Multi-wave migration imaging method and apparatus based on iterative deconvolutional imaging condition

Abstract

The present application relates to the technical field of seismic data imaging and migration in geophysical prospecting for petroleum. Provided are a multi-wave migration imaging method and apparatus based on an iterative deconvolutional imaging condition. The method comprises: acquiring a seismic wave forward wave field and a seismic wave reverse wave field; using a deconvolutional imaging condition to perform multi-wave imaging on the seismic wave forward wave field and the seismic wave reverse wave field so as 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, using an iterative deconvolutional imaging method to perform multi-wave imaging, so as to obtain an iterative deconvolutional multi-wave imaging result; during the multi-wave imaging, determining an objective function value of the deconvolutional imaging; if the objective function value does not meet a preset condition, iterating the imaging result until the objective function value of the deconvolutional imaging meets the preset condition, and generating a final iterative deconvolutional multi-wave imaging result according to an imaging result obtained after iteration.

Description

Multiple migration imaging method and device based on iterative deconvolution imaging conditions

[0001] Related applications

[0002] This application claims priority to Chinese patent application No. 202310678905.3 filed on June 8, 2023, and cites the contents disclosed in the above patent application as part of this application. Technical Field

[0003] The present application relates to the technical field of petroleum geophysical exploration seismic data imaging and migration, and in particular to a multiple wave migration imaging method and device based on iterative deconvolution imaging conditions. Background Art

[0004] This section is intended to provide a background or context to the embodiments of the present application that are recited in the claims. No admission is made that the description herein is prior art by virtue of its inclusion in this section.

[0005] In traditional marine exploration seismic processing, free surface multiples are generally removed as interference information. However, the free surface multiples contain information about subsurface medium parameters that is not fully utilized and exploited. This problem is a challenge and bottleneck in current seismic processing and imaging. Therefore, the free surface multiples imaging method can fully utilize the free surface multiples information to perform seismic migration in shallow and medium layers of the subsurface medium, achieving high-precision imaging of the seabed and its vicinity, and solving the problem of insufficient shallow imaging range of traditional imaging methods.

[0006] Berkhout and Verschuur (1994) proposed free-surface multiple migration based on the up- and down-wave framework. Subsequently, Schuster and Rickett (2000) converted multiples into primary waves through the principle of interference and migrated them according to the traditional imaging framework. Shan (2003) perfected this pseudo-primary 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 flows. Multiple imaging can be achieved within the framework of the one-way wave equation and the wave equation. Traditional multiple inversion methods, due to the presence of multi-order multiple information, cause multiple signals of different orders to image each other, resulting in interference and reduced imaging quality. This is also a major issue that makes its industrial application difficult.

[0007] Currently, methods for suppressing crosstalk during multiple imaging can be categorized into the following: The first is to use deconvolution imaging conditions to suppress crosstalk. This method is relatively simple to implement, but it can only serve as an approximation to eliminate crosstalk, suppressing or eliminating most of it. The second is to image multiples of different orders during imaging to avoid crosstalk caused by different orders. However, this method cannot eliminate crosstalk caused by multiples of the same order and requires additional separation of multiples of different orders in the seismic data. The third is multiple imaging based on migration algorithms. The core of this method is to estimate crosstalk events using a migration algorithm and then eliminate them. This method requires adaptive subtraction and separation of primaries and multiples. The fourth method is the least-squares multiple imaging method, which can effectively address the imaging crosstalk problem and can be implemented using one-way waves and wave equation methods. However, this method increases the computational complexity by several orders of magnitude and significantly affects the noise in the data.

[0008] Currently, industrial applications of multiple imaging primarily rely on multiple migration methods using deconvolution imaging, resulting in low-resolution and poor imaging quality. Therefore, a technical solution is urgently needed that can overcome these limitations and improve imaging quality.

[0009] Summary of the Invention

[0010] To address the challenges of existing technologies, this application proposes a multiple migration imaging method and apparatus based on iterative deconvolution imaging. Unlike conventional deconvolution imaging, this patent introduces regularization terms in both frequency and spatial methods, achieving a wider frequency range and clearer imaging results.

[0011] In a first aspect of an embodiment of the present application, a multiple migration imaging method based on iterative deconvolution imaging conditions is proposed, comprising:

[0012] Obtaining the forward propagation wave field of seismic waves and the reverse propagation wave field of seismic waves;

[0013] Deconvolution imaging conditions are used to perform multiple wave imaging processing on the forward and reverse wave fields of seismic waves to obtain the initial imaging results;

[0014] Taking the forward propagation wave field of seismic waves, the reverse propagation wave field of seismic waves and the initial imaging results as input, the iterative deconvolution imaging method is used to perform multiple wave imaging processing to obtain the iterative deconvolution multiple wave imaging results;

[0015] In the process of multiple wave imaging, the deconvolution imaging objective function value is determined;

[0016] If the objective function value does not meet the preset conditions, the imaging results are iterated until the deconvolution imaging objective function value meets the preset conditions, and the final iterative deconvolution multiple wave imaging results are generated based on the imaging results after iteration.

[0017] In the multiple wave migration imaging method based on iterative deconvolution imaging conditions in an embodiment of the present application, obtaining the seismic wave forward propagation wave field includes:

[0018] Get input data; in forward propagation, the input data is seismic full wave field shot record data containing direct wave, primary reflection wave and free surface multiple wave information,

[0019] According to the input data, the one-way wave equation is used to simulate the forward propagation of the wave field to obtain the forward propagation wave field of the seismic wave.

[0020] In the multiple wave migration imaging method based on iterative deconvolution imaging conditions in an embodiment of the present application, obtaining the seismic wave back propagation wave field includes:

[0021] Get input data; in reverse propagation, the input data is multiple wave information or seismic full wave field shot record;

[0022] According to the input data, the one-way wave equation is used to simulate the reverse propagation of the wave field to obtain the seismic wave reverse propagation wave field.

[0023] In the multiple migration imaging method based on iterative deconvolution imaging conditions in an embodiment of the present application, determining the deconvolution imaging objective function value during the multiple imaging process includes:

[0024] The relationship between the deconvolution imaging objective function is:

[0025] Where E(R) is the objective function value;

[0026] U is the back propagation wave field of seismic waves;

[0027] D is the forward propagation wave field of seismic waves;

[0028] R is the imaging result;

[0029] Indicates obtaining the spatial derivative of the imaging result;

[0030] a and β are dimensionless parameters;

[0031] ω is the circular frequency;

[0032] Indicates obtaining the frequency derivative of the imaging result.

[0033] In the multiple migration imaging method based on iterative deconvolution imaging conditions in an embodiment of the present application, if the objective function value does not meet the preset condition, the imaging result is iterated until the deconvolution imaging objective function value meets the preset condition. Based on the imaging result after the iteration, a final iterative deconvolution multiple imaging result is generated, including:

[0034] The formula for iterative deconvolution imaging conditions is:

[0035] Among them, R n+1 is the imaging result after the n+1th iteration;

[0036] R n is the imaging result after the nth iteration;

[0037] i, j, k, and l are the spatial and frequency coordinates of the imaging results (x, y, z, ω);

[0038] is the complex conjugate of the forward propagation wave field of the seismic wave.

[0039] In the multiple migration imaging method based on iterative deconvolution imaging conditions in an embodiment of the present application, if the objective function value does not meet the preset condition, the imaging result is iterated until the deconvolution imaging objective function value meets the preset condition. Based on the imaging result after the iteration, a final iterative deconvolution multiple imaging result is generated, including:

[0040] According to the imaging result R after iteration n+1 , recalculate the objective function value; wherein, the objective function value gradually approaches 0 during calculation;

[0041] When the deconvolution imaging objective function value meets the preset conditions, the final iterative deconvolution multiple wave imaging result is generated according to the imaging result after iteration.

[0042] In a second aspect of an embodiment of the present application, a multiple migration imaging device based on iterative deconvolution imaging conditions is proposed, comprising:

[0043] A data acquisition module is used to acquire the forward propagation wave field of seismic waves and the reverse propagation wave field of seismic waves;

[0044] The multiple wave imaging processing module is used to perform multiple wave imaging on the forward propagation wave field and the reverse propagation wave field of the seismic wave using deconvolution imaging conditions to obtain initial imaging results;

[0045] Taking the seismic wave forward wave field, the seismic wave backward wave field and the initial imaging result as input, the iterative deconvolution imaging method is used to perform multiple wave imaging to obtain the iterative deconvolution multiple wave imaging result;

[0046] In the process of multiple wave imaging, the deconvolution imaging objective function value is determined;

[0047] If the objective function value does not meet the preset conditions, the imaging results are iterated until the deconvolution imaging objective function value meets the preset conditions, and the final iterative deconvolution multiple wave imaging results are generated based on the imaging results after iteration.

[0048] In the multiple migration imaging device based on iterative deconvolution imaging conditions in the embodiment of the present application, the data acquisition module is specifically used to:

[0049] Get input data; in forward propagation, the input data is seismic full wave field shot record data containing direct wave, primary reflection wave and free surface multiple wave information,

[0050] According to the input data, the one-way wave equation is used to simulate the forward propagation of the wave field to obtain the forward propagation wave field of the seismic wave.

[0051] In the multiple migration imaging device based on iterative deconvolution imaging conditions in the embodiment of the present application, the data acquisition module is specifically used to:

[0052] Get input data; in reverse propagation, the input data is multiple wave information or seismic full wave field shot record;

[0053] According to the input data, the one-way wave equation is used to simulate the reverse propagation of the wave field to obtain the seismic wave reverse propagation wave field.

[0054] In the multiple migration imaging device based on iterative deconvolution imaging conditions in an embodiment of the present application, the multiple imaging processing module determines the deconvolution imaging objective function value during the multiple imaging process, including:

[0055] The relationship between the deconvolution imaging objective function is:

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

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

[0058] D is the forward propagation wave field of seismic waves;

[0059] R is the imaging result;

[0060] Indicates obtaining the spatial derivative of the imaging result;

[0061] a and β are dimensionless parameters;

[0062] ω is the circular frequency;

[0063] Indicates obtaining the frequency derivative of the imaging result.

[0064] In the multiple migration imaging device based on iterative deconvolution imaging conditions in an embodiment of the present application, the multiple imaging processing module iterates the imaging results until the deconvolution imaging objective function value satisfies the preset conditions if the objective function value does not meet the preset conditions, and generates a final iterative deconvolution multiple imaging result based on the iterative imaging results, including:

[0065] The formula for iterative deconvolution imaging conditions is:

[0066] Among them, R n+1 is the imaging result after the n+1th iteration;

[0067] R n is the imaging result after the nth iteration;

[0068] i, j, k, and l are the spatial and frequency coordinates of the imaging results (x, y, z, ω);

[0069] is the complex conjugate of the forward propagation wave field of the seismic wave.

[0070] In the multiple wave migration imaging device based on iterative deconvolution imaging conditions in an embodiment of the present application, the multiple wave imaging processing module is specifically configured to:

[0071] According to the imaging result R after iteration n+1 , recalculate the objective function value; wherein, the objective function value gradually approaches 0 during calculation;

[0072] When the deconvolution imaging objective function value meets the preset conditions, the final iterative deconvolution multiple wave imaging result is generated according to the imaging result after iteration.

[0073] In a third aspect of an embodiment of the present application, a computer device is proposed, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, a multiple wave migration imaging method based on iterative deconvolution imaging conditions is implemented.

[0074] In a fourth aspect of the embodiments of the present application, a computer-readable storage medium is proposed. The computer-readable storage medium stores a computer program. When the computer program is executed by a processor, a multiple-wave migration imaging method based on iterative deconvolution imaging conditions is implemented.

[0075] In a fifth aspect of the embodiments of the present application, a computer program product is proposed. The computer program product includes a computer program. When the computer program is executed by a processor, a multiple wave migration imaging method based on iterative deconvolution imaging conditions is implemented.

[0076] The multiple migration imaging method and apparatus proposed in this application, based on iterative deconvolution imaging conditions, employ constraints in both spatial and frequency domains, providing greater controllable imaging flexibility. This method extends conventional deconvolution imaging methods and boasts a more comprehensive physical foundation. Iterative deconvolution imaging conditions can extend the frequency range of imaging results and achieve higher resolution, providing powerful technical support for petroleum exploration. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0078] FIG1 is a flow chart of a multiple migration imaging method based on iterative deconvolution imaging conditions according to an embodiment of the present application.

[0079] FIG2 is a schematic diagram of a multiple wave imaging process under iterative deconvolution conditions according to a specific embodiment of the present application.

[0080] FIG3A is a schematic diagram of a full-wavefield seismic record of a single-layer model according to a specific embodiment of the present application.

[0081] FIG. 3B is a schematic diagram of multiple wave recording according to a specific embodiment of the present application.

[0082] FIG. 4A is a schematic diagram of a multiple migration result of a cross-correlation imaging condition according to a specific embodiment of the present application.

[0083] FIG4B is a partially enlarged schematic diagram of FIG4A .

[0084] FIG4C is a schematic diagram of a multiple migration result using conventional deconvolution imaging conditions according to a specific embodiment of the present application.

[0085] FIG4D is a partially enlarged schematic diagram of FIG4C .

[0086] FIG4E is a schematic diagram of the iterative deconvolution imaging conditional multiple migration results according to a specific embodiment of the present application.

[0087] FIG4F is a partially enlarged schematic diagram of FIG4E .

[0088] FIG5 is a schematic diagram of spectrum comparison results under cross-correlation, conventional deconvolution, and iterative deconvolution conditions according to a specific embodiment of the present application.

[0089] FIG6 is a schematic diagram of VSP acquisition and observation using the Marmousi model according to a specific embodiment of the present application.

[0090] FIG7A is a schematic diagram of seismic recording at a receiving point depth of 200 m according to a specific embodiment of the present application.

[0091] FIG7B is a schematic diagram of seismic records at a receiving point depth of 1700 m according to a specific embodiment of the present application.

[0092] FIG7C is a schematic diagram of seismic records at a receiving point depth of 3200 m according to a specific embodiment of the present application.

[0093] FIG8A is a schematic diagram of conventional deconvolution migration results according to a specific embodiment of the present application.

[0094] FIG8B is a schematic diagram of an iterative deconvolution migration result according to a specific embodiment of the present application.

[0095] FIG9 is a schematic diagram of the architecture of a multiple migration imaging device based on iterative deconvolution imaging conditions according to an embodiment of the present application.

[0096] FIG10 is a schematic diagram of the computer device structure according to an embodiment of the present application. DETAILED DESCRIPTION

[0097] The principles and spirit of the present application will be described below with reference to several exemplary embodiments. It should be understood that these embodiments are provided solely to enable those skilled in the art to better understand and implement the present application, and are not intended to limit the scope of the present application in any way. Rather, these embodiments are provided to make the present disclosure more thorough and complete, and to fully convey the scope of the present disclosure to those skilled in the art.

[0098] Those skilled in the art will appreciate that the embodiments of the present application may be implemented as a system, apparatus, device, method, or computer program product. Therefore, the present disclosure may be implemented in the following forms: entirely in hardware, entirely in software (including firmware, resident software, microcode, etc.), or in a combination of hardware and software.

[0099] According to embodiments of this application, a multiple migration imaging method and apparatus based on iterative deconvolution imaging conditions are proposed, relating to the technical field of seismic data imaging and migration for petroleum geophysical exploration. This application proposes a regularized objective function with spatial and frequency domain constraints and provides an iterative solution method. This approach maximizes the frequency band of the migration imaging and improves imaging quality during multiple migration.

[0100] The principles and spirit of the present application are explained in detail below with reference to several representative implementations of the present application.

[0101] FIG1 is a flow chart of a multiple migration imaging method based on iterative deconvolution imaging conditions according to an embodiment of the present invention. As shown in FIG1 , the method includes:

[0102] Step 101, obtaining the forward propagation wavefield of the seismic wave and the reverse propagation wavefield of the seismic wave;

[0103] Step 102, performing multiple wave imaging on the forward propagation wavefield and the reverse propagation wavefield of the seismic wave using deconvolution imaging conditions to obtain an initial imaging result;

[0104] Step 103, using the seismic wave forward wavefield, the seismic wave backward wavefield and the initial imaging result as input, performing multiple wave imaging using an iterative deconvolution imaging method to obtain an iterative deconvolution multiple wave imaging result;

[0105] Step 104, during the multiple wave imaging process, determining a deconvolution imaging objective function value;

[0106] Step 105: If the objective function value does not meet the preset condition, the imaging result is iterated until the deconvolution imaging objective function value meets the preset condition, and a final iterative deconvolution multiple wave imaging result is generated based on the iterative imaging result.

[0107] In actual application scenarios, the multiple wave migration imaging method based on iterative deconvolution imaging conditions has the following working principles: obtaining the forward propagation wave field and the reverse propagation wave field of the seismic wave; performing multiple wave imaging on the forward propagation wave field and the reverse propagation wave field of the seismic wave using the deconvolution imaging conditions to obtain an initial imaging result; using the forward propagation wave field, the reverse propagation wave field and the initial imaging result as input, performing multiple wave imaging using the iterative deconvolution imaging method to obtain an iterative deconvolution multiple wave imaging result; during the multiple wave imaging process, determining the deconvolution imaging objective function value; if the objective function value does not meet the preset conditions, iterating the imaging result until the deconvolution imaging objective function value meets the preset conditions, and generating the final iterative deconvolution multiple wave imaging result based on the imaging result after iteration. This application proposes an objective function with regularization constraints in spatial and frequency domains, and provides an iterative solution method. When performing multiple wave migration, the frequency band range of the migration imaging can be increased as much as possible, thereby improving the imaging quality.

[0108] In order to explain the multiple migration imaging method based on iterative deconvolution imaging conditions more clearly, each step will be described in detail below.

[0109] In one embodiment, step 101, obtaining a seismic wave forward propagation wave field, includes:

[0110] Get input data; in forward propagation, the input data is seismic full wave field shot record data containing direct wave, primary reflection wave and free surface multiple wave information,

[0111] According to the input data, the one-way wave equation is used to simulate the forward propagation of the wave field to obtain the forward propagation wave field of the seismic wave.

[0112] The forward wavelength of seismic waves can be represented by D.

[0113] In one embodiment, step 101, obtaining a seismic wave back propagation wave field, includes:

[0114] Get input data; in reverse propagation, the input data is multiple wave information or seismic full wave field shot record;

[0115] According to the input data, the one-way wave equation is used to simulate the reverse propagation of the wave field to obtain the seismic wave reverse propagation wave field.

[0116] The wavelength of the seismic wave can be expressed as U.

[0117] In one embodiment, in step 102, multiple wave imaging is performed on the forward and reverse wave fields of the seismic waves using deconvolution imaging conditions to obtain an initial imaging result R 0 ;

[0118] In one embodiment, step 103 is to convert the seismic wave forward wave field, the seismic wave backward wave field and the initial imaging result R 0 As input, multiple wave imaging is performed using an iterative deconvolution imaging method to obtain an iterative deconvolution multiple wave imaging result;

[0119] In one embodiment, step 104, determining a deconvolution imaging objective function value during the multiple imaging process, includes:

[0120] The relationship between the deconvolution imaging objective function is:

[0121] Where E(R) is the objective function value;

[0122] U is the back propagation wave field of seismic waves;

[0123] D is the forward propagation wave field of seismic waves;

[0124] R is the imaging result;

[0125] Indicates obtaining the spatial derivative of the imaging result;

[0126] a and β are dimensionless parameters;

[0127] ω is the circular frequency;

[0128] Indicates obtaining the frequency derivative of the imaging result.

[0129] In one embodiment, in step 105, if the objective function value does not satisfy a preset condition, the imaging result is iterated until the deconvolution imaging objective function value satisfies the preset condition, and a final iterative deconvolution multiple imaging result is generated based on the iterative imaging result, including:

[0130] The formula for iterative deconvolution imaging conditions is:

[0131] Among them, R n+1 is the imaging result after the n+1th iteration;

[0132] R n is the imaging result after the nth iteration;

[0133] i, j, k, l are the spatial and frequency coordinates (x, y, z, ω) of the imaging results; i, j, k correspond to the spatial coordinates x, y, z, and l corresponds to the frequency ω;

[0134] is the complex conjugate of the forward propagation wave field of the seismic wave.

[0135] According to the imaging result R after iteration n+1 , recalculate the objective function value; wherein, the objective function value gradually approaches 0 during calculation;

[0136] When the deconvolution imaging objective function value meets the preset conditions, the final iterative deconvolution multiple wave imaging result is generated according to the imaging result after iteration.

[0137] In order to more clearly explain the multiple migration imaging method based on iterative deconvolution imaging conditions, a detailed description is given below in conjunction with a specific embodiment.

[0138] In the context of existing technologies, the objective function E(R) that needs to be solved for multiple wave migration under traditional deconvolution imaging conditions is:

[0139] The multiple wave imaging under the traditional deconvolution imaging condition is to solve formula (1) and derive the following specific imaging formula:

[0140] in, is the imaging result;

[0141] Existing industrial applications of multiple wave imaging mainly use the multiple wave migration method under deconvolution imaging conditions. This patent application differs from the traditional multiple wave imaging under deconvolution imaging conditions by introducing regularization terms in frequency and space methods, achieving a wider frequency range of multiple wave imaging results and clearer imaging results. Specifically, compared with the objective function of traditional deconvolution imaging conditions, this application proposes a new deconvolution imaging objective function:

[0142] Formula (3) cannot use the traditional gradient solution to separate the imaging results. It is necessary to use the optical flow method to solve the objective function. The calculation method is:

[0143] Formula (4) is the formula for iterative deconvolution imaging conditions. By using it to iteratively solve the imaging results, iterative deconvolution multiple wave imaging can be achieved.

[0144] The multiple migration imaging method based on iterative deconvolution imaging conditions proposed in this application has at least the following advantages over the existing technology:

[0145] 1. Iterative deconvolution imaging conditions are constrained in both the spatial and frequency directions of imaging, and the imaging controllable flexibility is higher.

[0146] 2. The iterative deconvolution imaging condition is an extension of the conventional deconvolution imaging method, and its physical basis is more complete.

[0147] 3. Iterative deconvolution imaging conditions can make the frequency of imaging results wider and achieve better imaging resolution.

[0148] In conjunction with a practical scenario, reference is made to Figure 2, which illustrates a schematic diagram of the multiple wave imaging process for iterative deconvolution conditions in accordance with a specific embodiment of the present application. As shown in Figure 2, a seismic shot record is first input. The input data for forward propagation is a full-wavefield seismic shot record containing direct waves, primary reflections, and free-surface multiples. The input data for reverse propagation can be either just the multiples or a full-wavefield seismic shot record.

[0149] Then, using the input shot records, the one-way wave equation algorithm is used to perform forward and backward propagation of the wave field to obtain the forward propagation wave field D and the backward propagation wave field U. The conventional deconvolution imaging conditions are used to perform multiple wave imaging on the forward and backward propagation wave fields, and the imaging result R is calculated. 0 .

[0150] Then the wave fields U, D and the initial imaging result R 0 As input, the iterative deconvolution imaging formula is used to perform multiple wave imaging. After n iterations, the iterative deconvolution multiple wave imaging result R can be obtained. n After n+1 iterations, the iterative deconvolution multiple wave imaging result R can be obtained n+1 .

[0151] To verify the effectiveness of this method, full-wavefield seismic records (Figure 3A) and multiple wave records (Figure 3B) of a single-layer model were used as input for calculations. Multiple wave imaging under cross-correlation imaging conditions, conventional deconvolution imaging conditions, and iterative deconvolution imaging conditions was obtained. The calculation results are shown in Figures 4A to 4F. Among them, the abscissa range of Figures 4A, 4C, and 4E is 0-135, and the ordinate range is 0-123; the corresponding local enlarged images (Figures 4B, 4D, and 4F) all have abscissa ranges of 56-77, and the ordinate range is 0-100.

[0152] The spectra of the three results are further compared, as shown in Figure 5. As can be seen, the iterative deconvolution imaging result has the widest spectrum and the highest resolution, demonstrating the effectiveness of the method. To further verify the stability of the method, VSP seismic acquisition was performed using the Marmousi model, as shown in Figure 6. Due to the relatively complex Marmousi model, relatively complex common receiver gathers were received at different depths, as shown in Figures 7A to 7C.

[0153] Finally, multiple migration was performed using conventional deconvolution imaging and iterative deconvolution imaging, as shown in Figures 8A and 8B. Comparison shows that the resolution and lateral continuity of the iterative deconvolution imaging results are significantly improved, demonstrating the advantages and effectiveness of this method.

[0154] It should be noted that although the operations of the method of the present application are described in a specific order in the above embodiments and drawings, this does not require or imply that these operations must be performed in this specific order, or that all illustrated operations must be performed to achieve the desired results. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps.

[0155] After introducing the method according to the exemplary embodiment of the present application, the multiple migration imaging apparatus based on iterative deconvolution imaging conditions according to the exemplary embodiment of the present application will be introduced with reference to FIG. 9 .

[0156] The implementation of the multiple migration imaging device based on iterative deconvolution imaging conditions can be referenced to the implementation of the aforementioned method, and any repetitions will not be repeated. The terms "module" or "unit" used below may refer to a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented using software, implementation using hardware, or a combination of software and hardware, is also possible and contemplated.

[0157] Based on the same inventive concept, the present application also proposes a multiple wave migration imaging device based on iterative deconvolution imaging conditions, as shown in FIG9 . The device includes:

[0158] The data acquisition module 910 is used to acquire the forward propagation wave field and the reverse propagation wave field of the seismic wave;

[0159] The multiple wave imaging processing module 920 is used to perform multiple wave imaging on the forward propagation wave field and the reverse propagation wave field of the seismic wave using deconvolution imaging conditions to obtain initial imaging results;

[0160] Taking the seismic wave forward wave field, the seismic wave backward wave field and the initial imaging result as input, the iterative deconvolution imaging method is used to perform multiple wave imaging to obtain the iterative deconvolution multiple wave imaging result;

[0161] In the process of multiple wave imaging, the deconvolution imaging objective function value is determined;

[0162] If the objective function value does not meet the preset conditions, the imaging results are iterated until the deconvolution imaging objective function value meets the preset conditions, and the final iterative deconvolution multiple wave imaging results are generated based on the imaging results after iteration.

[0163] In one embodiment, the data acquisition module 910 is specifically configured to:

[0164] Get input data; in forward propagation, the input data is seismic full wave field shot record data containing direct wave, primary reflection wave and free surface multiple wave information,

[0165] According to the input data, the one-way wave equation is used to simulate the forward propagation of the wave field to obtain the forward propagation wave field of the seismic wave.

[0166] In one embodiment, the data acquisition module 910 is specifically configured to:

[0167] Get input data; in reverse propagation, the input data is multiple wave information or seismic full wave field shot record;

[0168] According to the input data, the one-way wave equation is used to simulate the reverse propagation of the wave field to obtain the seismic wave reverse propagation wave field.

[0169] In one embodiment, the multiple imaging processing module 920 determines the deconvolution imaging objective function value during the multiple imaging process, including:

[0170] The relationship between the deconvolution imaging objective function is:

[0171] Where E(R) is the objective function value;

[0172] U is the back propagation wave field of seismic waves;

[0173] D is the forward propagation wave field of seismic waves;

[0174] R is the imaging result;

[0175] Indicates obtaining the spatial derivative of the imaging result;

[0176] a and β are dimensionless parameters;

[0177] ω is the circular frequency;

[0178] Indicates obtaining the frequency derivative of the imaging result.

[0179] In one embodiment, if the objective function value does not satisfy a preset condition, the multiple imaging processing module 920 iterates the imaging result until the deconvolution imaging objective function value satisfies the preset condition, and generates a final iterative deconvolution multiple imaging result based on the iterative imaging result, including:

[0180] The formula for iterative deconvolution imaging conditions is:

[0181] Among them, R n+1 is the imaging result after the n+1th iteration;

[0182] R n is the imaging result after the nth iteration;

[0183] i, j, k, and l are the spatial and frequency coordinates of the imaging results (x, y, z, ω);

[0184] is the complex conjugate of the forward propagation wave field of the seismic wave.

[0185] In one embodiment, the multiple imaging processing module 920 is specifically configured to:

[0186] According to the imaging result R after iteration n+1 , recalculate the objective function value; wherein, the objective function value gradually approaches 0 during calculation;

[0187] When the deconvolution imaging objective function value meets the preset conditions, the final iterative deconvolution multiple wave imaging result is generated according to the imaging result after iteration.

[0188] It should be noted that while the above detailed description mentions several modules of the multiple migration imaging apparatus based on iterative deconvolution imaging conditions, this division is merely exemplary and not mandatory. In practice, depending on the embodiments of the present application, the features and functions of two or more modules described above may be embodied in a single module. Conversely, the features and functions of a single module described above may be further divided and embodied by multiple modules.

[0189] Based on the aforementioned inventive concept, as shown in FIG10 , the present application further proposes a computer device 1000, comprising 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, the aforementioned multiple-wave migration imaging method based on iterative deconvolution imaging conditions is implemented.

[0190] Based on the aforementioned inventive concept, the present application proposes a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the multiple wave migration imaging method based on iterative deconvolution imaging conditions is implemented.

[0191] Based on the aforementioned inventive concept, the present application proposes a computer program product, which includes a computer program. When the computer program is executed by a processor, a multiple wave migration imaging method based on iterative deconvolution imaging conditions is implemented.

[0192] The multiple migration imaging method and apparatus proposed in this application, based on iterative deconvolution imaging conditions, employ constraints in both spatial and frequency domains, providing greater controllable imaging flexibility. This method extends conventional deconvolution imaging methods and boasts a more comprehensive physical foundation. Iterative deconvolution imaging conditions can extend the frequency range of imaging results and achieve higher resolution, providing powerful technical support for petroleum exploration.

[0193] The acquisition, storage, use, and processing of data in the technical solution of this application comply with relevant laws and regulations.

[0194] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, devices, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0195] The present application is described with reference to the flowcharts and / or block diagrams of the methods and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device for implementing the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0196] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a product including an instruction device that implements the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0197] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0198] Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present application, which are used to illustrate the technical solutions of the present application, rather than to limit them. The scope of protection of the present application is not limited thereto. Although the present application has been described in detail with reference to the above-described embodiments, those skilled in the art should understand that any person skilled in the art can modify or easily conceive of changes to the technical solutions described in the above-described embodiments within the technical scope disclosed in the present application, or perform equivalent replacements for some of the technical features thereof. These modifications, changes, or replacements do not deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application shall be subject to the scope of protection of the claims.

Claims

1. A multiple wave migration imaging method based on iterative deconvolution imaging conditions, characterized in that: include: Obtaining seismic wave forward wave field and seismic wave reverse wave field; Performing multiple wave imaging on the forward wave field of the seismic wave and the reverse wave field of the seismic wave using deconvolution imaging conditions 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 input, performing multiple wave imaging by using an iterative deconvolution imaging method, and obtaining an iterative deconvolution multiple wave imaging result; In the process of multiple wave imaging, the objective function value of deconvolution imaging is determined; If the objective function value does not meet the preset condition, the imaging result is iterated until the deconvolution imaging objective function value meets the preset condition, and the final iterative deconvolution multiple wave imaging result is generated according to the iterative imaging result.

2. The multiple wave migration imaging method based on iterative deconvolution imaging conditions according to claim 1, characterized in that: Obtain seismic wave forward wave field, including: Get input data; in forward propagation, the input data is seismic full-wave field shot record data containing direct wave, primary reflection wave and free surface multiple wave information. According to the input data, the forward propagation of the wave field is simulated by using the one-way wave equation to obtain the seismic wave forward propagation wave field.

3. The multiple wave migration imaging method based on iterative deconvolution imaging conditions according to claim 1, characterized in that: Obtain seismic wave back propagation field, including: Get input data; in reverse propagation, the input data is multiple wave information or seismic full wave field shot records; According to the input data, the reverse propagation of the wave field is simulated by using the one-way wave equation to obtain the seismic wave reverse propagation wave field.

4. The multiple wave migration imaging method based on iterative deconvolution imaging conditions according to claim 1, characterized in that: In the process of multiple wave imaging, the deconvolution imaging objective function value is determined, including: The relational expression of the deconvolution imaging objective function is: Where, E(R) is the objective function value; U is the back propagation wave field of seismic waves; D is the positive wave field of seismic waves; R is the imaging result; Indicates obtaining the spatial derivative of the imaging result; a and β are dimensionless parameters; ω is the circular frequency; It means to obtain the frequency derivative of the imaging result.

5. The multiple wave migration imaging method based on iterative deconvolution imaging conditions according to claim 4, characterized in that: If the objective function value does not meet the preset condition, the imaging result is iterated until the deconvolution imaging objective function value meets the preset condition, and a final iterative deconvolution multiple wave imaging result is generated according to the iterative imaging result, including: The formula for iterative deconvolution imaging conditions is: Among them, R n+1 is the imaging result after the n+1th iteration; R n is the imaging result after the nth iteration; i, j, k, and l are the spatial and frequency coordinates of the imaging results (x, y, z, ω); It is the complex conjugate of the forward propagation wave field of the seismic wave.

6. The multiple wave migration imaging method based on iterative deconvolution imaging conditions according to claim 5, characterized in that: If the objective function value does not meet the preset condition, the imaging result is iterated until the deconvolution imaging objective function value meets the preset condition, and a final iterative deconvolution multiple wave imaging result is generated according to the iterative imaging result, including: According to the imaging result R after iteration n+1 , recalculate the objective function value; wherein the objective function value gradually approaches 0 during calculation; When the deconvolution imaging objective function value meets the preset condition, a final iterative deconvolution multiple wave imaging result is generated according to the imaging result after iteration.

7. A multiple wave migration imaging device based on iterative deconvolution imaging conditions, characterized in that: include: A data acquisition module, used to acquire the forward wave field of seismic waves and the reverse wave field of seismic waves; A multiple wave imaging processing module, used for performing multiple wave imaging on the seismic wave forward propagation wave field and the seismic wave reverse propagation wave field by using deconvolution imaging conditions 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 input, performing multiple wave imaging by using an iterative deconvolution imaging method, and obtaining an iterative deconvolution multiple wave imaging result; In the process of multiple wave imaging, the objective function value of deconvolution imaging is determined; If the objective function value does not meet the preset conditions, the imaging result is iterated until the deconvolution imaging objective function The numerical value satisfies the preset condition, and the final iterative deconvolution multiple wave imaging result is generated according to the imaging result after iteration.

8. The multiple wave migration imaging device based on iterative deconvolution imaging conditions according to claim 7, characterized in that: The data acquisition module is specifically used for: Get input data; in forward propagation, the input data is seismic full-wave field shot record data containing direct wave, primary reflection wave and free surface multiple wave information. According to the input data, the forward propagation of the wave field is simulated by using the one-way wave equation to obtain the seismic wave forward propagation wave field.

9. The multiple wave migration imaging device based on iterative deconvolution imaging conditions according to claim 7, characterized in that: The data acquisition module is specifically used for: Get input data; in reverse propagation, the input data is multiple wave information or seismic full wave field shot records; According to the input data, the reverse propagation of the wave field is simulated by using the one-way wave equation to obtain the seismic wave reverse propagation wave field.

10. The multiple wave migration imaging device based on iterative deconvolution imaging conditions according to claim 7, characterized in that: The multiple wave imaging processing module determines the deconvolution imaging objective function value during the multiple wave imaging process, including: The relational expression of the deconvolution imaging objective function is: Where, E(R) is the objective function value; U is the back propagation wave field of seismic waves; D is the positive wave field of seismic waves; R is the imaging result; Indicates obtaining the spatial derivative of the imaging result; a and β are dimensionless parameters; ω is the circular frequency; It means to obtain the frequency derivative of the imaging result.

11. The multiple wave migration imaging device based on iterative deconvolution imaging conditions according to claim 10, characterized in that: The multiple wave imaging processing module, if the objective function value does not meet the preset condition, 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: The formula for iterative deconvolution imaging conditions is: Among them, R n+1 is the imaging result after the n+1th iteration; R n is the imaging result after the nth iteration; i, j, k, and l are the spatial and frequency coordinates of the imaging results (x, y, z, ω); It is the complex conjugate of the forward propagation wave field of the seismic wave.

12. The multiple wave migration imaging device based on iterative deconvolution imaging conditions according to claim 11, characterized in that: The multiple wave imaging processing module is specifically used for: According to the imaging result R after iteration n+1 , recalculate the objective function value; wherein the objective function value gradually approaches 0 during calculation; When the deconvolution imaging objective function value meets the preset condition, a final iterative deconvolution multiple wave imaging result is generated according to the imaging result after iteration.

13. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 6 is implemented.

14. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

15. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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