment of the present invention, when executing the computer
program, the
processor implements:
the wide azimuth seismic data of the target region is divided and stacked in a
manner of
dividing the azimuthal angle at first and then dividing an offset, to form
multiple partial angle
CA 3069442 2020-01-23
. .
13
. ,
stacked seismic data with different azimuths;
performing an azimuth anisotropy inversion on the multiple partial angle
stacked seismic
data of different azimuths based on the constructed isotropic low-frequency
model, to acquire a
divided azimuthal P-wave and S-wave velocity ratio; and
determining the first anisotropy intensity from the divided azimuthal P-wave
and S-wave
velocity ratio.
In an embodiment of the present invention, when executing the computer
program, the
processor implements:
processing the wide azimuth seismic data of the target region, to acquire a
fast P-wave
velocity, a slow P-wave velocity and a fast P-wave velocity direction; and
determining anisotropy of the P-wave fast and slow velocity difference based
on the fast
P-wave velocity and the slow P-wave velocity.
In an embodiment of the present invention, when executing the computer
program, the
processor implements:
fitting the first anisotropy intensity and the anisotropy of P-wave fast and
slow velocity
difference in accordance with the following formula, to acquire the P-wave
fast and slow
velocity difference-based anisotropy intensity:
biv = -0.23xJ -0 005.
wherein, biv denotes P-wave fast and slow velocity difference-based anisotropy
intensity; and J denotes anisotropy of the P-wave fast and slow velocity
difference.
In an embodiment of the present invention, when executing the computer
program, the
processor implements:
establishing the azimuthal P-wave anisotropic low-frequency model in
accordance with the
following formula, according to the P-wave fast and slow velocity difference-
based anisotropy
intensity and the fast P-wave velocity direction:
i V µ
V P ,,,:er eiliv*c 52(gl-er) . P (
V
wherein, Vp denotes a P-wave velocity, Vs denotes an S-wave velocity, b1,
denotes
P-wave fast and slow velocity difference-based anisotropy intensity, co
denotes an azimuthal
angle of the seismic data, 0,, denotes a direction perpendicular to the fast P-
wave velocity,
CA 3069442 2020-01-23
. .
. .
14
. ,
. v
,p -
r denotes the
anisotropic low-frequency model of the azimuthal P-wave, and
(w , '
( Vp )
V_ )11
- ''. denotes an isotropic low-frequency model.
In another embodiment, the high-angle fracture prediction function may be
configured
separately from the processor 100, for example, the high-angle fracture
prediction function may
be configured on a chip connected to the processor 100, and the high-angle
fracture prediction
function is realized by the control of the processor.
As shown in FIG. 14, the computer device 500 may further comprise an input
unit 120, a
display 160, and a power supply 170. It is worth noting that the computer
device 500 does not
either necessarily comprise all of the components shown in FIG. 14; in
addition, the computer
device 500 may also comprise components not shown in FIG. 14, with reference
to the prior art.
Among other things, the processor 100, sometimes referred to as a controller
or an
operational control, may comprise a microprocessor or other processor
apparatuses and/or logic
apparatuses, the processor 100 receives inputs and controls operation of the
components of the
computer device 500.
The input unit 120 provides an input to the processor 100. The input unit 120
is, for
example, a key or a touch input apparatus.
The memory 140 may be, for example, one or more of a buffer, a flash memory, a
hard
drive, a removable medium, a volatile memory, a non-volatile memory, or other
suitable
apparatuses. A program executing related information may be stored, and the
processor 100
may execute the program stored in the memory 140 to implement information
storage or
processing and the like.
The memory 140 may be a solid state memory such as read only memory (ROM),
random
access memory (RAM), SIM card, or the like. The memory may also be such a
memory that it
saves information even when power is off, on which data can be selectively
erased and more
data is set, and an example of which is sometimes referred to as an EPROM or
the like. The
memory 140 may also be some other types of apparatuses. The memory 140
includes a buffer
memory 141 (sometimes referred to as a buffer). The memory 140 may include an
application/function storage unit 142 for storing application programs and
function programs or
a flow for performing operation of an electronic device by the processor 100.
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15
The memory 140 may also include a data storage unit 143 for storing data, such
as
contacts, digital data, pictures, sounds, and / or any other data used by the
electronic device. A
drive program storage unit 144 of the memory 140 may include various drive
programs of the
electronic device for communication functions and/or for executing other
functions of the
electronic device, such as a messaging application, an address book
application, and the like.
The display 160 is used for displaying objects to be displayed, such as images
and text,
and the like. The display may be, for example, an LCD display, but is not
limited thereto.
The power supply 170 is used to provide power to the computer device 500.
The embodiment of the present invention also provides a computer-readable
storage
.. medium which stores a computer program for implementing the any of the high
Angle fracture
prediction methods.
The computer-readable storage medium may include physical means for storing
information which may be digitized and then stored in a medium using
electrical, magnetic or
optical means. The computer-readable storage medium according to the present
embodiment
may include an apparatus for storing information in an electric energy manner,
e.g., various
types of memories such as RAM, ROM, and the like; an apparatus for storing
information in an
magnetic energy manner, such as a hard disk, a floppy disk, a magnetic tape, a
magnetic core
memory, a bubble memory, a U disk; an apparatus for storing information in an
optical manner,
such as a CD or a DVD. Of course, there are other kinds of readable storage
media, such as a
quantum memory, a graphene memory, and the like.
In summary, the high-angle fracture prediction method, the computer device and
the
computer-readable storage medium provided in the present invention have the
following
beneficial effects:
a first azimuthal anisotropy inversion is performed on wide azimuth seismic
data of a
target region based on a constructed isotropic low-frequency model, to acquire
a first anisotropy
intensity and a first anisotropy direction;, then P-wave fast and slow
velocity anisotropy
analysis is performed on the wide azimuth seismic data of the target region,
to acquire
anisotropy of P-wave fast and slow velocity difference and a fast P-wave
velocity direction, the
first anisotropy intensity is fitted with the anisotropy of P-wave fast and
slow velocity
difference, to acquire a P-wave fast and slow velocity difference-based
anisotropy intensity; an
azimuthal P-wave anisotropic low-frequency model is established according to
the P-wave fast
and slow velocity difference-based anisotropy intensity and the fast P-wave
velocity direction,
to achieve that results of anisotropy analysis of P-wave velocity difference
can be fused into the
establishment process of the azimuth anisotropy low-frequency, thereby solving
the technical
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problem of the prior art that it is impossible to provide a reasonable low-
frequency model in the
process of azimuthal anisotropy inversion fracture prediction. Then a second
azimuthal
anisotropy inversion is performed on the wide azimuth seismic data of the
target region based
on the azimuthal P-wave anisotropic low-frequency model, to acquire a second
anisotropy
intensity and a second anisotropy direction; and the second anisotropy
intensity and the second
anisotropy direction are analyzed, to acquire a fracture prediction result and
realize the
quantitative prediction of the fractures, which not only has the overall
rationality of fracture
distribution, but also ensures the accuracy of the fracture prediction.
The foregoing is merely preferred embodiments of the present invention and is
not
intended to limit the present invention, and various modifications and
variations can be made to
the embodiments of the present invention by those skilled in the art. Any
modifications,
equivalents, improvements, etc. made within the spirit and principle of the
present invention are
intended to be included within the protection scope of the present invention.
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