CN113283454A - Seismic attribute processing method and device, computer equipment and readable storage medium - Google Patents

Seismic attribute processing method and device, computer equipment and readable storage medium Download PDF

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CN113283454A
CN113283454A CN202010103755.XA CN202010103755A CN113283454A CN 113283454 A CN113283454 A CN 113283454A CN 202010103755 A CN202010103755 A CN 202010103755A CN 113283454 A CN113283454 A CN 113283454A
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attribute
seismic
data
amplitude modulation
frequency modulation
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李磊
万忠宏
崔京彬
李全虎
刘迪
姚燕飞
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China National Petroleum Corp
BGP Inc
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BGP Inc
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    • G06F18/00—Pattern recognition
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    • G06F18/25—Fusion techniques
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    • G06—COMPUTING; CALCULATING OR COUNTING
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    • G06F16/29—Geographical information databases
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    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
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Abstract

The embodiment of the invention provides a method and a device for processing seismic attributes, computer equipment and a readable storage medium, wherein the method comprises the following steps: carrying out rotation stacking on the five-dimensional seismic data volumes based on different rotation factor combinations to obtain a plurality of stacked data volumes; decomposing single-channel seismic attribute data in each stacked data volume into a plurality of amplitude modulation-frequency modulation attribute signals, wherein a preset error value is met between the numerical value stacking value of the plurality of amplitude modulation-frequency modulation attribute signals obtained through decomposition and the numerical value of the single-channel seismic attribute data, and all amplitude modulation-frequency modulation attribute signals obtained through decomposition form an attribute signal set; and filtering noise in the attribute signal set, and fusing amplitude modulation-frequency modulation attribute signals in the attribute signal set. The scheme is beneficial to improving the accuracy and reliability of the fusion result, and is beneficial to providing effective, accurate and reliable data basis for application scenes such as oil and gas reservoir prediction, fluid identification, well location deployment and the like.

Description

Seismic attribute processing method and device, computer equipment and readable storage medium
Technical Field
The invention relates to the technical field of oil and gas exploration, in particular to a method and a device for processing seismic attributes, computer equipment and a readable storage medium.
Background
Seismic attributes are any kind of seismic data measurements that can help us to enhance the visual effect of the interval of interest or to numerically describe the structure of interest, and are measures derived from seismic data on the geometric, kinematic, dynamic or statistical features of seismic wave propagation, including curvature, amplitude, waveform, frequency, velocity, attenuation, dip, azimuth, etc. of seismic waves, and the extraction and analysis techniques of seismic attributes have long been used as one of the main research contents for seismic special processing and interpretation. With the development of seismic exploration and computer technology, more and more types of seismic attributes are acquired by people. In actual practice and various theoretical studies, seismic attributes extracted from seismic data are more than three hundred.
With the proliferation of seismic attribute data, one aspect is beneficial for seismic interpretation, but at the same time new challenges are introduced. The interpreter is always troubled by the multi-solution problem of the seismic attributes, and inconsistency and contradiction often exist among various seismic attributes. In order to solve the problem of contradiction among multiple seismic attributes and improve the reliability of explanation, people in geophysics propose comprehensive utilization of the multiple seismic attributes. Fold-over display is the earliest means of processing multiple seismic attributes, and in view of image processing techniques, two or more seismic attributes are displayed under the same image condition by low-fold. Although superposition display is beneficial to observation of interpreters, the result of superposition display still cannot overcome the influence caused by factors such as multiple solutions of seismic attributes, inconsistency among multiple seismic attributes, contradiction and the like, so that the result data processed by multiple seismic attributes is inaccurate and unreliable, and effective, accurate and reliable data basis cannot be provided for application scenes such as oil and gas reservoir prediction, fluid identification, well location deployment and the like.
Disclosure of Invention
The embodiment of the invention provides a method for processing seismic attributes, which aims to solve the technical problems of inaccurate and unreliable result data after multi-seismic attribute processing in the prior art. The method comprises the following steps:
carrying out rotation stacking on the five-dimensional seismic data volumes based on different rotation factor combinations to obtain a plurality of stacked data volumes;
decomposing single-channel seismic attribute data in each stacked data volume into a plurality of amplitude modulation-frequency modulation attribute signals, wherein a preset error value is met between the numerical value stacking value of the plurality of amplitude modulation-frequency modulation attribute signals obtained through decomposition and the numerical value of the single-channel seismic attribute data, and all amplitude modulation-frequency modulation attribute signals obtained through decomposition form an attribute signal set;
and filtering noise in the attribute signal set, and fusing amplitude modulation-frequency modulation attribute signals in the attribute signal set.
The embodiment of the invention also provides a processing device of the seismic attributes, which is used for solving the technical problems of inaccuracy and unreliability of result data after multi-seismic attribute processing in the prior art. The device includes:
the stacking data volume acquisition module is used for rotationally stacking the five-dimensional seismic data volume based on different twiddle factor combinations to obtain a plurality of stacking data volumes;
the decomposition module is used for decomposing the single-channel seismic attribute data in the stacked data volume into a plurality of amplitude modulation-frequency modulation attribute signals aiming at each stacked data volume, the numerical value superposition value of the plurality of amplitude modulation-frequency modulation attribute signals obtained through decomposition and the numerical value of the single-channel seismic attribute data meet a preset error value, and all amplitude modulation-frequency modulation attribute signals obtained through decomposition form an attribute signal set;
and the fusion module is used for filtering noise in the attribute signal set and fusing the amplitude modulation-frequency modulation attribute signals in the attribute signal set.
The embodiment of the invention also provides computer equipment which comprises a memory, a processor and a computer program which is stored on the memory and can be run on the processor, wherein the processor realizes the processing method of any seismic attribute when executing the computer program so as to solve the technical problems of inaccuracy and unreliability of result data after multi-seismic attribute processing in the prior art.
The embodiment of the invention also provides a computer readable storage medium, wherein a computer program for executing the processing method of any seismic attribute is stored in the computer readable storage medium, so that the technical problems of inaccuracy and unreliability of result data after multi-seismic attribute processing in the prior art are solved.
In the embodiment of the invention, five-dimensional seismic data volumes are subjected to rotation superposition based on different twiddle factor combinations to obtain a plurality of superposed data volumes, then single-channel seismic attribute data in the superposed data volumes are decomposed into a plurality of amplitude modulation-frequency modulation attribute signals aiming at each superposed data volume, all the amplitude modulation-frequency modulation attribute signals obtained by decomposition form an attribute signal set, after noise in the attribute signal set is filtered, the amplitude modulation-frequency modulation attribute signals in the attribute signal set are fused, the fusion process enables the fused result to effectively eliminate redundant information among multiple seismic attributes, avoids and overcomes influences caused by factors such as multiple solutions of seismic attributes, inconsistency among multiple seismic attributes and contradiction, fully utilizes complementary information among the multiple seismic attributes at the same time, and is favorable for improving the accuracy of the fused result, And the reliability is favorable for providing effective, accurate and reliable data basis for application scenes such as oil and gas reservoir prediction, fluid identification, well location deployment and the like.
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The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the principles of the invention. In the drawings:
FIG. 1 is a flow chart of a method for processing seismic attributes provided by an embodiment of the invention;
FIG. 2 is a schematic diagram of an image before processing according to an embodiment of the present invention;
FIG. 3 is a schematic illustration of the image of FIG. 2 after being processed by a seismic attribute processing method according to an embodiment of the present invention;
FIG. 4 is a block diagram of a computer device according to an embodiment of the present invention;
fig. 5 is a block diagram of a seismic attribute processing device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail with reference to the following embodiments and accompanying drawings. The exemplary embodiments and descriptions of the present invention are provided to explain the present invention, but not to limit the present invention.
In an embodiment of the present invention, a method for processing seismic attributes is provided, as shown in fig. 1, the method includes:
step 102: carrying out rotation stacking on the five-dimensional seismic data volumes based on different rotation factor combinations to obtain a plurality of stacked data volumes;
step 104: decomposing single-channel seismic attribute data in each stacked data volume into a plurality of amplitude modulation-frequency modulation attribute signals, wherein a preset error value is met between the numerical value stacking value of the plurality of amplitude modulation-frequency modulation attribute signals obtained through decomposition and the numerical value of the single-channel seismic attribute data, and all amplitude modulation-frequency modulation attribute signals obtained through decomposition form an attribute signal set;
step 106: and filtering noise in the attribute signal set, and fusing amplitude modulation-frequency modulation attribute signals in the attribute signal set.
It can be known from the flow shown in fig. 1 that, in the embodiment of the present invention, a plurality of stacked data volumes are obtained by performing rotation stacking on five-dimensional seismic data volumes based on different twiddle factor combinations, and then for each stacked data volume, single-channel seismic attribute data in the stacked data volume is decomposed into a plurality of am-fm attribute signals, all the am-fm attribute signals obtained by decomposition form an attribute signal set, after noise in the attribute signal set is filtered, the am-fm attribute signals in the attribute signal set are fused, and the fusion process enables the fused result to effectively eliminate redundant information among multiple seismic attributes, avoids and overcomes the influence caused by factors such as multiple solutions of seismic attributes, inconsistency and contradiction among multiple seismic attributes, and simultaneously fully utilizes complementary information among multiple seismic attributes, which is beneficial to improving the accuracy of the fused result, And the reliability is favorable for providing effective, accurate and reliable data basis for application scenes such as oil and gas reservoir prediction, fluid identification, well location deployment and the like.
In specific implementation, the five-dimensional seismic data volume is seismic CRP gather data with information such as x, y, z, offset, azimuth and the like.
In specific implementation, in order to further improve the accuracy and reliability of the fusion result, in this embodiment, the five-dimensional seismic data volume may be rotated and stacked based on different rotation factor combinations through the following steps to obtain a plurality of stacked data volumes:
carrying out rotation stacking on data in the five-dimensional seismic data volume according to the following formula of a rotation stacking template to obtain a stacked data volume, wherein different scale factors and different rotation angles form different rotation factor combinations:
Figure BDA0002387782000000041
wherein F (x, sigma) is a one-dimensional function,
Figure BDA0002387782000000042
x is an offsetThe distance, σ, is a scale factor,
Figure BDA0002387782000000043
to rotate by an angle theta at an offset and scale factorhThe rotation matrix of (a) is,
Figure BDA0002387782000000044
in practical implementation, the scale factor σ needs to be set to different values in advance according to actual data, for example, to three sizes, i.e., σ ═ σ1,σ2,σ3]Angle of rotation thetahMay be a plurality of values, for example, the rotation angle θhThe discretized value range is as follows: thetah＝[θ1,θ2,θ3,θ4,θ5,θ6]Different scale factors sigma and different rotation angles thetahForming different twiddle factor combinations, wherein the different twiddle factor combinations correspond to different data in a five-dimensional seismic data body, performing rotary stacking on the five-dimensional seismic data body based on a formula of a rotary stacking template, namely performing stacking operation only on data in the five-dimensional seismic data body in the direction corresponding to the rotary stacking template, performing no correlation analysis on data outside the direction corresponding to the rotary stacking template, and performing rotary stacking according to the formula of the rotary stacking template under the different twiddle factor combinations, namely performing rotary stacking
Figure BDA0002387782000000045
(u, v) are new point coordinates obtained after the original coordinates (s, t) are transformed, different rotation factors are combined to rotate and overlap different overlapped data bodies, for example, the scale factor sigma has 3 different values, and the rotation angle theta ishIf there are 6 different values, then pass different scale factors sigma and different rotation angles thetahThe composition can obtain 18 different twiddle factor combinations, and further obtain a superposition data volume
Figure BDA0002387782000000051
T18, i.e. 18 different superimposed data volumes.
In specific implementation, in order to further improve the accuracy and reliability of the fusion result, in this embodiment, the decomposed am-fm attribute signals and the single-channel seismic attribute data satisfy the following objective function:
Figure BDA0002387782000000052
wherein L (-) is an optimization objective function,<·，·>representing the inner product between the multivariate variables,
Figure BDA0002387782000000053
is an amplitude-modulated-frequency-modulated attribute signal,
Figure BDA0002387782000000054
is the instantaneous frequency of the corresponding component, λ is the Lagrangian, α is the penalty factor, S is the predetermined decomposed AM-FM attribute signal
Figure BDA0002387782000000055
Is a Dirac function (i.e., Dirac delta function), is a convolution operator, and f isijFor a single trace of seismic attribute data to be decomposed,
Figure BDA0002387782000000056
and in the partial derivative calculation of the variable t, i and j are index variables and represent jth seismic attribute data in the ith stacked data volume, and t is the index variable and represents time.
Figure BDA0002387782000000057
Showing that each am-fm attribute signal is transformed by Hilbert
Figure BDA0002387782000000058
Becomes an analytic signal so that a real signal
Figure BDA0002387782000000059
And converted into a complex-valued signal, thereby obtaining a single-sided spectrum.
Specifically, the use of the penalty factor α and the lagrangian λ in the objective function realizes the conversion of the constraint problem of the above formula into an unconstrained problem and the solution thereof.
In specific implementation, the solution of the objective function adopts a method of iterative update and gradual optimization, namely, n represents the iteration number,
Figure BDA00023877820000000510
and
Figure BDA00023877820000000511
Figure BDA0002387782000000061
is the current remaining variable
Figure BDA0002387782000000062
The difference in the orthogonality of the signals,
Figure BDA0002387782000000063
for the center frequency of the current component power spectrum,
Figure BDA0002387782000000064
the real part can obtain the final decomposition result by expressing the inverse Fourier transform
Figure BDA0002387782000000065
α (n) is a linear function α (n) of 1/n which is gradually smaller according to the number of iterations. As the number of iterations increases, if
Figure BDA0002387782000000066
If this is true, the algorithm stops and k is a predetermined threshold.
In specific implementation, in order to further improve the accuracy and reliability of the fusion result, in this embodiment, the noise in the attribute signal set may be filtered out through the following steps, and then the amplitude modulation-frequency modulation attribute signals in the attribute signal set are fused, for example, the attribute signal set is used as observation data, and for each amplitude modulation-frequency modulation attribute signal in the attribute signal set, a known well-known common sense algorithm is used to determine whether a plurality of amplitude modulation-frequency modulation attribute signals corresponding to each single-channel seismic attribute data are independent;
aiming at independent single-channel seismic attribute data among a plurality of amplitude modulation-frequency modulation attribute signals, determining the energy of each amplitude modulation-frequency modulation attribute signal, and filtering the amplitude modulation-frequency modulation attribute signals with the energy smaller than a preset value as noise;
and fusing all amplitude modulation-frequency modulation attribute signals after noise is filtered.
Specifically, the obtained attribute signal set is used as observation data x, fixed-point Fast-ICA (well-known common perception algorithm) is adopted for each amplitude modulation-frequency modulation attribute signal in the attribute signal set, whether a plurality of amplitude modulation-frequency modulation attribute signals corresponding to each single-channel seismic attribute data are independent or not is judged and decomposed by utilizing mutual information, independent components are obtained, namely independent components are obtained based on an adaptive independent component analysis algorithm, the energy of each amplitude modulation-frequency modulation attribute signal is determined for the independent single-channel seismic attribute data among the plurality of amplitude modulation-frequency modulation attribute signals, the energy of each amplitude modulation-frequency modulation attribute signal is subjected to descending order sorting, the amplitude modulation-frequency modulation attribute signal with the smaller energy in the last 10 percent is regarded as noise, the noise is filtered in a self-adaptive manner, the amplitude modulation-frequency modulation attribute signal with the larger energy in the first 80 percent is extracted as a main independent component, and adding all the main independent components to obtain fused final seismic attribute data, wherein the attribute fusion processing can further contribute to improving the precision of a prediction result and reducing the risk of oil gas deployed at a well position.
The method for processing the seismic attributes is described in detail below, and comprises the following steps:
1) rotating and stacking the five-dimensional pre-stack seismic data volume by a self-adaptive rotating and stacking template method based on different rotating factor combinations to obtain a plurality of stacked data volumes GiI is 1 … T, T is the number of superimposed data volumes；
2) Using superimposed data volumes GiCurvature seismic attribute data volume R for computing well-known axiomiI is 1 … T, T is the number of superimposed data volumes;
3) each seismic data volume RiDecomposing into sum form of multiple AM-FM attribute signals, and forming attribute signal set R from AM-FM attribute signals obtained by decompositionijJ is 1 … M, where M is the number of each am-fm attribute signal determined in advance;
4) let x be { R ═ RijAdopting Fast-ICA algorithm to decompose x to obtain independent component
Figure BDA0002387782000000071
stFor each independent component, J is the number of independent components of a co-decomposition, which can be specified by the user before the algorithm operation, { s }tThe independent component set obtained by final decomposition is obtained;
5) adaptively filtering | stA component of | < 0.1 × | and let
Figure BDA0002387782000000072
P is the sum of the final components remaining after filtering out the low-energy components, wherein,
Figure BDA0002387782000000073
u is the minimum value that satisfies the condition.
In specific implementation, as shown in fig. 2 and 3, compared with the data before processing, the data fused by the seismic attribute processing method has the advantages that the result data after processing is clearer and the characteristics are more obvious.
In this embodiment, a computer device is provided, as shown in fig. 4, comprising a memory 402, a processor 404, and a computer program stored on the memory and executable on the processor, wherein the processor implements any of the above-mentioned methods for processing seismic attributes when executing the computer program.
In particular, the computer device may be a computer terminal, a server or a similar computing device.
In the present embodiment, there is provided a computer-readable storage medium storing a computer program for executing the processing method of the seismic attribute as described above.
In particular, computer-readable storage media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer-readable storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable storage medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
Based on the same inventive concept, the embodiment of the present invention further provides a processing apparatus for seismic attributes, as described in the following embodiments. Because the principle of the processing device for seismic attributes for solving the problems is similar to the processing method for seismic attributes, the implementation of the processing device for seismic attributes can refer to the implementation of the processing method for seismic attributes, and repeated details are not repeated. As used hereinafter, the term "unit" or "module" may be a combination of software and/or hardware that implements a predetermined function. Although the means described in the embodiments below are preferably implemented in software, an implementation in hardware, or a combination of software and hardware is also possible and contemplated.
Fig. 5 is a block diagram showing a configuration of a seismic attribute processing apparatus according to an embodiment of the present invention, and as shown in fig. 5, the apparatus includes:
a stacked data volume obtaining module 502, configured to perform rotation stacking on five-dimensional seismic data volumes based on different twiddle factor combinations to obtain multiple stacked data volumes;
the decomposition module 504 is configured to decompose, for each stacked data volume, the single-channel seismic attribute data in the stacked data volume into multiple am-fm attribute signals, a preset error value is satisfied between a numerical value superposition value of the multiple am-fm attribute signals obtained through decomposition and a numerical value of the single-channel seismic attribute data, and all the am-fm attribute signals obtained through decomposition constitute an attribute signal set;
and a fusion module 506, configured to filter noise in the attribute signal set, and then fuse the am-fm attribute signals in the attribute signal set.
In an embodiment, the stacked data volume obtaining module is specifically configured to perform rotation stacking on data in a five-dimensional seismic data volume according to the following formula of a rotation stacking template to obtain a stacked data volume, where different scale factors and different rotation angles form different rotation factor combinations:
Figure BDA0002387782000000081
wherein F (x, sigma) is a one-dimensional function,
Figure BDA0002387782000000082
x is the offset, σ is the scale factor,
Figure BDA0002387782000000083
to rotate by an angle theta at an offset and scale factorhThe rotation matrix of (a) is,
Figure BDA0002387782000000084
in one embodiment, the am-fm attribute signals decomposed by the decomposition module and the single-channel seismic attribute data satisfy the following objective function:
Figure BDA0002387782000000085
wherein L (-) is an optimization objective function,<·，·>representing the inner product between the multivariate variables,
Figure BDA0002387782000000091
is an amplitude-modulated-frequency-modulated attribute signal,
Figure BDA0002387782000000092
is the instantaneous frequency of the corresponding component, λ is the Lagrangian, α is the penalty factor, S is the predetermined decomposed AM-FM attribute signal
Figure BDA0002387782000000093
Is a Dirac function, is a convolution operator, fijFor a single trace of seismic attribute data to be decomposed,
Figure BDA0002387782000000094
and in the partial derivative calculation of the variable t, i and j are index variables and represent jth seismic attribute data in the ith stacked data volume, and t is the index variable and represents time.
In one embodiment, the fusion module includes:
the de-noising unit is used for taking the attribute signal set as observation data, and determining whether a plurality of amplitude modulation-frequency modulation attribute signals corresponding to each single-channel seismic attribute data are independent or not by adopting a known common sense algorithm aiming at each amplitude modulation-frequency modulation attribute signal in the attribute signal set; aiming at independent single-channel seismic attribute data among a plurality of amplitude modulation-frequency modulation attribute signals, determining the energy of each amplitude modulation-frequency modulation attribute signal, and filtering the amplitude modulation-frequency modulation attribute signals with the energy smaller than a preset value as noise;
and the fusion unit is used for fusing all amplitude modulation-frequency modulation attribute signals after noise is filtered. .
The embodiment of the invention realizes the following technical effects: the method comprises the steps of rotationally stacking five-dimensional seismic data volumes based on different twiddle factor combinations to obtain a plurality of stacked data volumes, further decomposing single-channel seismic attribute data in the stacked data volumes into a plurality of amplitude modulation-frequency modulation attribute signals aiming at each stacked data volume, forming an attribute signal set by all amplitude modulation-frequency modulation attribute signals obtained through decomposition, filtering noise in the attribute signal set, and then fusing the amplitude modulation-frequency modulation attribute signals in the attribute signal set The application scenarios such as fluid identification, well location deployment and the like provide effective, accurate and reliable data basis.
It will be apparent to those skilled in the art that the modules or steps of the embodiments of the invention described above may be implemented by a general purpose computing device, they may be centralized on a single computing device or distributed across a network of multiple computing devices, and alternatively, they may be implemented by program code executable by a computing device, such that they may be stored in a storage device and executed by a computing device, and in some cases, the steps shown or described may be performed in an order different than that described herein, or they may be separately fabricated into individual integrated circuit modules, or multiple ones of them may be fabricated into a single integrated circuit module. Thus, embodiments of the invention are not limited to any specific combination of hardware and software.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the present invention, and various modifications and changes may be made to the embodiment of the present invention by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (10)

1. A method of processing seismic attributes, comprising:
carrying out rotation stacking on the five-dimensional seismic data volumes based on different rotation factor combinations to obtain a plurality of stacked data volumes;
decomposing single-channel seismic attribute data in each stacked data volume into a plurality of amplitude modulation-frequency modulation attribute signals, wherein a preset error value is met between the numerical value stacking value of the plurality of amplitude modulation-frequency modulation attribute signals obtained through decomposition and the numerical value of the single-channel seismic attribute data, and all amplitude modulation-frequency modulation attribute signals obtained through decomposition form an attribute signal set;
and filtering noise in the attribute signal set, and fusing amplitude modulation-frequency modulation attribute signals in the attribute signal set.
2. The method of processing seismic attributes of claim 1 wherein performing a rotational stack of a five-dimensional seismic data volume based on different combinations of twiddle factors comprises:
carrying out rotation stacking on data in the five-dimensional seismic data volume according to the following formula of a rotation stacking template to obtain a stacked data volume, wherein different scale factors and different rotation angles form different rotation factor combinations:
Figure FDA0002387781990000011
wherein F (x, sigma) is a one-dimensional function,
Figure FDA0002387781990000012
x is the offset, σ is the scale factor,
Figure FDA0002387781990000013
to rotate by an angle theta at an offset and scale factorhThe rotation matrix of (a) is,
Figure FDA0002387781990000014
3. the method of claim 1, wherein the decomposed am-fm attribute signals and the single trace seismic attribute data satisfy the following objective function:
Figure FDA0002387781990000015
wherein L (-) is an optimization objective function,<·，·>representing the inner product between the multivariate variables,
Figure FDA0002387781990000016
is an amplitude-modulated-frequency-modulated attribute signal,
Figure FDA0002387781990000017
is the instantaneous frequency of the corresponding component, λ is the Lagrangian, α is the penalty factor, S is the predetermined decomposed AM-FM attribute signal
Figure FDA0002387781990000021
Is a Dirac function, is a convolution operator, fijFor a single trace of seismic attribute data to be decomposed,
Figure FDA0002387781990000022
and in the partial derivative calculation of the variable t, i and j are index variables and represent jth seismic attribute data in the ith stacked data volume, and t is the index variable and represents time.
4. The method for processing seismic attributes as claimed in any of claims 1 to 3, wherein filtering out noise in the attribute signal set and then fusing AM-FM attribute signals in the attribute signal set comprises: taking the attribute signal set as observation data, and determining whether a plurality of amplitude modulation-frequency modulation attribute signals corresponding to each single-channel seismic attribute data are independent or not by adopting a known axiom algorithm aiming at each amplitude modulation-frequency modulation attribute signal in the attribute signal set;
aiming at independent single-channel seismic attribute data among a plurality of amplitude modulation-frequency modulation attribute signals, determining the energy of each amplitude modulation-frequency modulation attribute signal, and filtering the amplitude modulation-frequency modulation attribute signals with the energy smaller than a preset value as noise;
and fusing all amplitude modulation-frequency modulation attribute signals after noise is filtered.
5. A seismic attribute processing apparatus, comprising:
the stacking data volume acquisition module is used for rotationally stacking the five-dimensional seismic data volume based on different twiddle factor combinations to obtain a plurality of stacking data volumes;
the decomposition module is used for decomposing the single-channel seismic attribute data in the stacked data volume into a plurality of amplitude modulation-frequency modulation attribute signals aiming at each stacked data volume, the numerical value superposition value of the plurality of amplitude modulation-frequency modulation attribute signals obtained through decomposition and the numerical value of the single-channel seismic attribute data meet a preset error value, and all amplitude modulation-frequency modulation attribute signals obtained through decomposition form an attribute signal set;
and the fusion module is used for filtering noise in the attribute signal set and fusing the amplitude modulation-frequency modulation attribute signals in the attribute signal set.
6. The seismic attribute processing apparatus of claim 5, wherein the stacked data volume acquisition module is specifically configured to perform rotation stacking on data in a five-dimensional seismic data volume according to the following formula of a rotation stacking template to obtain a stacked data volume, and different scale factors and different rotation angles form different rotation factor combinations:
Figure FDA0002387781990000023
wherein F (x, sigma) is a one-dimensional function,
Figure FDA0002387781990000024
x is the offset and σ is the scale factor，
Figure FDA0002387781990000025
To rotate by an angle theta at an offset and scale factorhThe rotation matrix of (a) is,
Figure FDA0002387781990000026
7. the seismic attribute processing apparatus of claim 5, wherein the AM-FM attribute signals decomposed by the decomposition module and the single-trace seismic attribute data satisfy the following objective function:
Figure FDA0002387781990000031
wherein L (-) is an optimization objective function,<·，·>representing the inner product between the multivariate variables,
Figure FDA0002387781990000032
is an amplitude-modulated-frequency-modulated attribute signal,
Figure FDA0002387781990000033
is the instantaneous frequency of the corresponding component, λ is the Lagrangian, α is the penalty factor, S is the predetermined decomposed AM-FM attribute signal
Figure FDA0002387781990000034
Is a Dirac function, is a convolution operator, fijFor a single trace of seismic attribute data to be decomposed,
Figure FDA0002387781990000035
and in the partial derivative calculation of the variable t, i and j are index variables and represent jth seismic attribute data in the ith stacked data volume, and t is the index variable and represents time.
8. The apparatus for processing seismic attributes of any of claims 5 to 7, wherein the fusion module comprises:
the de-noising unit is used for taking the attribute signal set as observation data, and determining whether a plurality of amplitude modulation-frequency modulation attribute signals corresponding to each single-channel seismic attribute data are independent or not by adopting a known common sense algorithm aiming at each amplitude modulation-frequency modulation attribute signal in the attribute signal set; aiming at independent single-channel seismic attribute data among a plurality of amplitude modulation-frequency modulation attribute signals, determining the energy of each amplitude modulation-frequency modulation attribute signal, and filtering the amplitude modulation-frequency modulation attribute signals with the energy smaller than a preset value as noise;
and the fusion unit is used for fusing all amplitude modulation-frequency modulation attribute signals after noise is filtered.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method of processing the seismic attribute of any of claims 1 to 4 when executing the computer program.
10. A computer-readable storage medium characterized in that the computer-readable storage medium stores a computer program that executes the seismic-attribute processing method according to any one of claims 1 to 4.
CN202010103755.XA 2020-02-20 2020-02-20 Seismic attribute processing method and device, computer equipment and readable storage medium Pending CN113283454A (en)

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