Multiple wave migration imaging method and device based on iterative deconvolution imaging condition

Abstract

The application provides a multiple wave migration imaging method and device based on an iterative deconvolution imaging condition, relates to the fields of seismic data imaging and migration in oil geophysical exploration, and comprises the following steps: obtaining a seismic wave forward wave field and a seismic wave reverse wave field; performing multiple wave imaging on the seismic wave forward wave field and the seismic wave reverse wave field by using a deconvolution imaging condition to obtain an initial imaging result; taking the seismic wave forward wave field, the seismic wave reverse wave field and the initial imaging result as inputs, and performing multiple wave imaging by using an iterative deconvolution imaging method to obtain an iterative deconvolution multiple wave imaging result; determining a deconvolution imaging target function value in the multiple wave imaging process; if the target function value does not satisfy a preset condition, performing iteration on the imaging result until the deconvolution imaging target function value satisfies the preset condition; and generating a final iterative deconvolution multiple wave imaging result according to the iterated imaging result.

Description

Technical Field

[0001] This invention relates to the field of seismic data imaging and migration technology for petroleum geophysical exploration, and particularly to a multiple-wave migration imaging method and apparatus based on iterative deconvolution imaging conditions. Background Technology

[0002] This section is intended to provide background or context for the embodiments of the invention set forth in the claims. The description herein is not an admission that it is prior art simply because it is included in this section.

[0003] In traditional marine exploration seismic processing, free surface multiples are generally removed as interference. However, the information contained in these multiples regarding subsurface medium parameters has not been fully utilized or explored, which remains a challenge and bottleneck in current seismic processing and imaging. Therefore, free surface multiple imaging can fully utilize free surface multiple information for shallow and intermediate layer seismic migration of subsurface media, enabling high-precision imaging of the seabed and its vicinity, and solving the problem of insufficient shallow imaging range in traditional imaging methods.

[0004] Berkhout and Verschuur (1994) proposed free-surface multiple-wave migration based on up- and down-wave frames. Subsequently, Schuster and Rickett (2000) converted multiple waves into single waves using the principle of interference and migrated them according to the traditional imaging framework. Shan (2003) improved this quasi-single-wave imaging theory and applied it to actual production. Lu et al. (2021) systematically studied and improved this type of method and applied it to industrial processing. Multiple-wave imaging can be realized within the framework of single-pass wave equations and wave equations. Traditional multiple-wave inversion methods suffer from interference due to the presence of multiple wave information of different orders, which reduces the imaging quality. This is a significant problem hindering its industrial application.

[0005] Currently, methods for suppressing crosstalk during multiple wave imaging can be categorized as follows: The first method uses deconvolution imaging conditions to suppress crosstalk. This method is relatively simple to implement, but it can only serve as an approximate method to eliminate crosstalk, suppressing or eliminating only a large portion of it. The second method images multiple waves of different orders during imaging to avoid crosstalk caused by different orders. However, this method cannot avoid crosstalk caused by multiple wave signals of the same order and requires additional separation of multiple wave signals of different orders from the seismic data. The third method is multiple wave imaging based on migration algorithms. The core of this type of method is to estimate the phase axis of the crosstalk using migration algorithms and then eliminate it. This type of method requires adaptive subtraction processing and separation of primary and multiple waves. The fourth method is the least squares multiple wave imaging method. This type of method can perfectly solve the imaging crosstalk problem and can be implemented using one-way waves and wave equations. However, this method increases the computational load by several orders of magnitude and is significantly affected by noise in the data.

[0006] Currently, industrial applications of multiple wave imaging mainly employ multiple wave migration methods under deconvolution imaging conditions, resulting in low image clarity and poor imaging quality. Therefore, there is an urgent need for a technical solution that can overcome these shortcomings and improve imaging performance. Summary of the Invention

[0007] To address the problems existing in the prior art, this invention proposes a multiple wave migration imaging method and apparatus based on iterative deconvolution imaging conditions. Unlike traditional multiple wave imaging based on deconvolution imaging conditions, this invention introduces regularization terms in frequency and spatial methods, achieving a wider frequency range and clearer imaging results in the multiple wave imaging results.

[0008] In a first aspect of the present invention, a multiple-wave migration imaging method based on iterative deconvolution imaging conditions is proposed, comprising:

[0009] Obtain the forward propagation wavefield and the reverse propagation wavefield of seismic waves;

[0010] Multiple wave imaging was performed on the forward propagation wavefield and the backward propagation wavefield of the seismic wave using deconvolution imaging conditions to obtain the initial imaging results.

[0011] Using the forward propagation wavefield, the backward propagation wavefield, and the initial imaging results as input, multiple wave imaging is performed using the iterative deconvolution imaging method to obtain iterative deconvolution multiple wave imaging results.

[0012] During multiple-wave imaging, the objective function value of deconvolution imaging is determined;

[0013] If the target function value does not meet the preset condition, the imaging result is iterated until the deconvolution imaging target function value meets the preset condition. Based on the iterated imaging result, the final iterative deconvolution multiple imaging result is generated.

[0014] In the multiple wave migration imaging method based on iterative deconvolution imaging conditions in this embodiment of the invention, obtaining the forward propagation wavefield of seismic waves includes:

[0015] Acquire input data; during forward propagation, the input data consists of seismic full-wavefield shot record data containing information on direct waves, primary reflected waves, and free-surface multiples.

[0016] Based on the input data, the forward propagation of the wave field is performed using the one-way wave equation algorithm to obtain the forward propagation wave field of the seismic wave.

[0017] In the multiple wave migration imaging method based on iterative deconvolution imaging conditions in this embodiment of the invention, obtaining the backpropagating wavefield of seismic waves includes:

[0018] Acquire input data; during backpropagation, the input data is multiple wave information or seismic full-wavefield shot record;

[0019] Based on the input data, the wave field is propagated in reverse using the one-way wave equation algorithm to obtain the back-propagated seismic wave field.

[0020] In the multiple-wave migration imaging method based on iterative deconvolution imaging conditions in this embodiment of the invention, determining the deconvolution imaging target function value during the multiple-wave imaging process includes:

[0021] The objective function for deconvolution imaging is expressed as follows:

[0022]

[0023] Where E(R) is the objective function value;

[0024] U represents the back propagation wave field of the seismic wave;

[0025] D represents the forward propagation wavefield of the seismic wave;

[0026] R represents the imaging result;

[0027] This indicates taking the spatial derivative of the imaging result;

[0028] a and β are dimensionless parameters;

[0029] ω is the angular frequency;

[0030] This indicates that the frequency derivative of the imaging result is obtained.

[0031] In the multiple wave migration imaging method based on iterative deconvolution imaging conditions in this embodiment of the invention, if the target function value does not meet the preset conditions, the imaging results are iterated until the deconvolution imaging target function value meets the preset conditions. Based on the iterated imaging results, the final iterative deconvolution multiple wave migration imaging result is generated, including:

[0032] The formula for the iterative deconvolution imaging condition is:

[0033]

[0034] Among them, R n+1 This is the imaging result after the (n+1)th iteration;

[0035] R n This is the imaging result after the nth iteration;

[0036] i, j, k, l are the spatial and frequency coordinates (x, y, z, ω) of the imaging result;

[0037] It is the complex conjugate of the forward propagation wavefield of the seismic wave.

[0038] In the multiple wave migration imaging method based on iterative deconvolution imaging conditions in this embodiment of the invention, if the target function value does not meet the preset conditions, the imaging results are iterated until the deconvolution imaging target function value meets the preset conditions. Based on the iterated imaging results, the final iterative deconvolution multiple wave migration imaging result is generated, including:

[0039] Based on the iterative imaging results R n+1 The objective function value is then recalculated; wherein the objective function value gradually approaches 0 during the calculation.

[0040] When the objective function value of the deconvolution imaging satisfies the preset condition, the final iterative deconvolution multiple imaging result is generated based on the iterative imaging result.

[0041] In a second aspect of the present invention, a multi-wave migration imaging device based on iterative deconvolution imaging conditions is proposed, comprising:

[0042] The data acquisition module is used to acquire the forward propagation wavefield and the reverse propagation wavefield of seismic waves;

[0043] The multiple wave imaging processing module is used to perform multiple wave imaging on the forward propagation wavefield and the backward propagation wavefield of the seismic wave using deconvolution imaging conditions to obtain the initial imaging results.

[0044] Using the forward propagation wavefield, the backward propagation wavefield, and the initial imaging results as input, multiple wave imaging is performed using the iterative deconvolution imaging method to obtain iterative deconvolution multiple wave imaging results.

[0045] During multiple-wave imaging, the objective function value of deconvolution imaging is determined;

[0046] If the target function value does not meet the preset condition, the imaging result is iterated until the deconvolution imaging target function value meets the preset condition. Based on the iterated imaging result, the final iterative deconvolution multiple imaging result is generated.

[0047] In the multi-wave migration imaging device based on iterative deconvolution imaging conditions in this embodiment of the invention, the data acquisition module is specifically used for:

[0048] Acquire input data; during forward propagation, the input data consists of seismic full-wavefield shot record data containing information on direct waves, primary reflected waves, and free-surface multiples.

[0049] Based on the input data, the forward propagation of the wave field is performed using the one-way wave equation algorithm to obtain the forward propagation wave field of the seismic wave.

[0050] In the multi-wave migration imaging device based on iterative deconvolution imaging conditions in this embodiment of the invention, the data acquisition module is specifically used for:

[0051] Acquire input data; during backpropagation, the input data is multiple wave information or seismic full-wavefield shot record;

[0052] Based on the input data, the wave field is propagated in reverse using the one-way wave equation algorithm to obtain the back-propagated seismic wave field.

[0053] In the multiple-wave migration imaging device based on iterative deconvolution imaging conditions in this embodiment of the invention, the multiple-wave imaging processing module determines the deconvolution imaging target function value during the multiple-wave imaging process, including:

[0054] The objective function for deconvolution imaging is expressed as follows:

[0055]

[0056] Where E(R) is the objective function value;

[0057] U represents the back propagation wave field of the seismic wave;

[0058] D represents the forward propagation wavefield of the seismic wave;

[0059] R represents the imaging result;

[0060] This indicates taking the spatial derivative of the imaging result;

[0061] a and β are dimensionless parameters;

[0062] ω is the angular frequency;

[0063] This indicates that the frequency derivative of the imaging result is obtained.

[0064] In the multiple wave migration imaging device based on iterative deconvolution imaging conditions in this embodiment of the invention, if the target function value does not meet the preset conditions, the multiple wave imaging processing module iterates the imaging results until the deconvolution imaging target function value meets the preset conditions, and generates the final iterative deconvolution multiple wave imaging result based on the iterated imaging results, including:

[0065] The formula for the iterative deconvolution imaging condition is:

[0066]

[0067] Among them, R n+1 This is the imaging result after the (n+1)th iteration;

[0068] R n This is the imaging result after the nth iteration;

[0069] i, j, k, l are the spatial and frequency coordinates (x, y, z, ω) of the imaging result;

[0070] It is the complex conjugate of the forward propagation wavefield of the seismic wave.

[0071] In the multiple wave migration imaging device based on iterative deconvolution imaging conditions in this embodiment of the invention, the multiple wave imaging processing module is specifically used for:

[0072] Based on the iterative imaging results R n+1 The objective function value is then recalculated; wherein the objective function value gradually approaches 0 during the calculation.

[0073] When the objective function value of the deconvolution imaging satisfies the preset condition, the final iterative deconvolution multiple imaging result is generated based on the iterative imaging result.

[0074] In a third aspect of the present invention, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement a multiple wave migration imaging method based on iterative deconvolution imaging conditions.

[0075] In a fourth aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing a computer program that, when executed by a processor, implements a multiple wave migration imaging method based on iterative deconvolution imaging conditions.

[0076] In a fifth aspect of the present invention, a computer program product is provided, the computer program product comprising a computer program that, when executed by a processor, implements a multiple wave migration imaging method based on iterative deconvolution imaging conditions.

[0077] The multi-wave migration imaging method and apparatus based on iterative deconvolution imaging conditions proposed in this invention offer greater flexibility and controllability during implementation. The iterative deconvolution imaging conditions constrain both the spatial and frequency directions of the imaging process. As an extension of conventional deconvolution imaging methods, the iterative deconvolution imaging conditions have a more complete physical basis. Furthermore, these conditions allow for a wider frequency spread in the imaging results, achieving better imaging resolution and providing strong technical support for oil exploration. Attached Figure Description

[0078] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0079] Figure 1 This is a schematic flowchart of a multi-wave migration imaging method based on iterative deconvolution imaging conditions according to an embodiment of the present invention.

[0080] Figure 2 This is a schematic diagram of the iterative deconvolution conditional multiple-wave imaging process according to a specific embodiment of the present invention.

[0081] Figure 3A This is a schematic diagram of the full-wavefield seismic record of a single-layer model according to a specific embodiment of the present invention.

[0082] Figure 3B This is a schematic diagram of multiple wave recording according to a specific embodiment of the present invention.

[0083] Figure 4A This is a schematic diagram of the cross-correlation imaging conditional multiple migration results according to a specific embodiment of the present invention.

[0084] Figure 4B yes Figure 4A A magnified view of a portion of the image.

[0085] Figure 4CThis is a schematic diagram of the multi-wave migration result under conventional deconvolution imaging conditions according to a specific embodiment of the present invention.

[0086] Figure 4D yes Figure 4C A magnified view of a portion of the image.

[0087] Figure 4E This is a schematic diagram of the conditional multiple migration results of iterative deconvolution imaging according to a specific embodiment of the present invention.

[0088] Figure 4F yes Figure 4E A magnified view of a portion of the image.

[0089] Figure 5 This is a schematic diagram showing the spectral comparison results of cross-correlation, conventional deconvolution, and iterative deconvolution conditions according to a specific embodiment of the present invention.

[0090] Figure 6 This is a schematic diagram of VSP acquisition and observation using the Marmousi model according to a specific embodiment of the present invention.

[0091] Figure 7A This is a schematic diagram of a seismic record at a receiving point depth of 200m according to a specific embodiment of the present invention.

[0092] Figure 7B This is a schematic diagram of a seismic record at a receiving point depth of 1700m according to a specific embodiment of the present invention.

[0093] Figure 7C This is a schematic diagram of a seismic record at a receiving point depth of 3200m according to a specific embodiment of the present invention.

[0094] Figure 8A This is a schematic diagram of the conventional deconvolution offset result of a specific embodiment of the present invention.

[0095] Figure 8B This is a schematic diagram of the iterative deconvolution offset result of a specific embodiment of the present invention.

[0096] Figure 9 This is a schematic diagram of the architecture of a multi-wave migration imaging device based on iterative deconvolution imaging conditions according to an embodiment of the present invention.

[0097] Figure 10 This is a schematic diagram of a computer device structure according to an embodiment of the present invention. Detailed Implementation

[0098] The principles and spirit of the invention will now be described with reference to several exemplary embodiments. It should be understood that these embodiments are given merely to enable those skilled in the art to better understand and implement the invention, and are not intended to limit the scope of the invention in any way. Rather, these embodiments are provided to make this disclosure more thorough and complete, and to fully convey the scope of this disclosure to those skilled in the art.

[0099] Those skilled in the art will recognize that embodiments of the present invention can be implemented as a system, apparatus, device, method, or computer program product. Therefore, this disclosure can be specifically implemented in the following forms: entirely hardware, entirely software (including firmware, resident software, microcode, etc.), or a combination of hardware and software.

[0100] According to embodiments of the present invention, a method and apparatus for multiple-wave migration imaging based on iterative deconvolution imaging conditions are proposed, relating to the field of seismic data imaging and migration technology in petroleum geophysical exploration. The present invention proposes an objective function for regularization constraints with spatial and frequency domain constraints, and provides an iterative solution method. When performing multiple-wave migration, this method can maximize the frequency band range of the migration imaging and improve imaging quality.

[0101] The principles and spirit of the present invention will be explained in detail below with reference to several representative embodiments.

[0102] Figure 1 This is a schematic flowchart of a multi-wave migration imaging method based on iterative deconvolution imaging conditions according to an embodiment of the present invention. Figure 1 As shown, the method includes:

[0103] Step 101: Obtain the forward propagation wavefield and the reverse propagation wavefield of the seismic wave;

[0104] Step 102: Perform multiple wave imaging on the forward propagation wavefield and the backward propagation wavefield of the seismic wave using deconvolution imaging conditions to obtain the initial imaging results.

[0105] Step 103: Using the forward propagation wavefield, the backward propagation wavefield, and the initial imaging results as input, perform multiple wave imaging using the iterative deconvolution imaging method to obtain the iterative deconvolution multiple wave imaging results.

[0106] Step 104: During the multiple-wave imaging process, determine the target function value for deconvolution imaging;

[0107] Step 105: If the target function value does not meet the preset condition, the imaging result is iterated until the deconvolution imaging target function value meets the preset condition. Based on the iterated imaging result, the final iterative deconvolution multiple imaging result is generated.

[0108] In practical applications, the working principle of the multiple-wave migration imaging method based on iterative deconvolution imaging conditions is as follows: First, acquire the forward propagation wavefield and the backward propagation wavefield of the seismic wave. Second, perform multiple-wave imaging on the forward and backward propagation wavefields of the seismic wave using deconvolution imaging conditions to obtain initial imaging results. Third, use the forward and backward propagation wavefields of the seismic wave and the initial imaging results as input, and perform multiple-wave imaging using the iterative deconvolution imaging method to obtain iterative deconvolution multiple-wave imaging results. Fourth, determine the deconvolution imaging objective function value during the multiple-wave imaging process. Fifth, if the objective function value does not meet the preset conditions, iterate the imaging results until the deconvolution imaging objective function value meets the preset conditions. Finally, generate the final iterative deconvolution multiple-wave imaging result based on the iterative imaging results. This invention proposes an objective function with regularization constraints in both spatial and frequency domains and provides an iterative solution method. This allows for maximizing the frequency band range of the migration imaging and improving imaging quality during multiple-wave migration.

[0109] To provide a clearer explanation of the multi-wave migration imaging method based on iterative deconvolution imaging conditions, each step will be described in detail below.

[0110] In one embodiment, step 101, obtaining the forward propagation wavefield of the seismic wave, includes:

[0111] Acquire input data; during forward propagation, the input data consists of seismic full-wavefield shot record data containing information on direct waves, primary reflected waves, and free-surface multiples.

[0112] Based on the input data, the forward propagation of the wave field is performed using the one-way wave equation algorithm to obtain the forward propagation wave field of the seismic wave.

[0113] The forward propagation wavelength of a seismic wave can be represented by D.

[0114] In one embodiment, step 101, obtaining the backpropagation wavefield of the seismic wave, includes:

[0115] Acquire input data; during backpropagation, the input data is multiple wave information or seismic full-wavefield shot record;

[0116] Based on the input data, the wave field is propagated in reverse using the one-way wave equation algorithm to obtain the back-propagated seismic wave field.

[0117] The wavelength of a seismic wave propagating backward can be represented by U.

[0118] In one embodiment, step 102 involves performing multiple wave imaging on the forward propagation wavefield and the backward propagation wavefield of the seismic wave using deconvolution imaging conditions to obtain an initial imaging result R. 0 ;

[0119] In one embodiment, step 103 involves combining the forward propagation wavefield, the backward propagation wavefield, and the initial imaging result R. 0 As input, multiple wave imaging is performed using the iterative deconvolution imaging method to obtain iterative deconvolution multiple wave imaging results.

[0120] In one embodiment, step 104, during multiple wave imaging, determines the deconvolution imaging target function value, including:

[0121] The objective function for deconvolution imaging is expressed as follows:

[0122]

[0123] Where E(R) is the objective function value;

[0124] U represents the back propagation wave field of the seismic wave;

[0125] D represents the forward propagation wavefield of the seismic wave;

[0126] R represents the imaging result;

[0127] This indicates taking the spatial derivative of the imaging result;

[0128] a and β are dimensionless parameters;

[0129] ω is the angular frequency;

[0130] This indicates that the frequency derivative of the imaging result is obtained.

[0131] In one embodiment, step 105 involves iterating the imaging results if the target function value does not meet a preset condition, until the deconvolution imaging target function value meets the preset condition. Based on the iterated imaging results, a final iterative deconvolution multiple imaging result is generated, including:

[0132] The formula for the iterative deconvolution imaging condition is:

[0133]

[0134] Among them, R n+1 This is the imaging result after the (n+1)th iteration;

[0135] R n This is the imaging result after the nth iteration;

[0136] i, j, k, l are the spatial and frequency coordinates (x, y, z, ω) of the imaging result; i, j, k correspond to the spatial coordinates x, y, z, and l corresponds to the frequency ω.

[0137] It is the complex conjugate of the forward propagation wavefield of the seismic wave.

[0138] Based on the iterative imaging results R n+1 The objective function value is then recalculated; wherein the objective function value gradually approaches 0 during the calculation.

[0139] When the objective function value of the deconvolution imaging satisfies the preset condition, the final iterative deconvolution multiple imaging result is generated based on the iterative imaging result.

[0140] To provide a clearer explanation of the above-mentioned multi-wave migration imaging method based on iterative deconvolution imaging conditions, a specific embodiment will be used for detailed explanation below.

[0141] In the context of existing technologies, the objective function E(R) to be solved for multiple-wave migration under traditional deconvolution imaging conditions is:

[0142]

[0143] Traditional deconvolution imaging conditions for multiple-wave imaging involve solving equation (1) to derive the following specific imaging formula:

[0144]

[0145] in, For imaging results;

[0146] Existing industrial applications of multiple wave imaging mainly employ multiple wave migration methods under deconvolution imaging conditions. This invention differs from traditional multiple wave imaging under deconvolution imaging conditions by introducing regularization terms in frequency and spatial methods, achieving a wider frequency range and clearer imaging results. Specifically, compared to the objective function of traditional deconvolution imaging conditions, this invention proposes a new deconvolution imaging objective function:

[0147]

[0148] Formula (3) cannot separate the imaging results using the traditional gradient calculation method. Therefore, the optical flow method is needed to solve the objective function. The calculation method is as follows:

[0149]

[0150] Formula (4) is the formula for the iterative deconvolution imaging condition. By using iteratively solving the imaging results, iterative deconvolution multiple imaging can be realized.

[0151] The multi-wave migration imaging method based on iterative deconvolution imaging conditions proposed in this invention has at least the following advantages compared to existing technologies:

[0152] 1. Iterative deconvolution imaging conditions are constrained in both the spatial and frequency directions of imaging, resulting in greater flexibility in imaging control.

[0153] 2. Iterative deconvolution imaging conditions are an extension of conventional deconvolution imaging methods, with a more complete physical basis.

[0154] 3. Iterative deconvolution imaging conditions can broaden the frequency range of the imaging results and achieve better imaging resolution.

[0155] Considering a real-world scenario, refer to Figure 2 This is a schematic diagram of the iterative deconvolution conditional multiple-wave imaging process according to a specific embodiment of the present invention. Figure 2 As shown, firstly, the seismic shot records are input; the input data for forward propagation is seismic full-wavefield shot record data containing information on direct waves, primary reflections, and free surface multiples; the input data for reverse propagation can be either multiples information only or seismic full-wavefield shot records.

[0156] Subsequently, using the input shot records, the wavefield was propagated in both the forward and reverse directions using a one-way wave equation algorithm, yielding the forward propagation wavefield D and the reverse propagation wavefield U. Multiple wave imaging was then performed on the forward and reverse propagation wavefields using conventional deconvolution imaging conditions, and the imaging result R was calculated. 0 .

[0157] Then the wavefields U and D and the initial imaging result R are used. 0 Using the iterative deconvolution imaging formula as input, multiple wave imaging is performed. After n iterations, the iterative deconvolution multiple wave imaging result R can be obtained. n After n+1 iterations, the iterative deconvolution multiple imaging result R can be obtained. n+1 .

[0158] To verify the effectiveness of this method, full-wavelength seismic records from a single-layer model were used. Figure 3A ) and multiple wave records ( Figure 3B Using this as input, multiple wave imaging under cross-correlation imaging conditions, conventional deconvolution imaging conditions, and iterative deconvolution imaging conditions was calculated. The calculation results are as follows: Figures 4A to 4F As shown, where, Figure 4A , 4C The horizontal axis range for both 4E and 4E is 0-135, and the vertical axis range is 0-123; the corresponding magnified view ( Figure 4B , Figure 4D , Figure 4F The horizontal axis ranges from 56 to 77, and the vertical axis ranges from 0 to 100.

[0159] The spectra of the three results were further compared, such as Figure 5As shown in the figure, the iterative deconvolution imaging result exhibits the widest spectrum and highest resolution, demonstrating the effectiveness of the method. To further verify the stability of the method, the Marmousi model was used for VSP seismic acquisition, as shown... Figure 6 As shown. Due to the relative complexity of the model, relatively complex common-detector point gathers are received at different depths, such as... Figures 7A to 7C As shown.

[0160] Finally, conventional deconvolution imaging and iterative deconvolution imaging were used to achieve multiple wave migration, and the results are as follows: Figure 8A and Figure 8B As shown in the figure, the resolution and lateral continuity of the iterative deconvolution imaging results are significantly improved, demonstrating the advantages and effectiveness of the method proposed in this application.

[0161] It should be noted that although the operation of the method of the present invention has been described in a specific order in the above embodiments and figures, this does not require or imply that the operations must be performed in that specific order, or that all the operations shown must be performed to achieve the desired result. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps.

[0162] After introducing the method of exemplary embodiments of the present invention, the following references are made. Figure 9 This invention provides an exemplary embodiment of a multi-wave migration imaging apparatus based on iterative deconvolution imaging conditions.

[0163] The implementation of the multi-wave migration imaging device based on iterative deconvolution imaging conditions can refer to the implementation of the above method, and the repeated parts will not be described again. The term "module" or "unit" used below can refer to a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0164] Based on the same inventive concept, this invention also proposes a multi-wave migration imaging device based on iterative deconvolution imaging conditions, such as... Figure 9 As shown, the device includes:

[0165] Data acquisition module 910 is used to acquire the forward propagation wavefield and the reverse propagation wavefield of seismic waves;

[0166] The multiple wave imaging processing module 920 is used to perform multiple wave imaging on the forward propagation wave field and the backward propagation wave field of the seismic wave using deconvolution imaging conditions to obtain the initial imaging results.

[0167] Using the forward propagation wavefield, the backward propagation wavefield, and the initial imaging results as input, multiple wave imaging is performed using the iterative deconvolution imaging method to obtain iterative deconvolution multiple wave imaging results.

[0168] During multiple-wave imaging, the objective function value of deconvolution imaging is determined;

[0169] If the target function value does not meet the preset condition, the imaging result is iterated until the deconvolution imaging target function value meets the preset condition. Based on the iterated imaging result, the final iterative deconvolution multiple imaging result is generated.

[0170] In one embodiment, the data acquisition module 910 is specifically used for:

[0171] Acquire input data; during forward propagation, the input data consists of seismic full-wavefield shot record data containing information on direct waves, primary reflected waves, and free-surface multiples.

[0172] Based on the input data, the forward propagation of the wave field is performed using the one-way wave equation algorithm to obtain the forward propagation wave field of the seismic wave.

[0173] In one embodiment, the data acquisition module 910 is specifically used for:

[0174] Acquire input data; during backpropagation, the input data is multiple wave information or seismic full-wavefield shot record;

[0175] Based on the input data, the wave field is propagated in reverse using the one-way wave equation algorithm to obtain the back-propagated seismic wave field.

[0176] In one embodiment, the multiple imaging processing module 920 determines the deconvolution imaging target function value during the multiple imaging process, including:

[0177] The objective function for deconvolution imaging is expressed as follows:

[0178]

[0179] Where E(R) is the objective function value;

[0180] U represents the back propagation wave field of the seismic wave;

[0181] D represents the forward propagation wavefield of the seismic wave;

[0182] R represents the imaging result;

[0183] This indicates taking the spatial derivative of the imaging result;

[0184] a and β are dimensionless parameters;

[0185] ω is the angular frequency;

[0186] This indicates that the frequency derivative of the imaging result is obtained.

[0187] In one embodiment, the multiple imaging processing module 920, if the target function value does not meet a preset condition, iterates the imaging results until the deconvolution imaging target function value meets the preset condition, and generates a final iterative deconvolution multiple imaging result based on the iterated imaging results, including:

[0188] The formula for the iterative deconvolution imaging condition is:

[0189]

[0190] Among them, R n+1 This is the imaging result after the (n+1)th iteration;

[0191] R n This is the imaging result after the nth iteration;

[0192] i, j, k, l are the spatial and frequency coordinates (x, y, z, ω) of the imaging result;

[0193] It is the complex conjugate of the forward propagation wavefield of the seismic wave.

[0194] In one embodiment, the multiple-wave imaging processing module 920 is specifically used for:

[0195] Based on the iterative imaging results R n+1 The objective function value is then recalculated; wherein the objective function value gradually approaches 0 during the calculation.

[0196] When the objective function value of the deconvolution imaging satisfies the preset condition, the final iterative deconvolution multiple imaging result is generated based on the iterative imaging result.

[0197] It should be noted that although several modules of the multi-wave migration imaging device based on iterative deconvolution imaging conditions have been mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, according to embodiments of the present invention, the features and functions of two or more modules described above can be embodied in one module. Conversely, the features and functions of one module described above can be further divided and embodied by multiple modules.

[0198] Based on the aforementioned inventive concept, such as Figure 10As shown, the present invention also proposes a computer device 1000, including a memory 1010, a processor 1020, and a computer program 1030 stored in the memory 1010 and executable on the processor 1020. When the processor 1020 executes the computer program 1030, it implements the aforementioned multi-wave migration imaging method based on iterative deconvolution imaging conditions.

[0199] Based on the aforementioned inventive concept, the present invention proposes a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the aforementioned multi-wave migration imaging method based on iterative deconvolution imaging conditions.

[0200] Based on the aforementioned inventive concept, the present invention proposes a computer program product, which includes a computer program that, when executed by a processor, implements a multi-wave migration imaging method based on iterative deconvolution imaging conditions.

[0201] The multi-wave migration imaging method and apparatus based on iterative deconvolution imaging conditions proposed in this invention offer greater flexibility and controllability during implementation. The iterative deconvolution imaging conditions constrain both the spatial and frequency directions of the imaging process. As an extension of conventional deconvolution imaging methods, the iterative deconvolution imaging conditions have a more complete physical basis. Furthermore, these conditions allow for a wider frequency spread in the imaging results, achieving better imaging resolution and providing strong technical support for oil exploration.

[0202] The acquisition, storage, use, and processing of data in this application comply with relevant laws and regulations.

[0203] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, apparatus, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0204] This invention is described with reference to flowchart illustrations and / or block diagrams of methods and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0205] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0206] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0207] Finally, it should be noted that the above-described embodiments are merely specific implementations of the present invention, used to illustrate the technical solutions of the present invention, and not to limit it. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments within the technical scope disclosed in the present invention, or make equivalent substitutions for some of the technical features; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method of multiple wave migration imaging based on an iterative deconvolution imaging condition, characterized in that, The method comprises the following steps: obtaining a forward seismic wave field and a reverse seismic wave field; performing multiple wave imaging on the forward seismic wave field and the reverse seismic wave field by using a deconvolution imaging condition to obtain an initial imaging result; using the forward seismic wave field, the reverse seismic wave field and the initial imaging result as inputs, performing multiple wave imaging by using an iterative deconvolution imaging method to obtain an iterative deconvolution multiple wave imaging result; in the multiple wave imaging process, determining a deconvolution imaging target function value; if the target function value does not satisfy a preset condition, iteratively performing imaging until the deconvolution imaging target function value satisfies the preset condition, and generating a final iterative deconvolution multiple wave imaging result according to the iteratively-imaged result; wherein, in the multiple wave imaging process, determining a deconvolution imaging target function value comprises: a relationship formula of the deconvolution imaging target function is: ； wherein, is the objective function value; to back-propagate the seismic wavefield; for seismic wave forward propagating field; for imaging results; denotes taking the spatial derivative of the imaging result; , dimensionless parameter; is the circular frequency; denotes taking the frequency derivative of the imaging result; if the target function value does not satisfy a preset condition, iteratively performing imaging until the deconvolution imaging target function value satisfies the preset condition, and generating a final iterative deconvolution multiple wave imaging result according to the iteratively-imaged result comprises: a formula of the iterative deconvolution imaging condition is: ； wherein, is the imaging result after the n+1th iteration; is the imaging result after the n-th iteration; i , j , k , l spatial and frequency coordinates of the imaging result (x, y, f); x, y, z, ); is the complex conjugate of the seismic wavefield.

2. The method of claim 1, wherein, obtaining a forward seismic wave field comprises: obtaining input data; in forward propagation, the input data is seismic full wave field shot record data containing direct wave, first reflection wave and free surface multiple wave information, performing forward propagation of the wave field by using a one-way wave equation algorithm according to the input data to obtain the forward seismic wave field.

3. The method of claim 1, wherein, obtaining a reverse seismic wave field comprises: obtaining input data; in reverse propagation, the input data is multiple wave information or seismic full wave field shot record; performing reverse propagation of the wave field by using a one-way wave equation algorithm according to the input data to obtain the reverse seismic wave field.

4. The method of claim 1, wherein, if the target function value does not satisfy a preset condition, iteratively performing imaging until the deconvolution imaging target function value satisfies the preset condition, and generating a final iterative deconvolution multiple wave imaging result according to the iteratively-imaged result comprises: re-computing the objective function value according to the iterated imaging result ; wherein the objective function value gradually approaches 0 when computed when the deconvolution imaging target function value satisfies the preset condition, generating a final iterative deconvolution multiple wave imaging result according to the iteratively-imaged result.

5. A device for multiple wave migration imaging based on an iterative deconvolution imaging condition, characterized in that, The method comprises the following steps: a data acquisition module is configured to obtain a forward seismic wave field and a reverse seismic wave field; a multiple wave imaging processing module is configured to perform multiple wave imaging on the forward seismic wave field and the reverse seismic wave field by using a deconvolution imaging condition to obtain an initial imaging result; using the forward seismic wave field, the reverse seismic wave field and the initial imaging result as inputs, performing multiple wave imaging by using an iterative deconvolution imaging method to obtain an iterative deconvolution multiple wave imaging result; in the multiple wave imaging process, determining a deconvolution imaging target function value; if the target function value does not satisfy a preset condition, iteratively performing imaging until the deconvolution imaging target function value satisfies the preset condition, and generating a final iterative deconvolution multiple wave imaging result according to the iteratively-imaged result; wherein, in the multiple wave imaging process, determining a deconvolution imaging target function value comprises: A relationship of the deconvolution imaging objective function is: wherein, is the objective function value; to backpropagate the wavefield of seismic waves; to be a seismic wavefield; for imaging results; denotes taking the spatial derivative of the imaging result; , dimensionless parameter; ω is the circular frequency; denotes taking the frequency derivative of the imaging result; The multiple wave imaging processing module iterates the imaging result until the deconvolution imaging objective function value meets the preset condition, and generates a final iterative deconvolution multiple wave imaging result according to the iterated imaging result, including: A formula of the iterative deconvolution imaging condition is: ； wherein, is the imaging result after the n+1th iteration; is the imaging result after the n-th iteration; i , j , k , l spatial and frequency coordinates of the imaging result x, y, z, ); is the complex conjugate of the seismic wavefield.

6. The apparatus for multiple wave migration imaging based on imaging conditions of iterative deconvolution of claim 5, wherein, The data acquisition module is specifically configured to: Obtain input data; in forward propagation, the input data is seismic full wave field shot record data containing direct wave, first reflection wave and free surface multiple wave information, According to the input data, a single-path wave wave equation algorithm is used for forward propagation of the wave field to obtain a seismic wave forward propagation wave field.

7. The apparatus for multiple wave migration imaging based on imaging conditions of iterative deconvolution of claim 5, wherein, The data acquisition module is specifically configured to: Obtain input data; in reverse propagation, the input data is multiple wave information or seismic full wave field shot record; According to the input data, a single-path wave wave equation algorithm is used for reverse propagation of the wave field to obtain a seismic wave reverse propagation wave field.

8. The apparatus for multiple wave migration imaging based on imaging conditions of iterative deconvolution of claim 7, wherein, The multiple wave imaging processing module is specifically configured to: re-computing the objective function value according to the iterated imaging result , wherein the objective function value gradually approaches 0 when calculated When the deconvolution imaging objective function value meets the preset condition, generate a final iterative deconvolution multiple wave imaging result according to the iterated imaging result.

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 executes the computer program to realize the method of any one of claims 1 to 4.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the computer program is executed by the processor to realize the method of any one of claims 1 to 4.

11. A computer program product, characterised in that, The computer program product includes a computer program, and the computer program is executed by the processor to realize the method of any one of claims 1 to 4.

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