Imaging gather stacking method and system based on illumination optimization

Abstract

The method and system described in the present invention relate to the field of geophysical exploration technology, including: counting the energy distribution characteristics on the imaging gathers; eliminating abnormal traces based on energy relationships; constructing an effective illumination area model and outputting the area with better illumination; correcting the imaging gathers based on energy constraints; constructing a new reference trace model and outputting weighted coefficients based on the similarity coefficient method; and outputting imaging profiles based on weighted stacking. The imaging gather stacking method based on illumination optimization provided by the present invention can realize the denoising of the imaging gathers, and can also correct the energy anomalies of the imaging gather stacking. At the same time, the present invention can balance the imaging profiles and realize the amplitude-preserving stacking. Secondly, the present invention can be applied not only to the time domain imaging gathers, but also to the depth domain imaging gathers to improve the quality of the offset imaging. The present invention achieves better results in both the denoising of the imaging gathers and the imaging quality.

Description

Technical Field

[0001] The invention relates to the field of geophysical exploration technology, and in particular to an imaging gather stacking method and system based on illumination optimization. Background Art

[0002] Migration imaging is an important output result in oil and gas exploration. Based on high-precision migration imaging results, the structural characteristics of the underground can be determined, and the physical property distribution characteristics of the underground can be revealed. The imaging results are usually obtained by generating a common imaging point gather (CIG) by pre-stack depth migration, and then superimposing the imaging gathers, or implicitly superimposing the imaging results of different shot data or different offset distance data. However, due to inaccurate velocity models and approximate physical processes, the stacked imaging results are uneven or unfocused. In addition, complex terrain and underground structures, incomplete observation systems, and seismic wavelets with dramatic spatial variations lead to uneven illumination and migration artifacts on the CIG. Therefore, it is necessary to study appropriate stacking imaging methods for imaging gathers to improve imaging quality. There are mainly the following methods for stacking imaging gathers:

[0003] (1): Average (mean) stacking, including stacking after removing the imaging gathers with large angles or large offsets. This type of method is generally implemented by default in the offset imaging process, or generates common imaging point gathers, and directly stacks without additional processing of the imaging gathers. However, in actual exploration, the imaging gathers obtained often have serious inter-trace depth differences (or time differences), low signal-to-noise ratio, and large-angle (large-offset) wavelet stretching. The imaging quality obtained by this type of method is often poor.

[0004] (2): Weighted superposition method, which improves the effect of mean superposition by giving different weighting coefficients on different channels. In this type of method, the determination of weighting coefficients is the core point. The existing methods mainly include cross-correlation method (Zhang and Williamson, 2018), similarity coefficient method (Liu et al., 2009; Deng et al., 2015), and simulated annealing method (Zhu, 2017).

[0005] However, the above method only considers the wavelet characteristics between imaging gathers, and does not consider the illumination conditions on the imaging gathers. In order to further improve the quality of migration imaging, the present invention optimizes the imaging gathers for optimal illumination, identifies and extracts the continuous images of the reflection angle and azimuth on the imaging gathers within the local spatial range, and then performs weighted stacking to obtain a high-quality stacked profile. Summary of the invention

[0006] In view of the above-mentioned problems, the present invention is proposed.

[0007] Therefore, the technical problem solved by the present invention is: the existing technology has the problem of poor superimposed imaging quality caused by uneven illumination on the imaging gathers in exploration seismic. Due to the complex surface conditions and underground structures, irregular observation systems and inaccurate offset speed, uneven illumination occurs at different directions or angles on the imaging gathers.

[0008] To solve the above technical problems, the present invention provides the following technical solutions: an imaging gather stacking method based on lighting optimization, comprising: statistically analyzing the energy distribution characteristics on the imaging gathers, and eliminating abnormal traces based on energy relationships; constructing an effective lighting area model, outputting areas with better lighting, and correcting the imaging gathers based on energy constraints; constructing a new reference trace model, and outputting weighted coefficients based on a similarity coefficient method; and outputting imaging profiles based on weighted stacking.

[0009] As a preferred solution of the imaging gather stacking method based on illumination optimization described in the present invention, wherein: the energy distribution characteristics on the statistical imaging gathers include constructing an energy model of the entire gather and an energy distribution model of each point;

[0010] The energy model of the entire trace in the imaging gather is expressed as:

[0011]

[0012] Where I(z,i) is the input imaging gather; z is the vertical index, which is time t in the prestack time migration result and depth h in the prestack depth migration result; i is the index of the extended dimension of the imaging gather; the number of sampling points of z and i are M and N respectively;

[0013] The energy distribution model of each point is expressed as:

[0014]

[0015] Among them, z 0 and i 0 is the current calculated imaging point position, M z and N i are the local window sizes in the vertical and horizontal directions respectively.

[0016] As a preferred solution of the imaging gather stacking method based on illumination optimization described in the present invention, the exclusion of abnormal traces based on energy relationship includes screening of abnormal seismic traces, which is expressed as:

[0017]

[0018] in, and are the maximum energy value and the minimum energy value respectively;

[0019] After excluding the abnormal traces and re-ordering, the output imaging trace gather is expressed as:

[0020]

[0021] Among them, N 1 is the imaging gather I 1 The number of valid channels in (z,i), is the sorted imaging gather.

[0022] As a preferred solution of the imaging gather stacking method based on illumination optimization described in the present invention, wherein: the effective illumination area model is constructed, and the area with better illumination is output, including the imaging gather Overlay, build reference trace I ref (z), construct an effective lighting area model based on energy distribution, energy difference and similarity coefficient, and output the area with better lighting;

[0023] Reference Channel I ref (z) is expressed as:

[0024]

[0025] Among them, I ref (z) is the reference channel, is the imaging gather, N 1 is the imaging gather I 1 The number of valid channels in (z,i);

[0026] The effective lighting area model is expressed as:

[0027]

[0028] Among them, si(I 1 ,I ref ) is the imaging gather and reference channel I ref (z), en(I 1 ,I ref ) is the imaging gather and reference channel I ref (z) The energy difference between the two, EI 1 is the imaging gather I 1 (z,i) The energy of each channel, EI fil is the imaging gather I 1 (z,i) Single channel energy result after median and low-pass filtering, ε s ,ε e ,ε f is the preset threshold coefficient.

[0029] As a preferred solution of the imaging gather stacking method based on illumination optimization described in the present invention, wherein: the imaging gathers corrected based on energy constraint are included in the effective area, and an illumination correction weighting operator is designed based on energy constraint to correct the imaging gathers;

[0030] The imaging gathers are expressed as:

[0031]

[0032] Among them, I 2 (z,i) is the imaging gather after illumination optimization correction, w(z,i) is the weighting coefficient of illumination optimization calculation, which is determined according to the energy change of adjacent traces;

[0033] The weighted coefficient function is expressed as:

[0034]

[0035] EI 1 is the imaging gather I 1 (z,i) The energy of each channel, EI fil is the imaging gather I 1 (z,i) Single channel energy result after median and low-pass filtering.

[0036] As a preferred solution of the imaging gather stacking method based on illumination optimization described in the present invention, wherein: the construction of the new reference trace model, outputting the weighting coefficient based on the similarity coefficient method, comprises: 2 (z,i) superposition, output new reference track The similarity coefficient method and wavelet-based similarity feature output weighted coefficient w 2 (z,i);

[0037] New reference track It is expressed as:

[0038]

[0039] Among them, I 2 (z,i) is the imaging gather after illumination correction, N 1 is the imaging gather I 1 The number of valid channels in (z,i);

[0040] Weighting coefficient w 2 (z,i) is expressed as:

[0041] w 2 (z,i)=r 1 r 2

[0042]

[0043] Among them, r 1 and r 2 They are min||I 2 -r 1 I ref || 2 and min||I ref -r 2 I 2 || 2 The solution, is the new reference channel, I 2 (z,i) is the imaging gather after illumination correction.

[0044] As a preferred solution of the imaging gather stacking method based on illumination optimization described in the present invention, wherein: the outputting of the imaging section based on weighted stacking includes outputting the final imaging section based on weighted stacking;

[0045] The imaging section model is expressed as:

[0046]

[0047] in, is the normalization coefficient, w 2 (z,i) is the weighting coefficient calculated using the local similarity coefficient method.

[0048] Another object of the present invention is to provide an imaging gather stacking system based on illumination optimization, which can extract effective illumination from the imaging gathers for weighted stacking by designing an optimal illumination operator, thereby improving imaging quality.

[0049] As a preferred solution of the imaging gather stacking system based on illumination optimization described in the present invention, it includes: an initialization module, an energy distribution statistics module, an abnormal trace exclusion module, an illumination area screening module, a correction imaging gather module, and an imaging profile module.

[0050] A computer device includes a memory and a processor, wherein the memory stores a computer program, and is characterized in that the processor executes the computer program to implement a step of an imaging gather stacking method based on illumination optimization.

[0051] A computer-readable storage medium having a computer program stored thereon, characterized in that when the computer program is executed by a processor, the steps of an imaging gather stacking method based on illumination optimization are implemented.

[0052] Beneficial effects of the present invention: The imaging gather stacking method based on illumination optimization provided by the present invention realizes denoising of imaging gathers, and can also correct energy anomalies of imaging gather stacking. At the same time, the present invention can balance imaging profiles and realize amplitude-preserving stacking. Secondly, the present invention can be applied not only to time domain imaging gathers, but also to depth domain imaging gathers. In addition, surface offset gathers, angle gathers, dip gathers, and gathers indexed by shot numbers can all be stacked using the present invention to improve the quality of offset imaging. The present invention achieves better effects in both denoising of imaging gathers and imaging quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0054] Figure 1 An overall flow chart of an imaging gather stacking method based on illumination optimization provided in the first embodiment of the present invention;

[0055] Figure 2 A flowchart of an imaging gather stacking method based on illumination optimization provided by the first embodiment of the present invention;

[0056] Figure 3 An original imaging gather map based on theoretical model testing of an imaging gather stacking method based on illumination optimization provided in the second embodiment of the present invention;

[0057] Figure 4 A conventional stacking result diagram based on theoretical data testing of an imaging gather stacking method based on illumination optimization provided in the second embodiment of the present invention;

[0058] Figure 5 An imaging gather stacking result diagram based on illumination optimization of an imaging gather stacking method based on illumination optimization provided by the second embodiment of the present invention;

[0059] Figure 6 A conventional stacking result diagram of an imaging gather stacking method based on illumination optimization provided in the second embodiment of the present invention;

[0060] Figure 7 A result diagram of imaging gather stacking based on illumination optimization provided by a second embodiment of the present invention;

[0061] Figure 8A conventional stacking result diagram of an imaging gather stacking method based on illumination optimization provided in the second embodiment of the present invention;

[0062] Fig. 9 A result diagram of imaging gather stacking based on illumination optimization provided by a second embodiment of the present invention;

[0063] Fig.10 An overall flow chart of an imaging gather stacking system based on illumination optimization provided in the third embodiment of the present invention. DETAILED DESCRIPTION

[0064] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0065] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0066] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0067] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0068] At the same time, in the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "upper, lower, inner and outer" are based on the directions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the present invention. In addition, the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0069] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0070] Example 1

[0071] Reference Figure 1-2 , which is an embodiment of the present invention, provides an imaging gather stacking method based on illumination optimization, comprising:

[0072] S1: Input the migration imaging gathers and count the energy distribution characteristics on the imaging gathers.

[0073] Furthermore, the imaging gathers may be surface offset gathers in the pre-stack depth domain, angle domain gathers in the pre-stack depth domain, inclination domain gathers in the pre-stack depth domain, and common shot index gathers in the pre-stack depth domain; or they may be surface offset gathers in the pre-stack time domain, angle domain gathers in the pre-stack time domain, inclination domain gathers in the pre-stack time domain, and common shot index gathers in the pre-stack time domain.

[0074] It should be noted that the energy distribution characteristics on the statistical imaging gathers are used to calculate the energy of the entire trace and the energy distribution of each point.

[0075] It should also be noted that the energy model of the entire imaging gather is expressed as:

[0076]

[0077] Where I(z,i) is the input imaging gather; z is the vertical index, which is time t in the prestack time migration result and depth h in the prestack depth migration result; i is the index of the extended dimension of the imaging gather; the number of sampling points of z and i are M and N respectively.

[0078] Furthermore, the energy distribution model of each point is expressed as:

[0079]

[0080] Among them, z 0 and i 0 is the current calculated imaging point position, M z and N i are the local window sizes in the vertical and horizontal directions respectively.

[0081] S2: Eliminate abnormal channels based on energy relationships.

[0082] Furthermore, according to the energy relationship, the abnormal seismic traces with too strong energy and too weak energy are filtered out respectively, which can be expressed as:

[0083]

[0084] in, and are the maximum energy value and the minimum energy value respectively.

[0085] It should be noted that, generally speaking, A larger value will be given. Then, after excluding the abnormal traces, they are reordered to obtain a new imaging trace set.

[0086] It should also be noted that the output imaging gathers are expressed as:

[0087]

[0088] Among them, N 1 is the imaging gather I 1 The number of valid channels in (z,i), is the sorted imaging gather.

[0089] S3: Correction of imaging gathers based on energy constraints.

[0090] Furthermore, the imaging gathers Superposition to form reference track I ref (z) is expressed as:

[0091]

[0092] Among them, I ref (z) is the reference channel, is the imaging gather, N 1 is the imaging gather I 1 The number of valid channels in (z,i).

[0093] It should be noted that the effective illumination area is determined based on energy distribution, energy difference and similarity coefficient.

[0094] The effective lighting area model is expressed as:

[0095]

[0096] Among them, si(I 1 ,I ref ) is the imaging gather and reference channel I ref (z), en(I 1 ,I ref ) is the imaging gather and reference channel I ref(z) The energy difference between the two, EI 1 is the imaging gather I 1 (z,i) The energy of each channel, EI fil is the imaging gather I 1 (z,i) Single channel energy result after median and low-pass filtering, ε s ,ε e ,ε f is the preset threshold coefficient.

[0097] It should also be noted that, through the above processing, the area with better lighting can be effectively identified and separated from the area with poor lighting.

[0098]

[0099] Where Ω is the lighting area.

[0100] S4: Construct a new reference channel model and output weighting coefficients based on the similarity coefficient method.

[0101] Furthermore, the illumination-dependent weighted operator is calculated. In the effective area, the illumination correction weighted operator is designed by energy constraint to correct the imaging gathers.

[0102] The imaging gathers are expressed as:

[0103]

[0104] Among them, I 2 (z,i) is the imaging gather after illumination optimization correction, w(z,i) is the weighting coefficient of illumination optimization calculation, which is determined according to the energy change of adjacent traces;

[0105] It should be noted that the weighting coefficient function is expressed as:

[0106]

[0107] EI 1 is the imaging gather I 1 (z,i) The energy of each channel, EI fil is the imaging gather I 1 (z,i) Single channel energy result after median and low-pass filtering.

[0108] S5: Similarity coefficient weighted operator calculation.

[0109] Furthermore, the illumination-corrected imaging gather I 2 (z,i) superimposed to form a new reference track New reference track It is expressed as:

[0110]

[0111] Among them, I 2 (z,i) is the imaging gather after illumination correction, N 1 is the imaging gather I 1 The number of valid channels in (z,i);

[0112] It should be noted that the similarity coefficient method is used to calculate the weighting coefficient w according to the similarity characteristics of the wavelet. 2 (z,i), expressed as:

[0113] w 2 (z,i)=r 1 r 2

[0114]

[0115] Among them, r 1 and r 2 They are min||I 2 -r 1 I ref || 2 and min||I ref -r 2 I 2 || 2 The solution, is the new reference channel, I 2 (z,i) is the imaging gather after illumination correction.

[0116] S6: Weighted stacking, outputting the final imaging section.

[0117] Furthermore, the imaging section model is expressed as:

[0118]

[0119] in, is the normalization coefficient, w 2 (z,i) is the weighting coefficient calculated using the local similarity coefficient method.

[0120] It should be noted that the imaging gathers after illumination correction are stacked according to the weighting coefficient to obtain the final imaging profile, and obtain more accurate and clear imaging results. The imaging gather stacking method based on illumination optimization can improve the imaging quality and highlight the areas with better illumination by statistical energy distribution, exclusion of abnormal traces, correction and weighting processing, so as to obtain more reliable and accurate seismic imaging results.

[0121] Example 2

[0122] Reference Figure 3-9, which is an embodiment of the present invention, provides an imaging gather stacking method based on illumination optimization. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through theoretical model test tests.

[0123] Theoretical model experiments were used to test the effectiveness of this method. Figure 3 is a synthetic imaging gather. There are four reflection layers in the imaging gather at this point. In order to simulate the inaccurate migration velocity, complex terrain and underground structure, random time difference disturbance, wavelet stretching and Gaussian noise are added to the imaging gather. Then, the abnormal amplitude of the deep two layers is designed as uneven illumination. The conventional method and the proposed method are used for superposition respectively. Figure 4 The results of conventional methods are superimposed. Figure 5 The weighted stacking result of this method. The result of the conventional stacking method is very poor. The waveform of the reflection event is distorted, and the amplitude in the deep two layers is different from that in the shallow layer. The proposed method can effectively correct the difference in waveform and amplitude, and the amplitude relationship of the deep layer is consistent with that of the shallow layer.

[0124] Next, actual data is used to test the application effect of the method. It should be noted that this specific embodiment is only for better illustrating the present invention and does not limit the application of the present invention. Figure 6 and Figure 8 is the conventional superposition result. Figure 7 and Fig. 9 This is the stacking result of this method. By comparison, it can be found that this method can effectively eliminate random noise and offset artifacts, the amplitude on the stacked seismic section is well balanced and adjusted, and the resolution is effectively improved, which can confirm the effectiveness of this method.

[0125] Example 3

[0126] Reference Fig.10 , which is an embodiment of the present invention, provides an imaging gather stacking system based on lighting optimization, including: an initialization module, an energy distribution statistics module, an abnormal channel exclusion module, an illumination area screening module, a correction imaging gather module, and an imaging profile module.

[0127] The initialization module is used to input the offset imaging gathers, the energy distribution statistics module is used to count the energy distribution characteristics on the imaging gathers, including the energy of the entire trace and the energy distribution of each point, the abnormal trace exclusion module is used to exclude abnormal seismic traces with too strong or too weak energy, the illumination area screening module is used to stack the imaging gathers, and determine the effective illumination area based on energy distribution, energy difference and similarity coefficient, the correction imaging gather module is used to design the illumination correction weighting operator through energy constraints, and correct the imaging gathers, the imaging profile module is used to stack the imaging gathers after illumination correction, output the weighting coefficient through the similarity coefficient method and the similarity characteristics of the wavelet, and output the final imaging profile based on weighted superposition.

[0128] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0129] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0130] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering, or processing in another suitable manner as necessary, and then stored in a computer memory.

[0131] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc. It should be noted that the above embodiments are only used to illustrate the technical solution of the present invention and are not limited. Although the present invention is described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention, which should be included in the scope of the claims of the present invention.

[0132] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. An imaging gather stacking method based on illumination optimization, characterized in that: include: Statistical analysis of energy distribution characteristics on imaging gathers, and exclusion of abnormal traces based on energy relationships; Construct an effective illumination area model, output the area with better illumination, and correct the imaging gathers based on energy constraints; Construct a new reference track model and output weighting coefficients based on the similarity coefficient method; Output imaging sections based on weighted stacking.

2. The imaging gather stacking method based on illumination optimization according to claim 1, characterized in that: The energy distribution characteristics on the statistical imaging gathers include constructing an energy model for the entire trace and an energy distribution model for each point; The energy model of the entire trace in the imaging gather is expressed as: Where I(z,i) is the input imaging gather; z is the vertical index, which is time t in the prestack time migration result and depth h in the prestack depth migration result; i is the index of the extended dimension of the imaging gather; the number of sampling points of z and i are M and N respectively; The energy distribution model of each point is expressed as: Among them, z0 and i0 are the current calculated imaging point positions, M z and N i are the local window sizes in the vertical and horizontal directions respectively.

3. The imaging gather stacking method based on illumination optimization according to claim 1, characterized in that: The elimination of abnormal traces based on energy relationship includes screening of abnormal seismic traces, which is expressed as: in, and are the maximum energy value and the minimum energy value respectively; After excluding the abnormal traces and re-ordering, the output imaging trace gather is expressed as: Where N1 is the number of effective channels in the imaging gather I1(z,i), is the sorted imaging gather.

4. The imaging gather stacking method based on illumination optimization according to claim 1, characterized in that: The effective illumination area model is constructed, and the area with better illumination is output, including the imaging gathers Overlay, build reference trace I ref (z), construct an effective lighting area model based on energy distribution, energy difference and similarity coefficient, and output the area with better lighting; Reference Channel I ref (z) is expressed as: Among them, I ref (z) is the reference channel, is the imaging gather, N1 is the number of valid traces in the imaging gather I1(z,i); The effective lighting area model is expressed as: Among them, si(I1,I ref ) is the imaging gather and reference channel I ref (z), en(I1,I ref ) is the imaging gather and reference channel I ref (z) is the energy difference between the two, EI1 is the energy of each trace of the imaging gather I1(z,i), EI fil is the single channel energy result of the imaging gather I1(z,i) after median and low-pass filtering, ε s ,ε e ,ε f is the preset threshold coefficient.

5. The imaging gather stacking method based on illumination optimization according to claim 1, characterized in that: The energy-constrained correction imaging gathers include designing an illumination correction weighting operator based on the energy constraint in the effective area to correct the imaging gathers; The imaging gathers are expressed as: Where I2(z,i) is the imaging gather after illumination optimization correction, w(z,i) is the weighting coefficient of illumination optimization calculation, which is determined according to the energy change of adjacent traces; The weighted coefficient function is expressed as: EI1 is the energy of each trace of the imaging gather I1(z,i), EI fil It is the single-channel energy result of the imaging gather I1(z,i) after median and low-pass filtering.

6. The imaging gather stacking method based on illumination optimization according to claim 1, characterized in that: The method of constructing a new reference track model and outputting weighted coefficients based on the similarity coefficient method includes superimposing the illumination-corrected imaging track gathers I2(z,i) to output a new reference track. Output weighted coefficient w2(z,i) based on similarity coefficient method and similarity characteristics of wavelet; New reference track It is expressed as: Where I2(z,i) is the imaging gather after illumination correction, N1 is the number of valid channels in the imaging gather I1(z,i); The weighting coefficient w2(z,i) is expressed as: w2(z,i)=r1r2 Among them, r1 and r2 are min||I2-r1I ref || 2 and min||I ref -r2I2|| 2 The solution, is the new reference trace, and I2(z,i) is the imaging trace after illumination correction.

7. The imaging gather stacking method based on illumination optimization according to claim 1, characterized in that: Outputting the imaging section based on weighted stacking includes outputting the final imaging section based on weighted stacking; The imaging section model is expressed as: in, is the normalization coefficient, and w2(z,i) is the weighting coefficient calculated using the local similarity coefficient method.

8. A system using the imaging gather stacking method based on illumination optimization as claimed in any one of claims 1 to 7, characterized in that: It includes initialization module, energy distribution statistics module, abnormal trace exclusion module, lighting area screening module, imaging gather correction module and imaging profile module; The initialization module is used to input migration imaging gathers; The energy distribution statistics module is used to count the energy distribution characteristics on the imaging gather, including the energy of the entire gather and the energy distribution of each point; The abnormal trace exclusion module is used to exclude abnormal seismic traces with excessive energy or too weak energy; The illumination area screening module is used to stack imaging gathers and determine the effective illumination area based on energy distribution, energy difference and similarity coefficient; The correction imaging gather module is used to design an illumination correction weighting operator through energy constraints to correct the imaging gather; The imaging profile module is used to stack the imaging gathers after illumination correction, output weighted coefficients through the similarity coefficient method and similarity characteristics of the wavelet, and output the final imaging profile based on weighted stacking.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of an imaging gather stacking method based on illumination optimization as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of an imaging gather stacking method based on illumination optimization according to any one of claims 1 to 7 are implemented.

Images