CN113933898B - Method, device and equipment for identifying anisotropic characteristics of fractured reservoir and storage medium - Google Patents

Method, device and equipment for identifying anisotropic characteristics of fractured reservoir and storage medium Download PDF

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CN113933898B
CN113933898B CN202111114999.9A CN202111114999A CN113933898B CN 113933898 B CN113933898 B CN 113933898B CN 202111114999 A CN202111114999 A CN 202111114999A CN 113933898 B CN113933898 B CN 113933898B
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reservoir
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CN113933898A (en
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薛姣
顾汉明
贺梅
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China University of Geosciences
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Abstract

The invention discloses a method, a device, equipment and a storage medium for identifying anisotropic characteristics of a fractured reservoir, wherein the method comprises the following steps: acquiring pre-stack seismic data and an effective azimuth space, and performing effective azimuth space division; sequentially extracting azimuth angle samples, enabling the fracture trend to be equal to the sampling azimuth angle, and inverting the isotropic coefficient and the fracture anisotropic coefficient by utilizing linear least squares on the seismic data before superposition; forward modeling is carried out on all fractured reservoir parameter combinations, an L2 norm of the difference between forward modeling data and pre-stack seismic data is taken as a target function, and a group of fracture trend, isotropic coefficient and fracture anisotropy parameters with the minimum target function are selected as optimal fractured reservoir parameters; and revising the fracture strike direction according to the relation between the fracture strike and the amplitude. The method combines system sampling and least square inversion, converts the nonlinear fractured reservoir parameter inversion problem into the linear inversion problem based on azimuth system sampling, and improves the accuracy and stability of the fractured reservoir parameter inversion identification.

Description

Method, device and equipment for identifying anisotropic characteristics of fractured reservoir and storage medium
Technical Field
The invention relates to the field of oil and gas geophysical exploration, in particular to a method, a device, equipment and a storage medium for identifying anisotropic characteristics of a fractured reservoir.
Background
In an actual fractured reservoir, high-angle and vertical fractures widely exist in volcanic rock and carbonate reservoirs, and play an important role in exploration and development of the fractured reservoir, and the fractured reservoir detection provides reliable guarantee for identification of fluids in the fractured reservoir. The method for detecting the fractures by using the azimuth anisotropy of the prestack seismic data is an important method for predicting the fractured reservoirs.
The amplitude of the reflection of the primary seismic wave at a fixed offset as a function of the azimuth is a function of the period pi. The amplitude variation with azimuth is usually approximated as an ellipse, and ellipse fitting is performed on the reflected amplitudes of the longitudinal waves in different azimuths, with the direction of the major or minor axis of the ellipse as the fracture strike and the ellipticity as the fracture density, however, the variation of the seismic amplitude with azimuth is not an exact ellipse. Another method for detecting fractured reservoirs is inversion using the variation of seismic amplitude with azimuth. Therefore, the inversion of the fracture anisotropy parameters and the fracture trend by using the prestack azimuth seismic data is a nonlinear inversion problem, and the direct nonlinear inversion of the fracture reservoir parameters is complex, so that the stability and the accuracy of the identification of the fracture reservoir anisotropy characteristics are low.
Disclosure of Invention
In order to improve the stability and the accuracy of the anisotropic feature identification of the fractured reservoir, the method combines system sampling and linear least square inversion, converts the nonlinear fractured reservoir parameter inversion problem into the linear inversion problem based on azimuth system sampling, and improves the stability and the accuracy of the fractured reservoir parameter inversion.
In order to achieve the purpose, the invention provides a method for identifying anisotropic characteristics of a fractured reservoir, which comprises the following steps:
s1, acquiring pre-stack seismic data and an effective azimuth space, and equally dividing the effective azimuth space to obtain a plurality of azimuth samples;
s2, acquiring a sampling azimuth from the azimuth samples, enabling the initial fracture trend to be equal to the acquired sampling azimuth, and performing inversion calculation on the pre-stack seismic data according to the sampling azimuth to obtain fracture reservoir parameters corresponding to the sampling azimuth;
s3, forward modeling calculation is carried out on the fracture reservoir parameters to obtain forward modeling data, the difference value between the forward modeling data and the pre-stack seismic data is calculated, and the L2 norm of the difference value is taken as a target function;
s4, repeating the steps S2 to S3 until fracture reservoir parameter combinations corresponding to all azimuth angle samples and corresponding target functions are obtained;
s5, calculating the minimum value of the target function, obtaining the fracture trend, the isotropy coefficient and the fracture anisotropy coefficient corresponding to the minimum value of the target function, namely the inversion result of the fracture reservoir parameters, and identifying the anisotropy characteristic of the fracture reservoir according to the inversion result;
and S6, revising the fracture strike orientation according to the relation between the fracture strike and the amplitude long axis.
Further, step S1 specifically includes:
acquiring prestack seismic data Fobs；
Obtaining an effective azimuth angle space of 0-90 degrees;
determining a decimation interval delta, equally dividing the effective azimuth angle space by taking delta as an interval, and generating K-90/delta azimuth angle samples which are respectively: 0, Δ,2 Δ, …, 90- Δ.
Further, step S2 specifically includes:
in an azimuthal anisotropic medium consisting of vertical fractures, the relationship between the amplitude response of longitudinal waves with fixed offset and the angle between the observed azimuth and the fracture strike is a function of the period pi:
Figure BDA0003274957680000021
wherein F is seismic reflection amplitude, A is an isotropic coefficient, B is a fracture anisotropy coefficient, and is used for representing fracture development strength,
Figure BDA0003274957680000022
is the direction of observation and the direction of observation,
Figure BDA0003274957680000023
is to observe the azimuth
Figure BDA0003274957680000024
The amplitude of the seismic reflections of (a) is,
Figure BDA0003274957680000025
the fracture strike, the isotropy coefficient, the fracture anisotropy coefficient and the fracture strike are parameters of a fracture reservoir to be inverted and parameters of the fracture reservoir
Figure BDA0003274957680000026
The inversion of (b) is a nonlinear inversion problem, where superscript T represents the transposition;
performing system sampling on azimuth angle samples according to a set sequence, wherein the azimuth angle sample acquired at the kth time is (k-1) delta, and the initial fracture trend is equal to the sampling azimuth angle:
Figure BDA0003274957680000027
then
Figure BDA0003274957680000028
The fracture reservoir parameter inversion problem is converted from nonlinear inversion into a linear inversion problem:
Figure BDA0003274957680000031
wherein, the first and the second end of the pipe are connected with each other,
Figure BDA0003274957680000032
the number of the ith observation direction is represented, and M represents the number of the observation directions;
Figure BDA0003274957680000033
the vector is formed by pre-stack seismic data, and the superscript T represents transposition;
inversion of isotropic coefficient A by linear least square methodkAnd crack anisotropy coefficient BkObtaining the fracture reservoir parameter model vector
Figure BDA0003274957680000034
Further, step S3 specifically includes:
forward calculation is carried out on the fracture reservoir parameters to obtain the fracture strike of
Figure BDA0003274957680000035
The reflection amplitude of time is the forward data:
Figure BDA0003274957680000036
establishing an objective function:
Figure BDA0003274957680000037
wherein m iskRepresenting a fracture reservoir parametric model vector,
Figure BDA0003274957680000038
Akis the isotropic coefficient, BkIs the coefficient of anisotropy of the crack,
Figure BDA0003274957680000039
is the crack direction, FobsAnd FkRespectively vectors consisting of pre-stack seismic data and forward data,
Figure BDA00032749576800000310
Figure BDA00032749576800000311
denotes the ith observation position, i is 1, 2.
Further, step S5 specifically includes:
calculating the minimum value of the target function and the optimal solution of the crack reservoir parameter inversion corresponding to the minimum value:
Figure BDA00032749576800000312
wherein D is a fracture reservoir parameter inversion result space corresponding to all sampling azimuth angles, mkRepresenting a fracture reservoir parametric model vector, J (m)k) Representing the objective function, mestAnd expressing an optimal solution of parameter inversion of the fractured reservoir, and identifying anisotropic characteristics of the fractured reservoir according to the optimal solution.
Further, step S6 specifically includes:
judging whether the fracture trend is in the amplitude long axis direction:
if the fracture trend is in the amplitude long axis direction, the sign relationship between the isotropic coefficient A and the fracture anisotropy coefficient B is further judged:
if the signs of A and B are opposite, the revised fracture strike inversion result is as follows:
Figure BDA0003274957680000041
Figure BDA0003274957680000042
representing an optimal solution for fracture strike inversion;
if the A and B symbols are the same, the fracture trend is unchanged;
if the fracture trend is in the minor axis direction of amplitude, the sign relationship between the isotropic coefficient A and the fracture anisotropy coefficient B is further judged:
if the A and B symbols are the same, the revised crack trend result is as follows:
Figure BDA0003274957680000043
if the signs of A and B are opposite, the crack orientation is unchanged.
In addition, in order to achieve the above object, the present invention also provides a fractured reservoir anisotropic feature identification apparatus, including the following modules:
the azimuth sample division module is used for acquiring pre-stack seismic data and an effective azimuth space, and equally dividing the effective azimuth space to obtain a plurality of azimuth samples;
the inversion calculation module is used for acquiring a sampling azimuth from a plurality of azimuth samples, enabling the initial fracture trend to be equal to the acquired sampling azimuth, and performing inversion calculation on the pre-stack seismic data according to the sampling azimuth to obtain fracture reservoir parameters corresponding to the sampling azimuth;
the forward modeling calculation module is used for performing forward modeling calculation on the fracture reservoir parameters to obtain forward modeling data, calculating a difference value between the forward modeling data and the pre-stack seismic data, and taking an L2 norm of the difference value as a target function;
the target function acquisition module is used for repeating the calculation of the inversion calculation module and the forward calculation module until acquiring the fracture reservoir parameter combinations corresponding to all azimuth angle samples and the corresponding target functions;
the optimal parameter acquisition module is used for calculating the minimum value of the target function, acquiring the fracture trend, the isotropic coefficient and the fracture anisotropic coefficient corresponding to the minimum value of the target function, namely the inversion result of the fracture reservoir parameters, and identifying the anisotropic characteristics of the fracture reservoir according to the inversion result;
and the fracture strike revising module is used for revising the fracture strike direction according to the relation between the fracture strike and the amplitude long axis.
In addition, in order to achieve the above object, the present invention further provides a fractured reservoir anisotropic feature identification device, which includes a memory, a processor and a fractured reservoir anisotropic feature identification program stored in the memory and executable on the processor, wherein the fractured reservoir anisotropic feature identification program, when executed by the processor, implements the steps of the fractured reservoir anisotropic feature identification method.
In addition, in order to achieve the above object, the present invention further provides a storage medium having a fractured reservoir anisotropic feature identification program stored thereon, wherein the fractured reservoir anisotropic feature identification program, when executed by a processor, implements the steps of the fractured reservoir anisotropic feature identification method.
The technical scheme provided by the invention has the following beneficial effects: the method combines system sampling and linear least square inversion, converts a nonlinear fractured reservoir parameter inversion problem into a linear inversion problem based on azimuth system sampling, and improves accuracy and stability of fractured reservoir parameter inversion. Meanwhile, due to the fact that the azimuth angle space is limited, the optimal fractured reservoir parameter can be obtained through limited sampling, and reliability guarantee is provided for the anisotropic feature identification of the fractured reservoir.
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The invention will be further described with reference to the accompanying drawings and examples, in which:
FIG. 1 is a flow chart of a method for identifying anisotropic characteristics of a fractured reservoir according to an embodiment of the invention;
FIG. 2 is a fracture reservoir model according to an embodiment of the present invention;
FIG. 3 is a fracture reservoir prestack azimuth seismic gather data volume according to an embodiment of the invention;
FIG. 4 is a result of inversion identification of fracture reservoir parameters according to an embodiment of the invention;
fig. 5 is a structural diagram of a fracture reservoir anisotropic feature recognition device according to an embodiment of the present invention.
Detailed Description
For a more clear understanding of the technical features, objects and effects of the present invention, embodiments of the present invention will now be described in detail with reference to the accompanying drawings.
Referring to fig. 1, fig. 1 is a flowchart of a method for identifying anisotropic features of a fractured reservoir according to an embodiment of the present invention, where the method includes the following steps:
s1, acquiring pre-stack seismic data and an effective azimuth space, and equally dividing the effective azimuth space to obtain a plurality of azimuth samples.
In this embodiment, S1 specifically includes:
acquiring pre-stack seismic data;
obtaining an effective azimuth angle space of 0-90 degrees;
determining a decimation interval delta, equally dividing the effective azimuth angle space by taking delta as an interval, and generating K-90/delta azimuth angle samples which are respectively: 0, Δ,2 Δ, …, 90- Δ.
S2, obtaining a sampling azimuth angle from the azimuth angle samples, enabling the initial fracture strike to be equal to the obtained sampling azimuth angle, and performing inversion calculation on the pre-stack seismic data according to the sampling azimuth angle to obtain fracture reservoir parameters corresponding to the sampling azimuth angle.
In this embodiment, S2 specifically includes:
in an azimuthal anisotropic medium consisting of vertical fractures, the relationship between the amplitude response of longitudinal waves with fixed offset and the angle between the observed azimuth and the fracture strike is a function of the period pi:
Figure BDA0003274957680000061
wherein F is seismic reflection amplitude, A is an isotropic coefficient, B is a fracture anisotropy coefficient, and is used for representing fracture development strength,
Figure BDA0003274957680000062
is the direction of observation and the direction of observation,
Figure BDA0003274957680000063
the fracture strike, the isotropy coefficient, the fracture anisotropy coefficient and the fracture strike are parameters of a fracture reservoir to be inverted and parameters of the fracture reservoir
Figure BDA0003274957680000064
The inversion of (1) is a nonlinear inversion problem, where superscript T denotes transposition;
performing system sampling on the azimuth angle samples according to a set sequence, for example, according to the sequence of the azimuths from small to large, the azimuth angle sample obtained at the kth time is (k-1) delta, and the initial fracture trend is equal to the sampling azimuth angle:
Figure BDA0003274957680000065
then
Figure BDA0003274957680000066
The fracture reservoir parameter inversion problem is converted from nonlinear inversion into a linear inversion problem:
Figure BDA0003274957680000067
wherein the content of the first and second substances,
Figure BDA0003274957680000068
denotes the ith observation direction, M denotes the observerThe number of bits;
Figure BDA0003274957680000069
the vector is formed by pre-stack seismic data, and the superscript T represents transposition;
inversion of isotropic coefficient A by linear least square methodkAnd crack anisotropy coefficient BkObtaining the fracture reservoir parameter model vector
Figure BDA00032749576800000610
S3, forward calculation is carried out on the fracture reservoir parameters to obtain forward data, the difference between the forward data and the pre-stack seismic data is calculated, and the L2 norm of the difference is taken as a target function.
In this embodiment, S3 specifically includes:
forward calculation is carried out on the fracture reservoir parameters to obtain the fracture strike of
Figure BDA00032749576800000611
The reflection amplitude of time is the forward data:
Figure BDA00032749576800000612
establishing an objective function:
Figure BDA00032749576800000613
wherein m iskRepresenting a fracture reservoir parametric model vector,
Figure BDA0003274957680000071
Akis the isotropic coefficient, BkIs the coefficient of anisotropy of the crack,
Figure BDA0003274957680000072
is the crack direction, FobsAnd FkAre pre-stack seismic data andthe vector of forward-acting data is composed of,
Figure BDA0003274957680000073
Figure BDA0003274957680000074
denotes the ith observation position, i is 1, 2.
And S4, repeating the steps S2 to S3 until the fracture reservoir parameter combinations corresponding to all the azimuth angle samples and the corresponding target functions are obtained.
S5, calculating the minimum value of the target function, obtaining the fracture trend, the isotropy coefficient and the fracture anisotropy coefficient corresponding to the minimum value of the target function, namely the inversion result of the fracture reservoir parameters, and identifying the anisotropic characteristics of the fracture reservoir according to the inversion result.
In this embodiment, step S5 specifically includes:
calculating the minimum value of the target function and the optimal solution of the crack reservoir parameter inversion corresponding to the minimum value:
Figure BDA0003274957680000075
wherein D is a fracture reservoir parameter inversion result space corresponding to all sampling azimuths, J (m)k) Represents an objective function, mkRepresenting a fracture reservoir parametric model vector,
Figure BDA0003274957680000076
optimal solution, A, representing the inversion of fracture reservoir parametersestRepresents the optimal solution of the inversion of the isotropic coefficients, BestRepresents the optimal solution for the inversion of the fracture anisotropy coefficients,
Figure BDA0003274957680000077
and representing the optimal solution of the fracture strike inversion, and identifying the anisotropic characteristics of the fracture reservoir according to the optimal solution.
And S6, revising the fracture strike direction according to the relation between the fracture strike and the amplitude long axis.
In this embodiment, step S6 specifically includes:
judging whether the fracture trend is in the amplitude long axis direction:
if the fracture trend is in the amplitude long axis direction, the sign relationship between the isotropic coefficient A and the fracture anisotropy coefficient B is further judged:
if the signs of A and B are opposite, the revised fracture strike inversion result is as follows:
Figure BDA0003274957680000078
if the A and B symbols are the same, the fracture trend is unchanged;
if the fracture trend is in the minor axis direction of amplitude, the sign relationship between the isotropic coefficient A and the fracture anisotropy coefficient B is further judged:
if the A and B symbols are the same, the revised crack trend result is as follows:
Figure BDA0003274957680000079
if the signs of A and B are opposite, the crack orientation is unchanged.
In an embodiment of the present invention, fig. 2 is a fractured reservoir model according to an embodiment of the present invention, where fig. 2(a) is a background compressional velocity of the fractured reservoir model, fig. 2(b) is a fracture density curve representing that three reservoirs are included in the model, which are a reservoir section 1, a reservoir section 2 and a reservoir section 3, respectively, and fig. 2(c) is a model fracture strike. Fig. 3 is a prestack azimuth seismic gather data volume (prestack seismic data for short) corresponding to a fracture reservoir model. The method is used for carrying out crack reservoir parameter inversion on the prestack azimuth seismic gather data volume. Referring to fig. 4, fig. 4 shows an isotropic coefficient a, a fracture anisotropy coefficient B and a fracture strike obtained by using the method for identifying the anisotropic characteristics of the fractured reservoir of the invention. Wherein, fig. 4(a) shows the seismic reflection record caused by the change of the background velocity, fig. 4(B) shows that the inversion result of the fracture anisotropy coefficient B is matched with the distribution of the fracture reservoir section, and fig. 4(c) shows that the fracture strike inversion result is consistent with the fracture strike of the model. The effectiveness of the invention is verified by the embodiment of the inversion of the parameters of the fractured reservoir.
Referring to fig. 5, fig. 5 is a structural diagram of a fractured reservoir anisotropic feature recognition apparatus according to an embodiment of the present invention, and the embodiment further provides a fractured reservoir anisotropic feature recognition apparatus, including the following modules:
the azimuth sample division module 1 is used for acquiring pre-stack seismic data and an effective azimuth space, and equally dividing the effective azimuth space to obtain a plurality of azimuth samples;
the inversion calculation module 2 is used for acquiring a sampling azimuth from a plurality of azimuth samples, making the initial fracture strike equal to the acquired sampling azimuth, and performing inversion calculation on the pre-stack seismic data according to the sampling azimuth to obtain fracture reservoir parameters corresponding to the sampling azimuth;
the forward calculation module 3 is configured to perform forward calculation on the fracture reservoir parameters to obtain forward data, calculate a difference between the forward data and the pre-stack seismic data, and take an L2 norm of the difference as a target function;
the target function acquisition module 4 is used for repeating the calculation of the inversion calculation module and the forward calculation module until acquiring the fracture reservoir parameter combinations corresponding to all azimuth angle samples and the corresponding target functions;
the optimal parameter obtaining module 5 is used for calculating the minimum value of the target function, obtaining the fracture trend, the isotropic coefficient and the fracture anisotropic coefficient corresponding to the minimum value of the target function, namely obtaining the inversion result of the fracture reservoir parameters, and identifying the anisotropic characteristics of the fracture reservoir according to the inversion result;
and the fracture strike revising module 6 is used for revising the fracture strike direction according to the relation between the fracture strike and the amplitude long axis.
As an optional implementation manner, this embodiment further provides a fractured reservoir anisotropic feature identification device, which includes a memory, a processor, and a fractured reservoir anisotropic feature identification program stored in the memory and executable on the processor, where the fractured reservoir anisotropic feature identification program, when executed by the processor, implements the steps of the fractured reservoir anisotropic feature identification method.
As an optional implementation manner, this embodiment further provides a storage medium, on which a fractured reservoir anisotropic feature identification program is stored, and when being executed by a processor, the fractured reservoir anisotropic feature identification program implements the steps of the fractured reservoir anisotropic feature identification method.
The invention firstly divides the effective azimuth angle space according to the decimation interval; sequentially extracting azimuth angle samples, and inverting an isotropic coefficient and a fracture anisotropy coefficient by using linear least squares on seismic data before stacking on the assumption that the fracture trend is equal to a sampling azimuth angle; performing forward modeling on all fractured reservoir parameter combinations, taking an L2 norm of a difference between forward modeling data and observation data as a target function, and selecting a group of fracture strike, isotropic coefficients and fracture anisotropic parameters with the minimum target function as an optimal solution of the fractured reservoir parameters; and finally, revising the fracture strike angle according to the relation between the fracture strike and the amplitude. The method for inverting the parameters of the fractured reservoir combines system sampling and a least square inversion method, converts the nonlinear fractured reservoir parameter inversion problem into a linear inversion problem based on azimuth system sampling, improves the accuracy and stability of the fractured reservoir parameter inversion, improves the accuracy and stability of identifying the anisotropic characteristics of the fractured reservoir, and verifies the effectiveness of the method through the embodiment.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The use of the words first, second, third and the like do not denote any order, but rather the words first, second and the like may be interpreted as indicating any order.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.

Claims (9)

1. A fracture reservoir anisotropic feature identification method is characterized by comprising the following steps:
s1, acquiring pre-stack seismic data and an effective azimuth space, and equally dividing the effective azimuth space to obtain a plurality of azimuth samples;
s2, acquiring a sampling azimuth from the azimuth samples, enabling the initial fracture trend to be equal to the acquired sampling azimuth, and performing inversion calculation on the pre-stack seismic data according to the sampling azimuth to obtain fracture reservoir parameters corresponding to the sampling azimuth;
s3, forward modeling calculation is carried out on the fracture reservoir parameters to obtain forward modeling data, the difference value between the forward modeling data and the pre-stack seismic data is calculated, and the L2 norm of the difference value is taken as a target function;
s4, repeating the steps S2 to S3 until fracture reservoir parameter combinations corresponding to all azimuth angle samples and corresponding target functions are obtained;
s5, calculating the minimum value of the target function, obtaining the fracture trend, the isotropy coefficient and the fracture anisotropy coefficient corresponding to the minimum value of the target function, namely the inversion result of the fracture reservoir parameters, and identifying the anisotropy characteristic of the fracture reservoir according to the inversion result;
and S6, revising the fracture strike orientation according to the relation between the fracture strike and the amplitude long axis.
2. The method for identifying anisotropic features of a fractured reservoir according to claim 1, wherein the step S1 specifically comprises the following steps:
acquiring prestack seismic data Fobs；
Obtaining an effective azimuth angle space of 0-90 degrees;
determining a decimation interval delta, equally dividing the effective azimuth angle space by taking delta as an interval, and generating K-90/delta azimuth angle samples which are respectively: 0, Δ,2 Δ, …, 90- Δ.
3. The method for identifying anisotropic features of a fractured reservoir according to claim 1, wherein the step S2 specifically comprises:
in an azimuthal anisotropic medium consisting of vertical fractures, the relationship between the amplitude response of longitudinal waves with fixed offset and the angle between the observed azimuth and the fracture strike is a function of the period pi:
Figure FDA0003274957670000011
wherein F is seismic reflection amplitude, A is an isotropic coefficient, B is a fracture anisotropy coefficient, and is used for representing fracture development strength,
Figure FDA0003274957670000012
is the direction of observation and the direction of observation,
Figure FDA0003274957670000013
is to observe the azimuth
Figure FDA0003274957670000014
The amplitude of the seismic reflections of (a) is,
Figure FDA0003274957670000015
is the direction of fractureThe isotropy coefficient, the fracture anisotropy coefficient and the fracture trend are parameters of a fracture reservoir to be inverted and parameters of the fracture reservoir
Figure FDA0003274957670000021
The inversion of (1) is a nonlinear inversion problem, where superscript T denotes transposition;
performing system sampling on azimuth angle samples according to a set sequence, wherein the azimuth angle sample acquired at the kth time is (k-1) delta, and the initial crack trend is equal to the sampling azimuth angle:
Figure FDA0003274957670000022
then
Figure FDA0003274957670000023
The fracture reservoir parameter inversion problem is converted from nonlinear inversion into a linear inversion problem:
Figure FDA0003274957670000024
where, a represents the decimation interval,
Figure FDA0003274957670000025
the number of the ith observation direction is represented, and M represents the number of the observation directions;
Figure FDA0003274957670000026
the vector is formed by pre-stack seismic data, and the superscript T represents transposition;
inversion of isotropic coefficient A by linear least square methodkAnd crack anisotropy coefficient BkObtaining the fracture reservoir parameter model vector
Figure FDA0003274957670000027
4. The method for identifying anisotropic features of a fractured reservoir according to claim 1, wherein the step S3 specifically comprises:
forward calculation is carried out on the fracture reservoir parameters to obtain the fracture strike of
Figure FDA0003274957670000028
The reflection amplitude of time is the forward data:
Figure FDA0003274957670000029
establishing an objective function:
Figure FDA00032749576700000210
wherein m iskRepresenting a fracture reservoir parametric model vector,
Figure FDA00032749576700000211
Akis the isotropic coefficient, BkIs the coefficient of anisotropy of the crack,
Figure FDA00032749576700000212
is the crack direction, FobsAnd FkRespectively vectors consisting of pre-stack seismic data and forward data,
Figure FDA00032749576700000213
Figure FDA00032749576700000214
denotes the ith observation position, i is 1, 2.
5. The method for identifying anisotropic features of a fractured reservoir according to claim 1, wherein the step S5 specifically comprises:
calculating the minimum value of the target function and the optimal solution of the crack reservoir parameter inversion corresponding to the minimum value:
Figure FDA0003274957670000031
wherein D is a fracture reservoir parameter inversion result space corresponding to all sampling azimuth angles, mkRepresenting a fracture reservoir parametric model vector, J (m)k) Representing the objective function, mestAnd expressing the optimal solution of the parameter inversion of the fractured reservoir, and identifying the anisotropic characteristics of the fractured reservoir according to the optimal solution.
6. The method for identifying anisotropic features of a fractured reservoir according to claim 1, wherein the step S6 specifically comprises the following steps:
judging whether the fracture trend is in the amplitude long axis direction:
if the fracture trend is in the amplitude long axis direction, the sign relationship between the isotropic coefficient A and the fracture anisotropy coefficient B is further judged:
if the signs of A and B are opposite, the revised fracture strike inversion result is as follows:
Figure FDA0003274957670000032
Figure FDA0003274957670000033
representing an optimal solution for fracture strike inversion;
if the A and B symbols are the same, the fracture trend is unchanged;
if the fracture trend is in the minor axis direction of amplitude, the sign relationship between the isotropic coefficient A and the fracture anisotropy coefficient B is further judged:
if the A and B symbols are the same, the revised crack trend result is as follows:
Figure FDA0003274957670000034
if A and B are opposite in sign, the crack progression is unchanged.
7. A fracture reservoir anisotropic feature recognition device is characterized by comprising the following modules:
the azimuth sample division module is used for acquiring pre-stack seismic data and an effective azimuth space, and equally dividing the effective azimuth space to obtain a plurality of azimuth samples;
the inversion calculation module is used for acquiring a sampling azimuth from a plurality of azimuth samples, enabling the initial fracture trend to be equal to the acquired sampling azimuth, and performing inversion calculation on the pre-stack seismic data according to the sampling azimuth to obtain fracture reservoir parameters corresponding to the sampling azimuth;
the forward calculation module is used for performing forward calculation on the fracture reservoir parameters to obtain forward data, calculating a difference value between the forward data and the pre-stack seismic data, and taking an L2 norm of the difference value as a target function;
the target function acquisition module is used for repeating the calculation of the inversion calculation module and the forward calculation module until acquiring the fracture reservoir parameter combinations corresponding to all azimuth angle samples and the corresponding target functions;
the optimal parameter acquisition module is used for calculating the minimum value of the target function, acquiring the fracture trend, the isotropic coefficient and the fracture anisotropic coefficient corresponding to the minimum value of the target function, namely the inversion result of the fracture reservoir parameters, and identifying the anisotropic characteristics of the fracture reservoir according to the inversion result;
and the fracture strike revising module is used for revising the fracture strike direction according to the relation between the fracture strike and the amplitude long shaft.
8. A fractured reservoir anisotropic feature identification device comprising a memory, a processor and a fractured reservoir anisotropic feature identification program stored on the memory and executable on the processor, the fractured reservoir anisotropic feature identification program when executed by the processor implementing the steps of the fractured reservoir anisotropic feature identification method as recited in any one of claims 1 to 6.
9. A storage medium having stored thereon a fractured reservoir anisotropic feature identification program, the fractured reservoir anisotropic feature identification program when executed by a processor implementing the steps of the fractured reservoir anisotropic feature identification method according to any one of claims 1 to 6.
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Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106094029A (en) * 2016-08-24 2016-11-09 中国石油集团川庆钻探工程有限公司地球物理勘探公司 The method utilizing offset distance vector sheet geological data Predicating Reservoir Fractures

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CN106556861B (en) * 2015-09-24 2018-11-13 中国石油化工股份有限公司 A kind of azimuthal AVO inversion method based on Omnibearing earthquake auto data
US10386515B2 (en) * 2015-12-04 2019-08-20 Cgg Services Sas Method and apparatus for analyzing fractures using AVOAz inversion
CN112649853B (en) * 2019-10-10 2023-08-11 中国石油化工股份有限公司 Crack parameter prediction method and system based on post-stack data

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106094029A (en) * 2016-08-24 2016-11-09 中国石油集团川庆钻探工程有限公司地球物理勘探公司 The method utilizing offset distance vector sheet geological data Predicating Reservoir Fractures

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