Earthquake AVF analysis method based on improved multi-channel matching pursuit algorithm

Abstract

The invention provides an earthquake AVF analysis method based on an improved multi-channel matching pursuit algorithm, and the method comprises the steps: collecting post-stack earthquake data s (t, x); extracting information of a current seismic channel and a seismic channel adjacent to the current seismic channel from s (t, x), calculating corresponding weighted average seismic channel data, and extracting an instantaneous time-frequency attribute InsFreq (t) of a time-frequency atom corresponding to the weighted average seismic channel data by adopting an optimization algorithm; performing iterative solution to obtain the seismic AVF attribute of the weighted average seismic channel data; for the current seismic data, calculating the seismic AVF attribute corresponding to the weighted average seismic trace data of each seismic trace one by one, and performing iteration until all seismic traces are traversed; and outputting the seismic AVF attributes of all seismic traces of s (t, x). The earthquake AVF analysis method based on the improved multi-channel matching pursuit algorithm has the advantages that the calculation efficiency of earthquake AVF analysis is improved, the result stability and the calculation precision are improved, and the earthquake AVF analysis method is simple, easy to implement, high in efficiency and the like.

Description

Technical Field

[0001] The invention belongs to the technical field of oil and gas field seismic exploration, and in particular relates to a seismic AVF analysis method based on an improved multi-channel matching pursuit algorithm. Background Art

[0002] Seismic exploration is a geophysical exploration method that uses artificially excited elastic waves to exploit differences in the elasticity and density of underground media. By observing and analyzing the propagation patterns of these waves, the properties and morphology of subsurface rock formations can be inferred. It is the most important and effective method in geophysical exploration for addressing oil and gas exploration problems. Seismic exploration generally offers advantages such as wide coverage and deep detection depth, providing crucial information for oil and gas exploration and development. The introduction of three-dimensional seismic exploration has significantly enhanced the ability of seismic data to image the subsurface, providing crucial data for understanding the structural and sedimentary characteristics of underground oil and gas reservoirs. As seismic waves propagate underground, their waveform characteristics, such as frequency, energy, and phase, vary continuously over time. When encountering strata with varying elastic properties, seismic reflections exhibit changes in various properties. Therefore, analyzing the amplitude-with-frequency (AVF) characteristics of seismic waves based on seismic data is crucial for guiding oil and gas exploration and development.

[0003] Seismic AVF interpretation utilizes the rich waveform-frequency information of seismic signals, reducing the uncertainty of conventional interpretation. Several techniques have been developed for seismic AVF analysis. For example, spectral decomposition can scan seismic data across the entire frequency range, generating seismic data volumes with specific dominant frequencies for geological characterization of target layers. This has been widely used for lithology identification and hydrocarbon detection. Seismic AVF analysis and time-frequency analysis share similar principles. The main difference lies in that AVF captures the variation of seismic waveforms with frequency, while time-frequency analysis captures the variation of seismic wave energy with frequency. Both involve transforming from the time domain to the time-frequency domain. Due to the constraints of time and frequency resolution, conventional time-frequency analysis techniques such as short-time Fourier transforms and wavelet transforms cannot simultaneously obtain high-precision spectral information in both the time and frequency domains. While the S-transform combines the advantages of both short-time Fourier transforms and wavelet transforms, its frequency information is inaccurate at frequency discontinuities. The matching pursuit (MP) algorithm is an adaptive seismic signal decomposition technique that adaptively searches for optimal matching atoms and obtains high-precision seismic AVF attributes.

[0004] However, the traditional matching pursuit-based seismic AVF method also has certain problems that need to be solved. For example, it processes seismic data channel by channel. Due to the influence of data noise and algorithm stability, the seismic AVF differences between adjacent channels may be large, which destroys the lateral continuity of the results. In addition, the traditional matching pursuit still has the problem of poor stability in calculating the instantaneous properties of earthquakes, which affects the accuracy of seismic AVF analysis. The full-length atomic inner product of traditional matching pursuit also consumes a lot of computing time, greatly affecting the efficiency of seismic AVF analysis. Therefore, it is necessary to optimize and improve the traditional matching pursuit algorithm to improve the accuracy, stability and efficiency of seismic AVF analysis results. Summary of the Invention

[0005] To solve the above problems, the present disclosure provides a seismic AVF analysis method based on an improved multi-channel matching pursuit algorithm to improve the computational efficiency of seismic AVF analysis and improve the result stability and computational accuracy.

[0006] The present invention provides a seismic AVF analysis method based on an improved multi-channel matching pursuit algorithm, comprising the following steps:

[0007] Step 1: Collect post-stack seismic data s(t, x);

[0008] Step 2: Extract the information of the current seismic trace and the adjacent seismic traces of the current seismic trace from the post-stack seismic data s(t, x), and calculate the corresponding weighted average seismic trace data.

[0009] Step 3: Use optimization algorithm to extract weighted average seismic trace data The instantaneous time-frequency property InsFreq(t) of the corresponding time-frequency atom;

[0010] Step 4: Weighted average seismic trace data Perform iterative solution to obtain weighted average seismic trace data Seismic AVF attributes of;

[0011] Step 5: Calculate the weighted average seismic trace data of each seismic trace for the current seismic data. The corresponding seismic AVF attributes are iterated until all seismic traces are traversed;

[0012] Step 6: Output the seismic AVF attributes of all seismic traces of the post-stack seismic data s(t, x).

[0013] Furthermore, in step 1, the original seismic data is subjected to static correction, denoising, amplitude compensation, velocity analysis, dynamic correction, and migration processing to obtain post-stack seismic data s(t, x).

[0014] Furthermore, in step 2, the weighted average seismic trace data It is calculated by the following formula (1);

[0015]

[0016] In formula (1), a i is the weighting coefficient (i=0,1,...,N-1).

[0017] Furthermore, in step 3, an optimization algorithm is used to extract weighted average seismic trace data. During the calculation of the instantaneous time-frequency property InsFreq(t) of the corresponding time-frequency atom, a damping factor λ is added.

[0018] Furthermore, in the iterative solution process in step 4, the weighted average seismic trace data is calculated in each iteration. The residual waveform corresponds to the seismic atom at a specific time position.

[0019] Furthermore, in the step 4, during the iterative solution process, the iterative process ends when the residual is less than a given threshold.

[0020] Furthermore, in the step 4, during the iterative solution, the best unit seismic atomic g is calculated. r The following formula (11) should be satisfied.

[0021]

[0022] In formula (11), <.,.> represents the inner product operation, is the residual data of seismic trace.

[0023] Furthermore, in step 6, the seismic AVF attributes of all seismic traces of the post-stack seismic data s(t, x) are output, and characteristic analysis of the seismic AVF attributes is performed.

[0024] The present invention also discloses an electronic device, comprising at least one processor and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the seismic AVF analysis method based on the improved multi-channel matching pursuit algorithm.

[0025] The present invention also discloses a computer-readable storage medium storing a computer program; when the computer program is executed by a processor, the seismic AVF analysis method based on the improved multi-channel matching pursuit algorithm is implemented.

[0026] Compared with the prior art, the present disclosure has the following advantages:

[0027] The present invention provides a seismic AVF analysis method based on an improved multi-channel matching pursuit algorithm, comprising: step 1: collecting post-stack seismic data s(t, x); step 2: extracting information of the current seismic trace and the seismic traces adjacent to the current seismic trace from the post-stack seismic data s(t, x), and calculating the corresponding weighted average seismic trace data. Step 3: Use optimization algorithm to extract weighted average seismic trace data The instantaneous time-frequency attribute InsFreq(t) of the corresponding time-frequency atom; Step 4: weighted average seismic trace data Perform iterative solution to obtain weighted average seismic trace data Seismic AVF attributes; Step 5: For the current seismic data, calculate the weighted average seismic trace data of each seismic trace one by one The corresponding seismic AVF attributes are iterated until all seismic traces are traversed; Step 6: output the seismic AVF attributes of all seismic traces of the post-stack seismic data s(t, x).

[0028] The seismic AVF analysis method based on the improved multi-channel matching pursuit algorithm of the present invention improves the traditional seismic AVF analysis theory based on matching pursuit by integrating multiple means such as multi-channel matching pursuit, instantaneous attribute optimization algorithm and limiting the inner product length of seismic atoms. It greatly improves the accuracy and efficiency of seismic AVF analysis, and also improves the lateral continuity and stability of its results, which has important guiding significance for oil and gas reservoir exploration and development.

[0029] The seismic AVF analysis method based on the improved multi-channel matching pursuit algorithm of the present invention has the advantages of improving the calculation efficiency of seismic AVF analysis, improving the stability of results and calculation accuracy, and being simple, easy to operate and highly efficient.

[0030] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0032] Figure 1The flowchart of the seismic AVF analysis method based on the improved multi-channel matching pursuit algorithm of the present invention is shown.

[0033] Figure 2 These are two actual seismic data inputted by the embodiment of the present invention.

[0034] Figure 3 is the instantaneous frequency attribute calculated in this embodiment: ab) corresponds to Figure 2 ab) seismic trace data.

[0035] Figure 4 It is the three-dimensional distribution of earthquake atoms in complex space.

[0036] Figure 5 The trend of the residual energy percentage change in the seismic trace calculated based on traditional single-channel (black) and multi-channel (white) matching pursuit.

[0037] Figure 6 is based on Figure 2 The results of earthquake AVF analysis on the middle channel are shown in the figure. The upper limit of the frequency division is set to 80Hz and the interval is 1Hz. Figure 2 (a), the right side corresponds to Figure 2 (b); Figure 6 (Top) corresponds to the traditional matching pursuit result, Figure 6 (Bottom) shows the calculation results of the improved multi-channel matching pursuit.

[0038] Figure 7 It is the post-stack two-dimensional seismic profile input in the embodiment of the present invention.

[0039] Figure 8 is based on Figure 7 Seismic AVF attribute analysis performed on the post-stack 2D seismic profile in: (left) the amplitude variation characteristics of some extracted seismic traces with frequency and (right) the seismic frequency fraction profile at a specific frequency.

[0040] Figure 9 is based on Figure 8 The seismic frequency profiles extracted from the results are: (upper left) 5Hz frequency profile, (upper right) 15Hz frequency profile, (lower left) 25Hz frequency profile, and (lower right) 35Hz frequency profile.

[0041] Figure 10 is based on Figure 9 The seismic spectrum calculated from the four frequency sections. DETAILED DESCRIPTION

[0042] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0043] The present invention provides a seismic AVF analysis method based on an improved multi-channel matching pursuit algorithm, comprising the following steps:

[0044] Step 1: Collect post-stack seismic data s(t, x);

[0045] Step 2: Extract the information of the current seismic trace and the adjacent seismic traces of the current seismic trace from the post-stack seismic data s(t, x), and calculate the corresponding weighted average seismic trace data.

[0046] Step 3: Use optimization algorithm to extract weighted average seismic trace data The instantaneous time-frequency property InsFreq(t) of the corresponding time-frequency atom;

[0047] Step 4: Weighted average seismic trace data Perform iterative solution to obtain weighted average seismic trace data Seismic AVF attributes of;

[0048] Step 5: Calculate the weighted average seismic trace data of each seismic trace for the current seismic data. The corresponding seismic AVF attributes are iterated until all seismic traces are traversed;

[0049] For each seismic data, firstly calculate the weighted average seismic data by combining its adjacent data. To improve the lateral stability of the seismic AVF attribute. On this basis, the AVF information of the current average seismic trace is iteratively solved in combination with steps 3 and 4, and each seismic data is traversed one by one to obtain the AVF attributes of all seismic traces of the entire seismic data.

[0050] Step 6: Output the seismic AVF attributes of all seismic traces of the post-stack seismic data s(t, x).

[0051] Figure 1This is a flow chart of the seismic AVF analysis method based on the improved multi-channel matching pursuit algorithm. The present invention is proposed on the basis of studying the following problems: (1) The traditional matching pursuit method ignores the lateral correlation characteristics of the seismic data, and the seismic AVF attributes calculated by it are usually less stable in the lateral direction, which affects the accuracy of seismic AVF analysis; by introducing the multi-channel matching pursuit method, the seismic neighborhood information is introduced in the process of calculating the AVF attributes of the current seismic trace, thereby improving the lateral stability of the seismic AVF attribute calculation; (2) The energy of seismic atoms outside a certain range is usually zero, but the traditional method performs atomic comparison through the full-length inner product in the process of seismic atom comparison, which not only greatly reduces the efficiency of seismic AVF analysis, but also the result is easily affected by the interference of adjacent layers, reducing the accuracy of seismic AVF analysis; by reasonably limiting the calculation range of the seismic atom inner product, the efficiency of the algorithm can be improved, and the accuracy can also be reduced. The influence of low-impact earthquake interference comprehensively improves the accuracy and stability of earthquake AVF attribute calculation; (3) The traditional method does not consider the monotonically increasing phase in the process of earthquake phase unwrapping, and the earthquake instantaneous frequency calculated by it has negative frequency values, which does not conform to the physical characteristics of seismic exploration; Therefore, in the process of earthquake phase calculation, by carrying out phase correction to ensure the monotonically increasing phase in the unwrapping process, the possibility of negative earthquake instantaneous frequency can be eliminated; (4) In actual seismic data, due to the influence of factors such as noise, there are sudden changes in earthquake instantaneous phase, which in turn produce instantaneous frequency anomalies; By adding a certain damping factor in the process of instantaneous frequency calculation, the stability of the instantaneous attribute calculation results is improved and the anomalies are suppressed, thereby achieving the purpose of improving the accuracy and stability of earthquake AVF attributes.

[0052] In specific implementation, in step 1, the original seismic data is subjected to static correction, denoising, amplitude compensation, velocity analysis, dynamic correction, and migration processing to obtain post-stack seismic data s(t, x).

[0053] After the original seismic data is collected, the post-stack seismic data undergoes a series of seismic data processing steps, including but not limited to: static correction, denoising, amplitude compensation, velocity analysis, dynamic correction, migration, etc. The final processed post-stack seismic data is equivalent to the data collected under self-excitation and self-collection conditions, which can be recorded as s(t, x), where t represents the two-way travel time of the seismic wave and x is the seismic channel number.

[0054] In the specific implementation, in step 2, the weighted average seismic trace data It is calculated by the following formula (1);

[0055]

[0056] In formula (1), a i is the weighting coefficient (i=0,1,...,N-1).

[0057] Traditional seismic AVF analysis techniques calculate the AVF attributes of each seismic trace, one by one, based on single-channel seismic data. Due to the influence of seismic noise and algorithm stability, the calculated seismic AVF attributes often exhibit lateral discontinuities, compromising the effectiveness of high-precision seismic AVF analysis. Therefore, the present invention addresses the common lateral discontinuities in seismic AVF attributes caused by existing single-channel seismic data-based calculations by incorporating neighboring seismic trace information into the AVF attribute calculation process. This approach enhances the lateral stability and accuracy of seismic AVF attributes.

[0058] For any seismic data, it can be recorded as s0(t), and its adjacent seismic data are recorded as [s1(t), s2(t), ..., s N-1 (t)]. Since s0(t) and [s1(t),s2(t),...,s N-1 (t)] is recorded at a relatively close distance, and there is a strong correlation between it and the adjacent channel seismic waveform. Therefore, the weighted average seismic channel data can be obtained by fusion of the current channel data and the adjacent channel information through weighted average. To improve the lateral stability of seismic AVF analysis results. For a, its value can be adjusted to control the contribution weight of any adjacent trace to the AVF attribute of the current trace. The value of the weight coefficient is generally related to the distance between it and the adjacent trace. The smaller the distance, the larger the weight coefficient, and vice versa.

[0059] In the specific implementation, in step 3, the weighted average seismic trace data is extracted using an optimization algorithm. During the calculation of the instantaneous time-frequency property InsFreq(t) of the corresponding time-frequency atom, a damping factor λ is added.

[0060] The calculation of seismic AVF attributes involves a phase unwrapping process. In real-world data, due to influences such as seismic noise, the instantaneous phase obtained through phase unwrapping does not guarantee a monotonically increasing pattern, resulting in negative values ​​in the calculated instantaneous frequency, which is inconsistent with the physical characteristics of actual seismic exploration. Furthermore, sudden phase shifts at certain time locations can lead to outliers in the instantaneous frequency, with values ​​far exceeding the actual range of variation. Therefore, improvements must be made to the current calculation methods for earthquake instantaneous attributes to improve the accuracy and stability of seismic AVF analysis.

[0061] Assume weighted average seismic trace data The corresponding complex seismic traces Hs(t), Hs(t) are expressed by the following formula (2).

[0062]

[0063] In formula (2), R(t) is the imaginary part of the complex seismic trace Hs(t), that is, the weighted average seismic trace data The Hilbert transform result of ; j represents the imaginary unit. Based on this, the instantaneous phase InsPhase(t) of the seismic trace can be expressed as formula (3).

[0064]

[0065] In formula (3), unwrap(.) represents phase unwrapping. Based on the instantaneous phase InsPhase(t), phase correction is performed to ensure that the instantaneous phase is monotonically increasing in the time dimension, as shown in formula (4).

[0066] InsPhase(t i )≤InsPhase(t i+1 ) (4)

[0067] For the instantaneous frequency InsFreq(t), its relationship with the instantaneous phase InsPhase(t) can be expressed by formula (5).

[0068]

[0069] In formula (5), InsPhase'(t) represents the derivative of the instantaneous phase InsPhase(t), and InsPhase'(t) can be calculated by the following formula (6).

[0070]

[0071] In formula (6), the superscript “′” of R(t) and s(t, x) is a derivative mark, indicating that the derivative is to be obtained.

[0072] Therefore, combining formula (5) and formula (6), the instantaneous frequency InsFreq(t) can be directly written as formula (7).

[0073]

[0074] Based on formula (7), the assumption is expressed as formula (8).

[0075]

[0076] Then the calculation expression of instantaneous frequency InsFreq(t) can be further written as formula (9).

[0077] InsFreq(t)=D -1 b (9)

[0078] Traditional methods typically calculate the instantaneous frequency InsFreq(t) based on equation (9). However, due to factors such as random noise, sudden phase changes may occur in localized seismic traces, leading to abnormal values ​​in the instantaneous frequency calculation. To address this issue, a damping factor λ is added to the instantaneous frequency InsFreq(t) formula to reduce the impact of seismic noise, thereby improving the accuracy and stability of the instantaneous frequency calculation, as expressed in equation (10).

[0079] InsFreq(t)=(D+λE) -1 b (10)

[0080] In formula (10), λ is the damping factor and E represents the unit matrix.

[0081] Adjusting the damping factor can effectively improve the stability of instantaneous frequency extraction. On this basis, the scale factor, amplitude and other parameters of the seismic atom are further calculated to determine the seismic atom corresponding to the current seismic trace at that location.

[0082] In the specific implementation, in the step 4, during the iterative solution, the weighted average seismic trace data is calculated in each iteration. The residual waveform corresponds to the seismic atom at a specific time position.

[0083] In a specific implementation, in step 4, during the iterative solution process, the iterative process ends when the residual is less than a given threshold.

[0084] For the above weighted average seismic trace data The weighted average seismic trace data is calculated in each iteration by an iterative solution method. The residual waveform of the seismic atom corresponding to a specific time position; each iteration determines an atom and adds it to all previous atoms whose main frequency can be classified as the same frequency in the seismic AVF frequency division. Then, the current seismic atom is subtracted from the current seismic residual waveform, and the iteration continues until the residual energy of the seismic trace is less than a given threshold. At this point, a seismic trace can be decomposed into multiple seismic traces with different main frequencies, which are set by the user.

[0085] In the specific implementation, in the step 4, during the iterative solution, the best unit of earthquake atomic g is calculated. r The following formula (11) should be satisfied.

[0086]

[0087] In formula (11), <.,.> represents the inner product operation, is the residual data of seismic trace.

[0088] The inner product operation <.,.> usually consumes a lot of computing power and sharply reduces the efficiency of seismic AVF analysis. Traditional methods perform inner product operations on the entire atomic length. However, analysis shows that the energy of seismic atoms is almost zero outside a certain time range. Calculating the inner product of these atoms not only sharply reduces the algorithm's operating efficiency but also has no practical significance. Therefore, this paper proposes to reasonably limit the atomic inner product length within a specific range to improve the accuracy and efficiency of seismic AVF analysis, as shown in the following formula (12):

[0089]

[0090] In formula (12), l1 and l2 are valid inner product ranges defined by the user, which usually satisfy -l1=l2.

[0091] In specific implementation, in step 6, the seismic AVF attributes of all seismic traces of the post-stack seismic data s(t, x) are output, and characteristic analysis of the seismic AVF attributes is performed.

[0092] Seismic AVF attributes typically add a frequency dimension to the corresponding seismic data: the AVF attribute of a seismic data trace is a two-dimensional profile, that is, the waveform characteristics of the data trace for each defined frequency; the AVF attribute corresponding to a two-dimensional seismic profile is a three-dimensional data volume, while the AVF attribute corresponding to a three-dimensional seismic data volume is four-dimensional data, which can also be regarded as a three-dimensional frequency-separated data volume corresponding to multiple main frequencies. By performing AVF analysis on seismic data, it is possible to accurately evaluate the seismic waveform information at any frequency component and obtain the frequency-separated data volume corresponding to multiple main frequencies of the seismic data, which is of great significance for conducting detailed seismic interpretation and analysis.

[0093] The present invention also discloses an electronic device, comprising at least one processor and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the seismic AVF analysis method based on the improved multi-channel matching pursuit algorithm.

[0094] The present invention also discloses a computer-readable storage medium storing a computer program; when the computer program is executed by a processor, the seismic AVF analysis method based on the improved multi-channel matching pursuit algorithm is implemented.

[0095] Figure 2 These are two actual seismic data inputted by the embodiment of the present invention.

[0096] Figure 3 is the instantaneous frequency attribute calculated in this embodiment: ab) corresponds to Figure 2 ab) seismic trace data. Figure 3As shown in the figure, the earthquake instantaneous frequency (dashed line) obtained by the traditional method may have negative frequency values; in addition, due to the sharp phase changes at certain locations, the earthquake instantaneous frequency obtained by the traditional method may have outliers. In the improved method, by maintaining the monotonically increasing phase during the unwrapping process and adding a damping factor to the instantaneous attribute calculation algorithm to prevent outliers, the instantaneous frequency obtained by the improved method (solid line) eliminates negative frequency values ​​and greatly suppresses outliers compared to the traditional method, ensuring the accuracy and stability of earthquake AVF attribute extraction.

[0097] Figure 4 It represents the three-dimensional distribution of seismic atoms in complex space. Observation shows that the energy of seismic atoms outside the black dot range in the figure is essentially zero. Therefore, in actual calculations, limiting the inner product calculation range can improve operational efficiency, reduce the influence of adjacent layer seismic interference, and comprehensively improve the accuracy and stability of seismic AVF attribute calculations.

[0098] Figure 5 The trend of residual energy percentage in seismic traces calculated using traditional single-channel (black) and multi-channel (white) matching pursuit methods is shown in the figure. As shown in the figure, the multi-channel matching pursuit algorithm converges faster than traditional methods, improving the efficiency of seismic AVF analysis.

[0099] Figure 6 is based on Figure 2 The results of earthquake AVF analysis on the middle channel are shown in the figure. The upper limit of the frequency division is set to 80Hz and the interval is 1Hz. Figure 2 (a), the right side corresponds to Figure 2 (b); Figure 6 (Top) corresponds to the traditional matching pursuit result, Figure 6 (Bottom) shows the results of the improved multi-channel matching pursuit (MCP) method. Comparison shows that the AVF attributes of the seismic traces obtained by the improved MCP method have excellent temporal resolution and higher frequency resolution than the traditional MCP method (indicated by the arrows and ellipses in the figure), demonstrating greater potential for oil and gas indication.

[0100] Figure 7 It is the post-stack two-dimensional seismic profile input in the embodiment of the present invention.

[0101] Figure 8 is based on Figure 7 Seismic AVF attribute analysis performed on the post-stack 2D seismic profile in: (left) the amplitude variation characteristics of some extracted seismic traces with frequency and (right) the seismic frequency fraction profile at a specific frequency.

[0102] Figure 9 is based on Figure 8The seismic frequency profiles extracted from the results are: (upper left) 5Hz frequency profile, (upper right) 15Hz frequency profile, (lower left) 25Hz frequency profile, and (lower right) 35Hz frequency profile.

[0103] Figure 10 is based on Figure 9 It can be observed that, compared with the traditional frequency division method, the seismic frequency division data calculated by the embodiment of the present invention has a wider effective seismic frequency band range and can more effectively characterize its geological characteristics.

[0104] The seismic AVF analysis method based on the improved multi-channel matching pursuit algorithm of the present invention is based on the traditional matching pursuit theory. In order to solve the problem of poor lateral continuity in single-channel seismic AVF analysis, the multi-channel matching pursuit algorithm is introduced to improve the lateral continuity and stability of the seismic AVF analysis results, laying the foundation for high-precision seismic AVF analysis.

[0105] Furthermore, to address the low accuracy and poor stability of traditional matching pursuit-based instantaneous attribute calculations (such as instantaneous frequency and instantaneous phase), this invention employs an optimized instantaneous attribute calculation algorithm, significantly improving the accuracy and stability of these attributes, suppressing the occurrence of negative frequencies and making the results more geophysical. Furthermore, in practice, this invention significantly improves the efficiency of seismic AVF analysis by limiting the inner product calculation range of seismic atoms, reducing the impact of adjacent layer seismic interference, and comprehensively improving the accuracy and stability of seismic AVF attribute calculations.

[0106] The seismic AVF analysis method based on the improved multi-channel matching pursuit algorithm of the present invention has the following advantages.

[0107] 1. This technical solution uses multi-channel matching pursuit technology, which not only optimizes the lateral continuity and stability of seismic AVF attributes, but also improves the computational efficiency of seismic AVF analysis;

[0108] 2. This technical solution adopts an improved method for calculating the instantaneous attributes of seismic time-frequency atoms, which improves the calculation accuracy of parameters such as the instantaneous phase and instantaneous frequency of seismic data, helps suppress abnormal values ​​of seismic AVF attributes, and improves the stability of the results;

[0109] 3. This technical solution significantly improves the efficiency of seismic AVF analysis by limiting the inner product calculation range of seismic atoms, reduces the impact of adjacent layer seismic interference, and comprehensively improves the accuracy and stability of seismic AVF attribute calculation;

[0110] 4. The algorithm of this technical solution is simple and easy to implement, with high operating efficiency, and it is easy to form software functional modules for promotion and application.

[0111] In summary, this technical solution improves the traditional seismic AVF analysis theory based on matching pursuit by combining multiple means such as multi-channel matching pursuit, instantaneous attribute optimization algorithm, and limiting the inner product length of seismic atoms. It greatly improves the accuracy and efficiency of seismic AVF analysis, and also improves the lateral continuity and stability of its results, which has important guiding significance for oil and gas reservoir exploration and development.

[0112] The method presented in this paper not only suppresses negative frequency anomalies in seismic AVF attribute analysis, improving the accuracy of seismic sedimentary analysis, but also significantly improves algorithm efficiency by suppressing atomic inner product lengths and, to a certain extent, suppresses the interference effect of adjacent seismic layers. The multi-channel matching pursuit method significantly optimizes the lateral continuity, stability, and accuracy of seismic AVF attributes. These improvements have significant practical value for the high-precision and efficient extraction of seismic AVF attributes. Therefore, this invention has broad application prospects.

[0113] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above and that the invention can be embodied in other specific forms without departing from the spirit or essential characteristics of the invention. Therefore, the embodiments should be considered in all respects as illustrative and non-restrictive, and the scope of the invention is defined by the appended claims, not the foregoing description, and all variations within the meaning and range of equivalents of the claims are intended to be included therein. Any reference sign in a claim should not be construed as limiting the claim to which it relates.

[0114] In addition, it should be understood that although this specification is described in terms of implementation methods, not every implementation method contains only one independent technical solution. This narrative method of the specification is only for the sake of clarity. Those skilled in the art should regard the specification as a whole. The technical solutions in each embodiment can also be appropriately combined to form other implementation methods that can be understood by those skilled in the art.

Claims

1. A seismic AVF analysis method based on an improved multi-channel matching pursuit algorithm, characterized in that: The method comprises the following steps: Step 1: Collect post-stack seismic data s(t, x); Step 2: Extract the information of the current seismic trace and the adjacent seismic traces of the current seismic trace from the post-stack seismic data s(t, x), and calculate the corresponding weighted average seismic trace data. Step 3: Use optimization algorithm to extract weighted average seismic trace data The instantaneous time-frequency property InsFreq(t) of the corresponding time-frequency atom; Step 4: Weighted average seismic trace data Perform iterative solution to obtain weighted average seismic trace data Seismic AVF attributes of; Step 5: Calculate the weighted average seismic trace data of each seismic trace for the current seismic data. The corresponding seismic AVF attributes are iterated until all seismic traces are traversed; Step 6: Output the seismic AVF attributes of all seismic traces of the post-stack seismic data s(t, x).

2. The seismic AVF analysis method based on the improved multi-channel matching pursuit algorithm according to claim 1 is characterized in that: In step 1, the original seismic data are subjected to static correction, denoising, amplitude compensation, velocity analysis, dynamic correction, and migration processing to obtain post-stack seismic data s(t, x).

3. The seismic AVF analysis method based on the improved multi-channel matching pursuit algorithm according to claim 1 is characterized in that: In step 2, the weighted average seismic trace data Calculated by the following formula (1); In formula (1), a i is the weighting coefficient (i=0,1,...,N-1).

4. The seismic AVF analysis method based on the improved multi-channel matching pursuit algorithm according to claim 1, characterized in that: In step 3, an optimization algorithm is used to extract weighted average seismic trace data. During the calculation of the instantaneous time-frequency property InsFreq(t) of the corresponding time-frequency atom, a damping factor λ is added.

5. The seismic AVF analysis method based on the improved multi-channel matching pursuit algorithm according to claim 1 is characterized in that: In the step 4, during the iterative solution process, the weighted average seismic trace data is calculated in each iteration. The residual waveform corresponds to the seismic atom at a specific time position.

6. The seismic AVF analysis method based on the improved multi-channel matching pursuit algorithm according to claim 5, characterized in that: In step 4, during the iterative solution process, the iterative process ends when the residual is less than a given threshold.

7. The seismic AVF analysis method based on the improved multi-channel matching pursuit algorithm according to claim 1, characterized in that: In the process of the iterative solution in step 4, the best unit of seismic atomic g is calculated. r The following formula (11) should be satisfied: In formula (11), <.,.> represents the inner product operation, is the residual data of seismic trace.

8. The seismic AVF analysis method based on the improved multi-channel matching pursuit algorithm according to claim 1 is characterized in that: In step 6, the seismic AVF attributes of all seismic traces of the post-stack seismic data s(t, x) are output, and a characteristic analysis of the seismic AVF attributes is performed.

9. An electronic device, characterized in that: The invention comprises at least one processor and a memory in communication with the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so as to enable the at least one processor to perform the seismic AVF analysis method based on the improved multi-channel matching pursuit algorithm as described in any one of claims 1 to 8.

10. A computer-readable storage medium storing a computer program; characterized in that: When the computer program is executed by a processor, the seismic AVF analysis method based on the improved multi-channel matching pursuit algorithm according to any one of claims 1 to 8 is implemented.

Images