Seismic trace set optimization method and system based on phase constraint

Abstract

This invention provides a phase-constrained seismic gather optimization method and system, belonging to the field of seismic data processing technology. The method includes: acquiring seismic signals; processing the seismic signals into a corresponding frequency domain form; constructing a symmetric signal based on the frequency domain form of the seismic signals; constructing an initial loss function based on the trace form of the seismic signals; correcting the initial loss function based on a weighting coefficient matrix to obtain a final loss function; processing the acquired seismic signals into a two-dimensional Hessian matrix; constructing constraint terms based on the two-dimensional Hessian matrix; constructing an objective function based on the final loss function and the constraint terms; and solving the objective function to obtain the optimized seismic gather. This invention introduces phase constraints for noise removal, ensuring the accuracy of the seismic gather optimization results.

Description

Technical Field

[0001] This invention relates to the field of seismic data processing technology, and more specifically to a phase-constrained seismic gather optimization method and a phase-constrained seismic gather optimization system. Background Technology

[0002] In gather optimization, current research primarily focuses on two aspects: random noise reduction and gather flattening. Firstly, regarding random noise reduction, methods mainly include inverse filtering, statistical methods, and regularization-based methods, including classical denoising methods and constructive guided filtering. These methods consider the impact of noise from different research perspectives, but each has its limitations. Secondly, regarding gather flattening, there are two main types of methods: flattening based on velocity adjustment and flattening based on statistical effects. These two techniques are generally used in combination, and there is no unified approach to addressing this issue. Furthermore, the introduction of phase constraints is often avoided in most studies due to the difficulty in optimizing solutions. It is precisely because existing methods cannot incorporate phase constraints for seismic gather processing that some noise cannot be eliminated, leading to inaccurate gather optimization results. To address the issue of low accuracy in gather optimization results in existing schemes, a new seismic gather optimization scheme needs to be developed. Summary of the Invention

[0003] The purpose of this invention is to provide a phase-constrained seismic gather optimization method to at least solve the problem of low accuracy of gather optimization results in existing gather optimization schemes.

[0004] To achieve the above objectives, a first aspect of the present invention provides a phase-constrained seismic gather optimization method, the method comprising: acquiring seismic signals; processing the seismic signals into a corresponding frequency domain form; constructing a symmetrical signal based on the frequency domain form of the seismic signals; obtaining multi-channel seismic signals by combining individual seismic signals in the gather based on the symmetrical signal; constructing an initial loss function based on the multi-channel seismic signals; performing weight coefficient allocation on each individual seismic signal; constructing a weight coefficient matrix based on the allocation result; and correcting the initial loss function based on the weight coefficient matrix to obtain a final loss function; processing the acquired seismic signals into a two-dimensional Hessian matrix; constructing constraint terms based on the two-dimensional Hessian matrix; constructing an objective function based on the final loss function and the constraint terms; and solving the objective function to obtain the optimized seismic gather.

[0005] Optionally, the processing rule for converting the seismic signal into its corresponding frequency domain form is as follows:

[0006] s = F -1 Ae-jθ

[0007] Where s is the time-domain seismic signal; F -1 θ is the Fourier inverse matrix; A is the amplitude spectrum of the seismic signal; θ is the phase of the seismic signal.

[0008] Optionally, the symmetrical signal is represented as:

[0009]

[0010] Where s is the seismic signal; s' is the inverted form of s; s * Construct new symmetric signal vectors for both.

[0011] Optionally, after constructing a symmetrical signal based on the seismic signal in the frequency domain form, the method further includes: processing the symmetrical signal into a corresponding frequency domain form; determining the imaginary part of the symmetrical signal as zero based on the frequency domain form, and constructing a corresponding first real-domain signal based on a real-domain signal construction function; wherein the real-domain signal construction function is:

[0012]

[0013] in, θ is the real part of the Fourier inverse matrix; Acos(θ) is a real vector; θ is the phase of the seismic signal.

[0014] Optionally, obtaining multi-channel seismic signals based on the symmetrical signal by combining individual channel seismic signals in the combined trace set includes: obtaining the phase function of each individual channel seismic signal based on the real-domain signal; arranging the individual channel seismic signals into a one-dimensional matrix to obtain the corresponding multi-channel seismic signals.

[0015] The multichannel seismic signal is represented as follows:

[0016]

[0017] in, For multichannel seismic signals; s N (θ) represents the Nth single-channel seismic signal; N is the number of channels in the gather.

[0018] Optionally, the initial loss function is:

[0019]

[0020] in, This is the original earthquake record.

[0021] Optionally, the step of assigning weight coefficients to each single-channel seismic signal, constructing a weight coefficient matrix based on the assignment results, and modifying the initial loss function based on the weight coefficient matrix to obtain the final loss function includes: evaluating the gather quality of each single-channel seismic signal based on signal quality, and ranking the single-channel seismic signals based on the evaluation results, with higher-quality single-channel seismic signals ranked higher; assigning weight coefficients to each single-channel seismic signal based on the ranking results, with higher-quality signals receiving larger weight coefficients; vectorizing the assigned weight coefficients into a corresponding weight coefficient matrix; and modifying the initial loss function based on the weight coefficient matrix to obtain the final loss function; wherein, the final loss function is expressed as:

[0022]

[0023] Among them, W p The weight coefficient matrix is ​​represented as follows:

[0024]

[0025] Among them, w N is the weighting coefficient for the Nth single-channel seismic signal.

[0026] Optionally, the step of processing the acquired seismic signals into a two-dimensional Hessian matrix and constructing constraint terms based on the two-dimensional Hessian matrix includes: establishing a two-dimensional Hessian matrix of the seismic signals based on the longitudinal continuity constraint rules of the seismic gathers; and constructing constraint terms based on the two-dimensional Hessian matrix.

[0027] Establish a horizontal continuity constraint term, expressed as:

[0028]

[0029] Among them, L i,j It is a two-dimensional Hessian matrix.

[0030] Optionally, the step of constructing an objective function based on the final loss function and the constraint terms, and solving for the optimized seismic gather based on the objective function, includes: constructing an objective function based on the final loss function and the constraint terms, wherein the objective function is expressed as:

[0031]

[0032] Wherein, λ is the preset weight of the constraint term; the objective function is solved to obtain the target phase angle; based on the target phase angle and the real domain signal, a function is constructed to obtain the corresponding second real domain signal, and the obtained second real domain signal is used as the optimized seismic gather.

[0033] A second aspect of the present invention provides a phase-constrained seismic gather optimization system, the system comprising: an acquisition unit for acquiring seismic signals, processing the seismic signals into a corresponding frequency domain form, and constructing a symmetrical signal based on the frequency domain form of the seismic signals; a processing unit for obtaining multi-channel seismic signals by combining individual seismic signals in the gather based on the symmetrical signal, and constructing an initial loss function based on the multi-channel seismic signals; a correction unit for performing weight coefficient allocation on each individual seismic signal, constructing a weight coefficient matrix based on the allocation result, and correcting the initial loss function based on the weight coefficient matrix to obtain a final loss function; a construction unit for processing the acquired seismic signals into a two-dimensional Hessian matrix, and constructing constraint terms based on the two-dimensional Hessian matrix; and an output unit for constructing an objective function based on the final loss function and the constraint terms, and solving the objective function to obtain the optimized seismic gather.

[0034] On the other hand, the present invention provides a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the above-described phase-constrained seismic gather optimization method.

[0035] Through the above technical solutions, the present invention proposes a seismic gather optimization method based on phase constraints. This method constructs an objective equation to eliminate noise through phase changes and flattens the gathers through lateral continuity, resulting in more accurate gather optimization results and providing a high-quality gather foundation for reservoir prediction and seismic inversion.

[0036] Other features and advantages of the embodiments of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0037] The accompanying drawings are provided to further illustrate embodiments of the present invention and form part of the specification. They are used together with the following detailed description to explain the embodiments of the present invention, but do not constitute a limitation thereof. In the drawings:

[0038] Figure 1 This is a flowchart of the steps of a phase-constrained seismic gather optimization method provided in one embodiment of the present invention;

[0039] Figure 2 This is a schematic diagram of the effect of seismic synthetic records and phase changes on waveforms provided by one embodiment of the present invention;

[0040] Figure 3 This is a schematic diagram of the symmetrical signal spectrum characteristics provided by one embodiment of the present invention;

[0041] Figure 4This is a comparison chart of the gather flattening effect after phase constraint optimization provided by one embodiment of the present invention;

[0042] Figure 5 This is a schematic diagram of a comparative analysis of denoising based on phase constraint of the advantage gather provided in one embodiment of the present invention;

[0043] Figure 6 This is a comparison chart of the effects of phase constraint optimization on denoising and gather flattening provided by one embodiment of the present invention;

[0044] Figure 7 This is a comparison diagram of the actual pre-stack gather phase constraint before and after optimization according to one embodiment of the present invention;

[0045] Figure 8 This is a system structure diagram of a phase-constrained seismic gather optimization system provided in one embodiment of the present invention. Detailed Implementation

[0046] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0047] In gather optimization, current research primarily focuses on two aspects: random noise reduction and gather flattening. Firstly, regarding random noise reduction, methods mainly include inverse filtering, statistical methods, and regularization-based methods, including classical denoising methods and constructive guided filtering. These methods consider the impact of noise from different research perspectives, but each has its limitations. Secondly, regarding gather flattening, there are two main types of methods: flattening based on velocity adjustment and flattening based on statistical effects. These two techniques are generally used in combination, and there is no unified approach to addressing this issue. Furthermore, the introduction of phase constraints is often avoided in most studies due to the difficulty in optimizing solutions. It is precisely because existing methods cannot incorporate phase constraints for seismic gather processing that some noise remains unremoved, leading to inaccurate gather optimization results.

[0048] To address the issue of low accuracy in gather optimization results in existing schemes, this invention proposes a phase-constrained seismic gather optimization method. This method constructs an objective equation to eliminate noise through phase changes and flattens the gathers through lateral continuity, resulting in more accurate gather optimization results and providing a high-quality gather foundation for reservoir prediction and seismic inversion.

[0049] Figure 1 This is a flowchart of a phase-constrained seismic gather optimization method provided in one embodiment of the present invention. Figure 1As shown, this invention provides a phase-constrained seismic gather optimization method, the method comprising:

[0050] Step S10: Acquire seismic signals, process the seismic signals into the corresponding frequency domain form, and construct a symmetrical signal based on the seismic signals in the frequency domain form.

[0051] Specifically, the processing rule for converting the seismic signal into its corresponding frequency domain form is as follows:

[0052] s = F -1 Ae -jθ

[0053] Where s is the time-domain seismic signal; F -1 θ is the Fourier inverse matrix; A is the amplitude spectrum of the seismic signal; θ is the phase of the seismic signal.

[0054] In this embodiment of the invention, the phase is a complex number. In the optimization algorithm, it is difficult to optimize complex variables for objective functions with constraints, so they must be transformed into real number form. A symmetric signal is constructed based on the fact that the imaginary part of a real symmetric signal is zero.

[0055] Specifically, the symmetrical signal is represented as:

[0056]

[0057] Where s is the seismic signal; s' is the inverted form of s; s * Construct new symmetric signal vectors for both.

[0058] Preferably, after constructing a symmetrical signal based on the seismic signal in the frequency domain form, the method further includes: processing the symmetrical signal into a corresponding frequency domain form; based on the symmetrical signal in the frequency domain form, confirming that the imaginary part of the symmetrical signal is zero, and constructing a corresponding first real-domain signal based on a real-domain signal construction function; wherein, the real-domain signal construction function is:

[0059]

[0060] in, θ is the real part of the Fourier inverse matrix; Acos(θ) is a real vector; θ is the phase of the seismic signal.

[0061] Step S20: Based on the symmetrical signal, obtain a multi-channel seismic signal by combining the single-channel seismic signals in the combined trace set, and construct an initial loss function based on the multi-channel seismic signal.

[0062] Specifically, an objective function is constructed, with phase as the variable. The loss function is the residual between the actual seismic signal and the seismic signal with phase as the variable. Based on the matrix form of seismic gathers, the seismic multi-trace can be transformed into a gather matrix.

[0063] Preferably, based on the real-domain signal, the phase function of each single-channel seismic signal is obtained; the single-channel seismic signals are arranged into a one-dimensional matrix to obtain the corresponding multi-channel seismic signal; wherein, the multi-channel seismic signal is represented as:

[0064]

[0065] in, For multichannel seismic signals; s N (θ) represents the Nth single-channel seismic signal; N is the number of channels in the gather.

[0066] Preferably, the initial loss function is:

[0067]

[0068] in, This is the original earthquake record.

[0069] Step S30: Perform weight coefficient allocation on each single-channel seismic signal, construct a weight coefficient matrix based on the allocation results, and modify the initial loss function based on the weight coefficient matrix to obtain the final loss function.

[0070] Specifically, the gather quality of each single-channel seismic signal is evaluated based on signal quality, and the single-channel seismic signals are ranked according to the evaluation results, with higher-quality single-channel seismic signals ranked higher. Based on the ranking results, weight coefficients are assigned to each single-channel seismic signal, with higher quality signals receiving larger weight coefficients. The assigned weight coefficients are vectorized into corresponding weight coefficient matrices. The initial loss function is then modified based on the weight coefficient matrix to obtain the final loss function. The final loss function is expressed as follows:

[0071]

[0072] Among them, W p The weight coefficient matrix is ​​represented as follows:

[0073]

[0074] Among them, w N is the weighting coefficient for the Nth single-channel seismic signal.

[0075] Step S40: Process the acquired seismic signals into a two-dimensional Hessian matrix, and construct constraint terms based on the two-dimensional Hessian matrix.

[0076] Specifically, based on the longitudinal continuity constraint rules of seismic gathers, a two-dimensional Hessian matrix of the seismic signal is established; based on the two-dimensional Hessian matrix, a lateral continuity constraint term is constructed, expressed as:

[0077]

[0078] Among them, L i,j It is a two-dimensional Hessian matrix.

[0079] In this embodiment of the invention, a horizontal continuity constraint is constructed. Considering that the phase axis of the seismic gather is horizontal, but continuity must also be maintained in the vertical direction, a two-dimensional form of the Hessian matrix is ​​established:

[0080]

[0081] Where H is a two-dimensional Hessian matrix, L xx L xz L zx L zz The second-order difference matrix in different directions is given by the following formula:

[0082]

[0083] Step S50: Construct an objective function based on the final loss function and the constraint terms, and solve the objective function to obtain the optimized seismic gathers.

[0084] Specifically, an objective function is constructed based on the final loss function and the constraint terms, and the objective function is expressed as follows:

[0085]

[0086] Wherein, λ is the preset weight of the constraint term; the objective function is solved to obtain the target phase angle; based on the target phase angle and the real domain signal, a function is constructed to obtain the corresponding second real domain signal, and the obtained second real domain signal is used as the optimized seismic gather.

[0087] Example:

[0088] Construct a corresponding mathematical model to prove the effect of phase change on the signal, such as Figure 2Multiple radiation coefficients were randomly constructed to simulate actual seismic records. The synthesized seismic record used a convolution model, with the seismic wavelet being the Ricker wavelet with a main frequency of 30Hz. The amplitude of the recorded signal was kept constant, while some phases were modified. As shown in the lower part of the figure, the phase changes were not significant, only affecting the phase in the 50-60Hz frequency range. However, the resulting seismic record showed relatively large changes. Figure 2 The diagram on the right shows significant changes in the details of the signal, indicating that phase changes have a significant impact on seismic records. Not only are large peaks and troughs difficult to correspond, but the details of the signal also change considerably.

[0089] Furthermore, such as Figure 2 For the spectral feature analysis of symmetrical signals, signal 1 is an asymmetrical signal, and signal 2 is a symmetrical signal. Both signals have the same initial phase. Signal 1 has both non-zero real and imaginary parts in its spectrum, meaning it has a non-zero phase. Signal 2 has a non-zero real part and a zero imaginary part, meaning it has a zero-phase signal. Symmetrical processing of the signals eliminates the imaginary part of the spectrum, laying the foundation for constructing a real-valued objective function later.

[0090] Furthermore, such as Figure 3 This illustrates the effect of phase optimization in gather flattening. The left image shows the original gathers. Due to inaccurate velocity spectrum extraction, the gathers were not flattened at far offsets. The dashed area represents the superior gathers, which have relatively high quality. According to the method principle, this part has a relatively large weight coefficient. After applying phase constraints, under the control of lateral continuity, the pre-stack seismic gathers are flattened with satisfactory results.

[0091] Furthermore, such as Figure 4 This paper analyzes the effect of gather optimization on noise reduction. The left figure shows the simulated seismic gather; the middle figure shows the left figure with Gaussian noise of 2.5 added, with the noise type tending to be low to mid-frequency. According to the actual situation, the signal-to-noise ratio is relatively high in the low to mid-range migration gathers, while the noise has a greater impact on the near and far migration gathers; the right figure shows the seismic gather after phase optimization based on lateral continuity constraints, where the noise in the near and far migration gathers is well suppressed.

[0092] Furthermore, such as Figure 5 The figures show the effects of phase optimization on gather flattening and denoising. The left figure shows the gather without flattening and without noise; the middle figure shows the gather after adding noise, mainly simulating the processing effect of seismic gather data under the influence of unflattened gathers and noise; the right figure shows the effect of gather optimization based on lateral continuity constraints. It can be clearly seen that both gathers and noise are well recovered, especially the flattening and denoising effect of far-migrated gathers is quite ideal.

[0093] Furthermore, such as Figure 6The figures show the effects of phase optimization on gather flattening and denoising. The left figure shows the gather without flattening and without noise; the middle figure shows the gather after adding noise, mainly simulating the processing effect of seismic gather data under the influence of unflattened gathers and noise; the right figure shows the effect of gather optimization based on lateral continuity constraints. It can be clearly seen that both gathers and noise are well recovered, especially the flattening and denoising effect of far-migrated gathers is quite ideal.

[0094] Furthermore, such as Figure 7 To optimize the phase of actual seismic gather data, the left image shows the original gather, which has poor overall quality, low signal-to-noise ratio at long offsets, and issues such as phase axis misalignment and energy imbalance, significantly impacting subsequent reservoir prediction gather analysis. The right image shows the gather after phase optimization, where the overall profile is improved to some extent, especially in the area enclosed by the black dashed box, where the lateral continuity of the phase axis is well restored, while largely preserving the compositional information of the original gather and avoiding compromise on its fidelity.

[0095] Figure 8 This is a system structure diagram of a phase-constrained seismic gather optimization system provided in one embodiment of the present invention. Figure 8 As shown, an embodiment of the present invention provides a phase-constrained seismic gather optimization system, the system comprising:

[0096] The acquisition unit is used to acquire seismic signals, process the seismic signals into a corresponding frequency domain form, and construct a symmetrical signal based on the seismic signals in the frequency domain form.

[0097] Specifically, the processing rule for converting the seismic signal into its corresponding frequency domain form is as follows:

[0098] s = F -1 Ae -jθ

[0099] Where s is the time-domain seismic signal; F -1 θ is the Fourier inverse matrix; A is the amplitude spectrum of the seismic signal; θ is the phase of the seismic signal.

[0100] In this embodiment of the invention, the phase is a complex number. In the optimization algorithm, it is difficult to optimize complex variables for objective functions with constraints, so they must be transformed into real number form. A symmetric signal is constructed based on the fact that the imaginary part of a real symmetric signal is zero.

[0101] Specifically, the symmetrical signal is represented as:

[0102]

[0103] Where s is the seismic signal; s' is the inverted form of s; s *Construct new symmetric signal vectors for both.

[0104] Preferably, after constructing a symmetrical signal based on the seismic signal in the frequency domain form, the method further includes: processing the symmetrical signal into a corresponding frequency domain form; based on the symmetrical signal in the frequency domain form, confirming that the imaginary part of the symmetrical signal is zero, and constructing a corresponding first real-domain signal based on a real-domain signal construction function; wherein, the real-domain signal construction function is:

[0105]

[0106] in, θ is the real part of the Fourier inverse matrix; Acos(θ) is a real vector; θ is the phase of the seismic signal.

[0107] The processing unit is used to obtain multi-channel seismic signals based on the symmetrical signal by combining the single-channel seismic signals in the combined trace set, and to construct an initial loss function based on the multi-channel seismic signals.

[0108] Specifically, an objective function is constructed, with phase as the variable. The loss function is the residual between the actual seismic signal and the seismic signal with phase as the variable. Based on the matrix form of seismic gathers, the seismic multi-trace can be transformed into a gather matrix.

[0109] Preferably, based on the real-domain signal, the phase function of each single-channel seismic signal is obtained; the single-channel seismic signals are arranged into a one-dimensional matrix to obtain the corresponding multi-channel seismic signal; wherein, the multi-channel seismic signal is represented as:

[0110]

[0111] in, For multichannel seismic signals; s N (θ) represents the Nth single-channel seismic signal; N is the number of channels in the gather.

[0112] Preferably, the initial loss function is:

[0113]

[0114] in, This is the original earthquake record.

[0115] The correction unit is used to perform weight coefficient allocation on each single-channel seismic signal, construct a weight coefficient matrix based on the allocation results, and correct the initial loss function based on the weight coefficient matrix to obtain the final loss function.

[0116] Specifically, the gather quality of each single-channel seismic signal is evaluated based on signal quality, and the single-channel seismic signals are ranked according to the evaluation results, with higher-quality single-channel seismic signals ranked higher. Based on the ranking results, weight coefficients are assigned to each single-channel seismic signal, with higher quality signals receiving larger weight coefficients. The assigned weight coefficients are vectorized into corresponding weight coefficient matrices. The initial loss function is then modified based on the weight coefficient matrix to obtain the final loss function. The final loss function is expressed as follows:

[0117]

[0118] Among them, W p The weight coefficient matrix is ​​represented as follows:

[0119]

[0120] Among them, w N is the weighting coefficient for the Nth single-channel seismic signal.

[0121] The construction unit is used to process the acquired seismic signals into a two-dimensional Hessian matrix and construct constraint terms based on the two-dimensional Hessian matrix.

[0122] Specifically, based on the longitudinal continuity constraint rules of seismic gathers, a two-dimensional Hessian matrix of the seismic signal is established; based on the two-dimensional Hessian matrix, a lateral continuity constraint term is constructed, expressed as:

[0123]

[0124] Among them, L i,j It is a two-dimensional Hessian matrix.

[0125] In this embodiment of the invention, a horizontal continuity constraint is constructed. Considering that the phase axis of the seismic gather is horizontal, but continuity must also be maintained in the vertical direction, a two-dimensional form of the Hessian matrix is ​​established:

[0126]

[0127] Where H is a two-dimensional Hessian matrix, L xx L xz L zx L zz The second-order difference matrix in different directions is given by the following formula:

[0128]

[0129] The output unit is used to construct an objective function based on the final loss function and the constraint terms, and to obtain the optimized seismic gathers by solving the objective function.

[0130] Specifically, an objective function is constructed based on the final loss function and the constraint terms, and the objective function is expressed as follows:

[0131]

[0132] Wherein, λ is the preset weight of the constraint term; the objective function is solved to obtain the target phase angle; based on the target phase angle and the real domain signal, a function is constructed to obtain the corresponding second real domain signal, and the obtained second real domain signal is used as the optimized seismic gather.

[0133] The present invention also provides a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the above-described phase-constrained seismic gather optimization method.

[0134] Those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware. This program is stored in a storage medium and includes several instructions to cause a microcontroller, chip, or processor to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0135] The optional embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the embodiments of the present invention are not limited to the specific details described above. Within the scope of the technical concept of the embodiments of the present invention, various simple modifications can be made to the technical solutions of the embodiments of the present invention, and these simple modifications all fall within the protection scope of the embodiments of the present invention. It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. To avoid unnecessary repetition, the embodiments of the present invention will not further describe the various possible combinations.

[0136] Furthermore, various different embodiments of the present invention can be combined in any way, as long as they do not violate the spirit of the embodiments of the present invention, they should also be regarded as the content disclosed by the embodiments of the present invention.

Claims

1. A method for phase constraint based seismic gather optimization, the method comprising: The method includes: Seismic signals are acquired, processed into their corresponding frequency domain form, and a symmetrical signal is constructed based on this frequency domain form; wherein, The symmetrical signal is represented as: in, This is an earthquake signal; for The inversion; Construct new symmetric signal vectors for both; After constructing a symmetrical signal based on the seismic signal in its frequency domain form, the symmetrical signal is processed into its corresponding frequency domain form. Based on the frequency domain form of the symmetrical signal, the imaginary part of the symmetrical signal is set to zero, and a corresponding first real-domain signal is constructed based on the real-domain signal construction function. The real-domain signal construction function is as follows: in, is the real part of the Fourier inverse matrix; It is a real number vector; The phase of the seismic signal; Based on the symmetrical signal, a multi-channel seismic signal is obtained by combining the single-channel seismic signals in the combined trace set, and an initial loss function is constructed based on the multi-channel seismic signal. Weighting coefficients are assigned to each single-channel seismic signal, a weighting coefficient matrix is ​​constructed based on the assignment results, and the initial loss function is corrected based on the weighting coefficient matrix to obtain the final loss function. The acquired seismic signals are processed into a two-dimensional Hessian matrix, and constraint terms are constructed based on the two-dimensional Hessian matrix. An objective function is constructed based on the final loss function and the constraint terms, and the optimized seismic gathers are obtained by solving the objective function.

2. The method according to claim 1, characterized in that, The processing rule for converting the seismic signal into its corresponding frequency domain form is as follows: in, This is a time-domain seismic signal; It is the Fourier inverse matrix; The amplitude spectrum of the seismic signal; This represents the phase of the seismic signal.

3. The method according to claim 1, characterized in that, The process of obtaining multi-channel seismic signals based on the symmetrical signal by combining individual seismic signals from the combined trace set includes: Based on the first real-domain signal, the phase function of each single-channel seismic signal is obtained; The individual seismic signals are arranged into a one-dimensional matrix to obtain the corresponding multi-channel seismic signals; where... The multichannel seismic signal is represented as follows: in, This is a multi-channel seismic signal; This is the Nth single-channel seismic signal; N is the number of the Tao set.

4. The method according to claim 3, characterized in that, The initial loss function is: in, This is the original earthquake record.

5. The method according to claim 4, characterized in that, The process of assigning weight coefficients to each single-channel seismic signal, constructing a weight coefficient matrix based on the assignment results, and modifying the initial loss function based on the weight coefficient matrix to obtain the final loss function includes: The gather quality of each single-channel seismic signal is evaluated based on signal quality, and the single-channel seismic signals are ranked based on the evaluation results, with the single-channel seismic signals of higher quality being ranked higher. Weighting coefficients are assigned to each single-channel seismic signal based on the sorting results; the higher the quality, the larger the corresponding weighting coefficient. The assigned weight coefficients are vectorized into the corresponding weight coefficient matrix; The initial loss function is modified based on the weight coefficient matrix to obtain the final loss function; wherein the final loss function is expressed as: in, The weight coefficient matrix is ​​represented as follows: in, is the weighting coefficient for the Nth single-channel seismic signal.

6. The method according to claim 1, characterized in that, The process of processing the acquired seismic signals into a two-dimensional Hessian matrix and constructing constraint terms based on the two-dimensional Hessian matrix includes: Based on the longitudinal continuity constraint rule of seismic gathers, a two-dimensional Hessian matrix of seismic signals is established. The lateral continuity constraint term is constructed based on the two-dimensional Hessian matrix and is expressed as follows: in, It is a two-dimensional Hessian matrix; This is a multi-channel seismic signal; The horizontal Hessian component; This represents the Hessian component in the longitudinal direction.

7. The method according to claim 5, characterized in that, The step of constructing an objective function based on the final loss function and the constraint terms, and obtaining the optimized seismic gather by solving the objective function, includes: Based on the final loss function and the constraint terms, an objective function is constructed, which is expressed as follows: in, Preset weights for constraint terms; This is the weight coefficient matrix; Original earthquake trace collection; These are second-order difference matrices in different directions; The objective function is solved to obtain the target phase angle; Based on the target phase angle and the first real domain signal, a function is constructed to obtain the corresponding second real domain signal, and the obtained second real domain signal is used as the optimized seismic gather.

8. A phase-constrained seismic gather optimization system, characterized in that, The system includes: The acquisition unit is used to acquire seismic signals, process the seismic signals into a corresponding frequency domain form, and construct a symmetrical signal based on the seismic signals in the frequency domain form; wherein, The symmetrical signal is represented as: in, This is an earthquake signal; for The inversion; Construct new symmetric signal vectors for both; After constructing a symmetrical signal based on the seismic signal in its frequency domain form, the symmetrical signal is processed into its corresponding frequency domain form. Based on the frequency domain form of the symmetrical signal, the imaginary part of the symmetrical signal is set to zero, and a corresponding first real-domain signal is constructed based on the real-domain signal construction function. The real-domain signal construction function is as follows: in, is the real part of the Fourier inverse matrix; It is a real number vector; The phase of the seismic signal; The processing unit is used to obtain multi-channel seismic signals based on the symmetrical signal by combining the single-channel seismic signals in the combined trace set, and to construct an initial loss function based on the multi-channel seismic signals. The correction unit is used to perform weight coefficient allocation on each single-channel seismic signal, construct a weight coefficient matrix based on the allocation result, and correct the initial loss function based on the weight coefficient matrix to obtain the final loss function. A construction unit is used to process the acquired seismic signals into a two-dimensional Hessian matrix and construct constraint terms based on the two-dimensional Hessian matrix. The output unit is used to construct an objective function based on the final loss function and the constraint terms, and to obtain the optimized seismic gathers by solving the objective function.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed on a computer, cause the computer to perform the phase-constrained seismic gather optimization method as described in any one of claims 1-7.

Images