Free-surface multiple prediction method and apparatus for converted wave, and device and medium

Abstract

The present invention belongs to the field of seismic data processing. Provided are a free-surface multiple prediction method and apparatus for a converted wave, and a device and a medium. The method comprises: acquiring a seismic signal, and extracting a longitudinal-wave component downgoing-wave record from the seismic signal; on the basis of Kirchhoff migration and the longitudinal-wave component downgoing-wave record, determining a downgoing-wave imaging data volume; on the basis of Kirchhoff demigration and the downgoing-wave imaging data volume, determining a longitudinal-wave component demigration seismic record, and using the longitudinal-wave component demigration seismic record as a free-surface multiple prediction factor; on the basis of the longitudinal-wave component demigration seismic record and a preset free-surface reflection coefficient, determining a free-surface factor; and on the basis of the free-surface factor and the free-surface multiple prediction factor, constructing a free-surface multiple prediction model. By means of the present invention, all free-surface multiple components in converted-wave data can be accurately predicted, and thus the elimination precision of multiples can be further improved.

Description

Method, device, equipment and medium for predicting multiple waves of converted wave free interface Technical Field

[0001] The present invention relates to the field of seismic data processing, and in particular to a method for predicting multiple waves of a converted wave free interface, a device for predicting multiple waves of a converted wave free interface, an electronic device, and a computer-readable storage medium. Background Art

[0002] To obtain high-quality marine seismic data with wide azimuth, high coverage, and small bins, ocean bottom node (OBN) seismic acquisition has rapidly developed in my country's offshore seismic exploration. Because the sea surface can be approximated as a free interface (with a reflection coefficient close to -1), in the converted wave components X and Y obtained by OBN exploration, the P-wave energy reflected down from the sea surface, upon reflection back from the subsurface interface, generates free-interface multiples of the converted wave type, with amplitudes significantly greater than those of interlayer multiples (downward reflections at the seabed or its underlying interface). Given that the primary seismic signal used in oil and gas exploration is primary reflection, the prediction and suppression of free-interface multiples in the converted wave components X and Y is a key issue in OBN data processing.

[0003] In recent years, the free-interface multiple attenuation (SRME) method, based on feedback loop theory, has made significant progress. It effectively suppresses multiple components in seismic records with virtually no prior information. It has become one of the preferred methods for processing two-dimensional seismic data and has been extended to suppress multiples in three-dimensional conventional streamer data. However, this method faces significant challenges in processing OBN converted-wave data. Because the seismic signal receiving equipment is deployed on the seafloor, OBN acquisitions are unable to receive primary reflections from the seafloor (without illumination). Furthermore, the "few-channel, multiple-shot" observation system employed results in low and uneven coverage of shallow-to-medium depths, even missing reflections from some shallow strata. This severely limits the effectiveness of data-driven three-dimensional SRME. The lack of reflections significantly impacts the prediction accuracy of multiples. Not only can multiples associated with the seafloor and shallow interfaces not be predicted, but significant spatial aliasing can also be generated, compromising the effectiveness of multiple rejection in the converted-wave component of OBN data.

[0004] Summary of the Invention

[0005] The purpose of the present invention is to provide a method, device, equipment and medium for predicting multiple waves of a converted wave free interface, so as to solve the problem that the existing methods cannot accurately predict multiple waves.

[0006] To achieve the above objectives, the present invention provides, in one aspect, a method for predicting multiples of a converted wave free interface, the method comprising:

[0007] Acquire seismic signals and extract down-going wave records of the longitudinal wave component of the seismic signals;

[0008] Based on Kirchhoff migration, the downgoing wave imaging data volume is determined according to the downgoing wave record of the longitudinal wave component;

[0009] Based on Kirchhoff demigration, the P-wave component demigration seismic records are determined according to the down-going wave imaging data volume, and the P-wave component demigration seismic records are used as the free interface multiple wave prediction factors.

[0010] Determine the free interface factor based on the P-wave component back-migration seismic record and the preset free interface reflection coefficient;

[0011] Based on the free interface factor and the free interface multiple wave prediction factor, a free interface multiple wave prediction model is constructed. The free interface multiple wave prediction model is used to output corresponding multiple wave records according to input converted wave component data.

[0012] Preferably, the method further comprises:

[0013] Acquiring converted wave component data to be predicted;

[0014] The converted wave component data to be predicted is input into the free interface multiple wave prediction model to obtain the multiple wave record.

[0015] Preferably, extracting the downgoing wave record of the longitudinal wave component of the seismic signal includes:

[0016] Extract P component data and Z component data from seismic signals;

[0017] Determine the matching factor based on the P component data and the Z component data;

[0018] The downgoing wave record of the longitudinal wave component is determined based on the P component data, Z component data and matching factors.

[0019] Preferably, based on Kirchhoff migration and according to the downgoing wave record of the longitudinal wave component, determining the downgoing wave imaging data volume includes:

[0020] Based on Kirchhoff migration, a computational model for downlink wave imaging data volume is constructed;

[0021] The downgoing wave record of the longitudinal wave component is input into the downgoing wave imaging data volume calculation model to obtain the downgoing wave imaging data volume.

[0022] Preferably, determining the P-wave component demigration seismic record based on Kirchhoff demigration and the down-going wave imaging data volume comprises:

[0023] Based on Kirchhoff demigration, a demigration seismic record calculation model is constructed;

[0024] The downlink wave imaging data volume is input into the demigration seismic record calculation model to obtain the P-wave component demigration seismic record.

[0025] Preferably, determining the free interface factor based on the P-wave component demigration seismic record and the preset free interface reflection coefficient comprises:

[0026] Extract seismic wavelets from the P-wave component de-migration seismic records;

[0027] Transform the seismic wavelet from the time domain to the frequency domain to obtain the frequency domain seismic wavelet;

[0028] Phase correction is performed based on the frequency-domain seismic wavelet and the preset reflection coefficient of the free interface to obtain the free interface factor.

[0029] Preferably, the free interface multiple wave prediction model is expressed as:

[0030] Where M X (x s ,y s ,x r ,y r ,f) is the free interface multiple wave record of the predicted converted wave component data, X(x s ,y s ,x k ,y k ,f) is the input converted wave component data, A(f) is the free interface factor, H(x k ,y k ,x r ,y r ,f) is the free interface multiple wave prediction factor, x s with y s Represents the spatial coordinates of the shot point, x r with y r represents the spatial coordinates of the receiving point, f is the frequency, x k with y k Indicates the spatial coordinates of the receiving point in wave field X and the shot point in wave field H involved in the summation operation.

[0031] In another aspect, the present invention further provides a device for predicting multiples of a converted-wave free interface, for implementing the above-mentioned method for predicting multiples of a converted-wave free interface. The device comprises:

[0032] Downward wave extraction module, used to obtain seismic signals and extract the downward wave record of the longitudinal wave component of the seismic signal;

[0033] A longitudinal wave migration processing module is used to determine a downgoing wave imaging data volume based on the downgoing wave record of the longitudinal wave component based on Kirchhoff migration;

[0034] The first factor determination module is used to determine the P-wave component de-migration seismic record based on the Kirchhoff de-migration and the down-going wave imaging data volume, and use the P-wave component de-migration seismic record as the free interface multiple wave prediction factor;

[0035] A second factor determination module is used to determine the free interface factor based on the P-wave component de-migration seismic record and the preset reflection coefficient of the free interface;

[0036] The prediction model building module is used to build a free interface multiple wave prediction model based on the free interface factor and the free interface multiple wave prediction factor.

[0037] On the other hand, the present invention also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned method for predicting multiple waves of a converted wave free interface when executing the computer program.

[0038] On the other hand, the present invention further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned method for predicting multiple waves of a converted wave free interface.

[0039] Through the above technical solution, the present invention has at least the following technical effects:

[0040] The present invention can accurately predict all free interface multiple wave components in converted wave data, thereby further improving the precision of eliminating multiple waves.

[0041] Other features and advantages of the present invention will be described in detail in the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The accompanying drawings are used to provide a further understanding of the embodiments of the present invention and constitute a part of the specification. Together with the following detailed description, they are used to explain the embodiments of the present invention, but do not constitute a limitation of the embodiments of the present invention. In the accompanying drawings:

[0043] The accompanying drawings are used to provide a further understanding of the embodiments of the present invention and constitute a part of the specification. Together with the following detailed description, they are used to explain the embodiments of the present invention, but do not constitute a limitation of the embodiments of the present invention. In the accompanying drawings:

[0044] FIG1 is a flow chart of a method for predicting multiples of a converted wave free interface provided by one embodiment of the present invention;

[0045] FIG2 is a ray tracing process of a “straight ray” model for prestack time mirror migration of down-going P-wave component records provided by one embodiment of the present invention;

[0046] FIG3 is a ray tracing process of Kirchhoff demigration of a longitudinal wave component in the time domain provided by one embodiment of the present invention;

[0047] FIG4 is an example of a common receiving point gather of P component data provided by one embodiment of the present invention;

[0048] FIG5 is an example of a common receiving point gather of downlink waves of extracted longitudinal wave components provided by one embodiment of the present invention;

[0049] FIG6 is a downlink imaging data volume of a longitudinal wave component provided by one embodiment of the present invention;

[0050] FIG7 is an example of a P-wave component demigration seismic record constructed by time-domain Kirchhoff demigration according to an embodiment of the present invention;

[0051] FIG8 is an example of an original converted wave common receiving point gather provided by one embodiment of the present invention;

[0052] FIG9 is an example of a predicted converted wave free interface multiple record provided by one embodiment of the present invention;

[0053] FIG10 is a block diagram of a device for predicting multiple waves of a converted wave free interface according to an embodiment of the present invention. DETAILED DESCRIPTION

[0054] The following describes the specific implementation of the embodiment of the present invention in detail with reference to the accompanying drawings. It should be understood that the specific implementation described herein is only used to illustrate and explain the embodiment of the present invention and is not used to limit the embodiment of the present invention.

[0055] Unless otherwise defined, all technical and scientific terms used herein have the same meanings as commonly understood by those skilled in the art to which the present invention belongs; the terms used herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention; the terms "including" and "having" and any variations thereof in the specification and claims of the present invention and the above-mentioned drawings are intended to cover non-exclusive inclusions.

[0056] In the description of the embodiments of the present invention, technical terms such as "first" and "second" are used solely to distinguish between different objects and should not be understood to indicate or imply relative importance or to implicitly specify the quantity, specific order, or primary and secondary relationship of the technical features indicated. In the description of the embodiments of the present invention, "plurality" means more than two, unless otherwise specifically defined.

[0057] References herein to "embodiments" mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present invention. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute a separate or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0058] Example 1

[0059] It should be noted that Sea Area A is a shallow water area with a relatively flat seabed and a water depth of 50 to 60 meters. An air gun source towed at the stern of a ship continuously excites seismic waves in a cruising manner, and seismic signals are received using Ocean Bottom Nodes (OBNs). During the seismic acquisition process, 6 receiving lines with a total of 4020 nodes were first laid out on the seabed. Seismic signals were excited in sequence through 24 shot lines, and the spacing between the receiving lines and the shot lines was 200 meters and 50 meters, respectively, and the directions of the two were parallel to each other. The sampling interval and record length of the seismic data were 0.004 seconds and 6 seconds, respectively. Since both the sea surface and the seabed are strong wave impedance interfaces, a large number of free interface multiple waves with large amplitudes exist in the acquired converted wave data, which seriously affects the imaging quality of the underground structure and will mislead subsequent geological interpretation and analysis.

[0060] FIG1 is a flow chart of a method for predicting multiples of a converted-wave free interface provided by one embodiment of the present invention. As shown in FIG1 , this embodiment provides a method for predicting multiples of a converted-wave free interface, the method comprising:

[0061] Step S101: Acquire a seismic signal and extract the downgoing wave record of the longitudinal wave component of the seismic signal.

[0062] In this embodiment, extracting the downgoing wave record of the longitudinal wave component of the seismic signal includes:

[0063] Step a01: extracting P component data and Z component data from the seismic signal;

[0064] Step a02: Determine the matching factor based on the P component data and the Z component data;

[0065] Step a03: Determine the downgoing wave record of the longitudinal wave component based on the P component data, the Z component data and the matching factor.

[0066] During OBN exploration, pressure and velocity geophones are placed directly at the same location on the seafloor and receive seismic signals simultaneously. P-component data and Z-component data are obtained, respectively. In the P-component and Z-component data, the polarity of the upgoing wave responses is the same, while the polarity of the downgoing wave responses is opposite. Therefore, by taking the difference between the two, the downgoing wave can be extracted and the upgoing wave suppressed.

[0067] Since there is a significant difference in amplitude between the P component data and the Z component data, the least square filtering technique is required. For the adaptive subtraction process based on the L2 norm, the matching factor is determined by minimizing the sum of squared error energy e in the following formula: e=||pz*a||2; (1)

[0068] Where, vector p is the P component data, vector z is the Z component data, and * is the convolution operation. The matching factor a can be obtained by solving equation (1). When the length of the matching factor a is 1, the solution of the linear equation group can be avoided, and the calculation formula of the matching factor can be directly given.

[0069] Where a represents a matching factor of length 1, and the superscript “T” represents the transpose operation of the matrix.

[0070] Substituting the matching factor a into the following formula can realize the extraction of the downlink wave. The corresponding calculation formula is: d(i,t)=p(i,t)-a*z(i,t); (3)

[0071] Where d(i, t) represents the extracted downlink wave record of the longitudinal wave component, p(i, t) is the P component data, z(i, t) is the Z component data, i is the channel number of the seismic signal, and t is the travel time.

[0072] In this embodiment, FIG4 is a common receiving point gather of P component data. By performing adaptive P and Z subtraction processing of formula (2) and formula (3) simultaneously, the downlink wave record of the longitudinal wave component shown in FIG5 can be obtained.

[0073] Step S102: Based on Kirchhoff migration and the downgoing wave record of the longitudinal wave component, a downgoing wave imaging data volume is determined.

[0074] In this embodiment, based on Kirchhoff migration and according to the downgoing wave record of the longitudinal wave component, a downgoing wave imaging data volume is determined, including:

[0075] Step b01: constructing a downlink wave imaging data volume calculation model based on Kirchhoff migration;

[0076] Step b02: Input the downgoing wave record of the longitudinal wave component into the downgoing wave imaging data volume calculation model to obtain the downgoing wave imaging data volume.

[0077] Kirchhoff migration is the most commonly used migration imaging method in production. In the case of a migration velocity field, it can realize the process of generating seismic profiles using pre-stack seismic data.

[0078] The Kirchhoff shift can be expressed as an integral process in the following form:

[0079] Where I(η) represents the migration profile, η is the coordinate of the profile sample point, ξ is the coordinate of a shot-to-check pair (s, r); w m (ξ,η) is the weight factor of Kirchhoff integral migration, d(ξ,t) is the time domain seismic record; ds represents the integration bin, and τ(ξ,η) represents the sum of the travel times of the ray from the shot point to the imaging point and from the imaging point to the receiver point.

[0080] In order to realize the time domain mirror migration based on down-going waves, Kirchhoff prestack time migration in the shot gather domain is studied in detail. The shot-to-check pair ξ in formula (4) is replaced by the down-going wave recorded shot gather. The migration result is a data in the imaging gather. That is, the down-going wave imaging data volume calculation model is:

[0081] Where g i (η) is the downlink wave imaging data volume after the migration of the i-th shot record, d i (j, t) is the down-wave record shot gather of the longitudinal wave component in the time domain, i is the shot number, j is the trace number, J is the total number of traces, η is the coordinate of the profile sample point, w m (s i ,r j ,η) is the weight factor of Kirchhoff integral shift, ds is the integral surface element, τ(s i ,r j ,η) represents the sum of the travel time of the ray from the shot point to the imaging point and from the imaging point to the detector point, s i is the i-th shot point, r j is the jth detection point.

[0082] In order to image the downgoing wave (ghost wave reflected from the sea surface), the detection point on the seabed needs to be mirror-projected to a symmetrical position above the sea surface, as shown in Figure 3. j Projected above the sea surface r′ j , and then calculate the Kirchhoff weight factor and travel time based on the new receiver point position, so as to achieve the imaging of the seabed and underlying strata. In Figure 3, S(x k ,y k ) and G(x r ,y r ) represent the spatial coordinates of the shot point and the receiver point respectively.

[0083] The mirror Kirchhoff prestack time migration adopts the ray tracing process of the “straight ray” model (as shown in Figure 2). In Figure 2, S m Indicates the gun point, G n represents the detection point, so the weight factor W in formula (5) m (s i ,r′ j ,η) and travel time τ(s i ,r′ j ,η) is significantly simplified, and the two can be expressed as:

[0084] Where r′ j is the detection point r j projection, v(η) represents the seismic wave velocity, v0(η) is the migration velocity of the primary wave, cosθ is the tilt factor, l0 is the distance from the shot point to the imaging point, l is the distance from the imaging point to the shot point, r0 represents the straight-line distance from the shot point to the reflection point, and r represents the straight-line distance from the reflection point to the receiver point.

[0085] Taking the down-going wave record d(i, j) of the P-wave component shown in Fig. 5 as input, the horizontal coordinates in Fig. 4 and Fig. 5 are the shot number (Shot No.), and the vertical coordinates are the two-way travel time (TWT) of the seismic wave, the shot domain Kirchhoff prestack time mirror migration processing is performed according to formulas (4), (5), and (6), and the down-going wave imaging data volume of the P-wave component shown in Fig. 6 can be obtained.

[0086] Step S103: Based on Kirchhoff demigration, the P-wave component demigration seismic record is determined according to the downlink wave imaging data volume, and the P-wave component demigration seismic record is used as a free interface multiple wave prediction factor.

[0087] In this embodiment, based on Kirchhoff demigration, the P-wave component demigration seismic record is determined according to the down-going wave imaging data volume, including:

[0088] Step c01: Based on Kirchhoff demigration, a demigration seismic record calculation model is constructed;

[0089] Step c02: Input the downlink wave imaging data volume into the demigration seismic record calculation model to obtain the longitudinal wave component demigration seismic record.

[0090] Taking the pre-stack time migration profile I(η) generated by formula (4) as input and introducing the “straight ray” model ray tracing process of pre-stack time migration, the time domain demigration seismic record calculation model can be expressed as:

[0091] In the formula, H(x k ,y k ,x r,y r ,t) is the de-migration record, i.e. the de-migration seismic record of the longitudinal wave component, x k with y k Indicates the spatial coordinates of the shot point for de-migration, x r with y r represents the spatial coordinates of the receiving point for demigration, η is the coordinates of the profile sample point, ds represents the integral bin; W H (η,x k ,y k ,x r ,y r ) is the weight factor of Kirchhoff demigration, t(η,x k ,y k ,x r ,y r ) represents the sum of the travel time of the ray from the shot point to point η and from point η to the detector point.

[0092] When predicting multiple waves for a data in a shot gather, x r with y r is a fixed value, and x k with y k is changing, so H(x k ,y k ,x r ,y r ,t) represents the common receiver gather record; it should be noted that the integral weight factor W in the demigration process H (η,x k ,y k ,x r ,y r ) is somewhat different from that in time migration imaging, and should be calculated using the more accurate Kirchhoff integrated diffraction superposition method (as shown in Figure 3).

[0093] where l0 is the propagation distance of the incident ray (the distance from the shot point to the imaging point), l is the propagation distance of the diffracted ray (the distance from the imaging point to the shot point), θ0 and θ are the angles between l0, l, and the bin normal vector n, respectively; and v(η) represents the seismic wave velocity.

[0094] The downlink wave imaging data volume of the P-wave component shown in Figure 6 is used as input. The horizontal distance in Figure 6 is the horizontal position (horizontal distance (km)), and the vertical distance is the two-way travel time (TWT) of the seismic wave. The P-wave component de-migration seismic record shown in Figure 7 is constructed based on the time-domain Kirchhoff de-migration of formulas (7) and (8). The horizontal distance in Figures 7 to 9 is the detection point number (Trace No.), and the vertical distance is the two-way travel time (TWT) of the seismic wave. The P-wave component de-migration seismic record is used as a free interface multiple wave prediction factor to participate in the free interface multiple wave prediction of the OBN data conversion wave component.

[0095] Step S104: Determine the free interface factor based on the P-wave component demigration seismic record and the preset free interface reflection coefficient.

[0096] In this embodiment, the free interface factor is determined based on the P-wave component demigration seismic record and the preset free interface reflection coefficient, including:

[0097] Step d01: extracting seismic wavelets from the de-migration seismic records of the longitudinal wave component;

[0098] Step d02: transform the seismic wavelet from the time domain to the frequency domain to obtain the frequency domain seismic wavelet;

[0099] Step d03: Perform phase correction based on the frequency-domain seismic wavelet and the preset reflection coefficient of the free interface to obtain the free interface factor.

[0100] In this embodiment, the calculation expression of the free interface factor is: A(f) = [W(f)] -1 (-1) = -[W(f)] -1 ; (9)

[0101] Where A(f) is the free interface factor, (-1) is the preset free interface reflection coefficient (the reflection coefficient of the free interface (sea surface) in offshore seismic exploration), W(f) is the Fourier transform of the seismic wavelet w(t) extracted from the de-migration seismic record based on the P-wave component, and f represents the frequency.

[0102] Step S105: constructing a free interface multiple wave prediction model based on the free interface factor and the free interface multiple wave prediction factor, wherein the free interface multiple wave prediction model is used to output corresponding multiple wave records according to the input converted wave component data.

[0103] In this embodiment, the converted wave component data separated by wavefield and the P-wave component de-migrated seismic records constructed by time-domain Kirchhoff de-migration are used as prediction factors for free interface multiples prediction. Both are transformed into the frequency domain and substituted into the three-dimensional free interface multiples prediction equation. The free interface multiples prediction process of the converted wave component is:

[0104] Where M X (x s ,y s ,x r ,y r ,f) is the free interface multiple wave record of the predicted converted wave component data, X(x s ,y s ,x k ,y k ,f) is the input conversion wave component data, H(x k ,y k ,x r ,y r ,f) is the free interface multiple wave prediction factor, x s with y s Represents the spatial coordinates of the shot point, x r with y r represents the spatial coordinates of the receiving point, f is the frequency, x k with y k Indicates the spatial coordinates of the receiving point in wave field X and the shot point in wave field H involved in the summation operation.

[0105] By introducing the free interface factor A(f) calculated by equation (9), equation (10) can further obtain the free interface multiple wave prediction model, which is:

[0106] Equation (11) is a multiple wave prediction model that introduces the free interface multiple wave prediction factor and the free interface factor. This process is carried out in the frequency domain. After obtaining the multiple wave records based on Equation (11), the multiple waves in the converted wave component data X can be eliminated by the adaptive attenuation method.

[0107] As a further optimization of this embodiment, the method further includes:

[0108] Step e01: obtaining the converted wave component data to be predicted;

[0109] Step e02: Input the converted wave component data to be predicted into the free interface multiple wave prediction model to obtain multiple wave records.

[0110] Taking the converted wave component data shown in Figure 8 as input (as the converted wave component data to be predicted), the free interface multiple wave prediction of the converted wave component of the OBN data is realized based on formula (11), and the multiple wave record shown in Figure 9 is obtained, which contains rich multiple wave information. By comparison, it can be seen that the travel times of the multiple wave phase axes in the two records shown in Figures 8 and 9 are basically consistent, which proves the effectiveness of the converted wave free interface multiple wave prediction method.

[0111] The prediction method of this embodiment achieves three-dimensional free-interface multiple prediction for converted-wave components of OBN data, effectively resolving the inability of conventional streamer SRME methods to apply to such data. This method significantly improves the multiple suppression effectiveness of converted-wave component data from OBN data. Compared with multiple prediction techniques based on wavefield continuation, this method offers significant accuracy advantages. This is because the former only predicts a subset of free-interface multiples—ghost waves and seafloor multiples (full-range multiples on the seafloor and slightly bent multiples related to the seafloor). While this method predicts the entire free-interface multiple component in converted-wave data, it significantly improves the accuracy of multiple suppression.

[0112] Example 2

[0113] FIG10 is a block diagram of a device for predicting multiples at a converted-wave free interface according to an embodiment of the present invention. As shown in FIG10 , based on the same inventive concept as in Example 1, this embodiment further provides a device for predicting multiples at a converted-wave free interface. The device is used to implement the method for predicting multiples at a converted-wave free interface according to Example 1. The device includes:

[0114] Downward wave extraction module, used to obtain seismic signals and extract the downward wave record of the longitudinal wave component of the seismic signal;

[0115] A longitudinal wave migration processing module is used to determine a downgoing wave imaging data volume based on the downgoing wave record of the longitudinal wave component based on Kirchhoff migration;

[0116] The first factor determination module is used to determine the P-wave component de-migration seismic record based on the Kirchhoff de-migration and the down-going wave imaging data volume, and use the P-wave component de-migration seismic record as the free interface multiple wave prediction factor;

[0117] A second factor determination module is used to determine the free interface factor based on the P-wave component de-migration seismic record and the preset reflection coefficient of the free interface;

[0118] The prediction model building module is used to build a free interface multiple wave prediction model based on the free interface factor and the free interface multiple wave prediction factor.

[0119] Based on the same inventive concept as in the first embodiment, this embodiment further provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned method for predicting multiple waves of a converted wave free interface when executing the computer program.

[0120] Based on the same inventive concept as the first embodiment, this embodiment further provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the above-mentioned method for predicting multiple waves of a converted-wave free interface.

[0121] The prediction method of this embodiment achieves three-dimensional free-interface multiple prediction for converted-wave components of OBN data, effectively resolving the inability of conventional streamer SRME methods to apply to such data. This method significantly improves the multiple suppression effectiveness of converted-wave component data from OBN data. Compared with multiple prediction techniques based on wavefield continuation, this method offers significant accuracy advantages. This is because the former only predicts a subset of free-interface multiples—ghost waves and seafloor multiples (full-range multiples on the seafloor and slightly bent multiples related to the seafloor). While this method predicts the entire free-interface multiple component in converted-wave data, it significantly improves the accuracy of multiple suppression.

[0122] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take 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.) containing computer-usable program code.

[0123] The present invention is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of 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.

[0124] 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.

[0125] 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.

[0126] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0127] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0128] Computer-readable media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0129] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0130] The above are merely embodiments of the present invention and are not intended to limit the present invention. It will be apparent to those skilled in the art that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention are intended to be included within the scope of the claims of the present invention.

Claims

1. A method for predicting multiple waves of a converted wave free interface, characterized in that: The method comprises: Acquire seismic signals and extract down-going wave records of longitudinal wave components of seismic signals; Based on Kirchhoff migration, the downgoing wave imaging data volume is determined according to the downgoing wave record of the longitudinal wave component; Based on Kirchhoff de-migration, the P-wave component de-migration seismic record is determined according to the down-going wave imaging data volume, and the P-wave component de-migration seismic record is used as the free interface multiple wave prediction factor; Determine the free interface factor based on the P-wave component back-migration seismic record and the preset reflection coefficient of the free interface; Based on the free interface factor and the free interface multiple wave prediction factor, a free interface multiple wave prediction model is constructed, and the free interface multiple wave prediction model is used to output corresponding multiple wave records according to the input converted wave component data.

2. The method according to claim 1, characterized in that The method further comprises: Acquiring converted wave component data to be predicted; The converted wave component data to be predicted is input into the free interface multiple wave prediction model to obtain the multiple wave records.

3. The method according to claim 1, characterized in that Extract the downgoing wave record of the longitudinal component of the seismic signal, including: Extract P component data and Z component data from seismic signals; Determine a matching factor according to the P component data and the Z component data; The downgoing wave record of the longitudinal wave component is determined based on the P component data, the Z component data and the matching factor.

4. The method according to claim 1, characterized in that: Based on Kirchhoff migration and the downgoing wave record of the longitudinal wave component, the downgoing wave imaging data volume is determined, including: Based on Kirchhoff migration, a computational model for downlink wave imaging data volume is constructed; The downgoing wave record of the longitudinal wave component is input into the downgoing wave imaging data volume calculation model to obtain the downgoing wave imaging data volume.

5. The method according to claim 1, characterized in that Based on Kirchhoff de-migration, the P-wave component de-migration seismic records are determined according to the down-going wave imaging data volume, including: Based on Kirchhoff de-migration, a calculation model for de-migration seismic records is constructed; The downlink wave imaging data volume is input into the anti-migration seismic record calculation model to obtain the longitudinal wave component anti-migration seismic record.

6. The method according to claim 1, characterized in that Based on the P-wave component back-migration seismic records and the preset reflection coefficient of the free interface, the free interface factor is determined, including: Extract seismic wavelets from the P-wave component back-migration seismic records; Transform the seismic wavelet from the time domain to the frequency domain to obtain the frequency domain seismic wavelet; Phase correction is performed based on the frequency-domain seismic wavelet and the preset reflection coefficient of the free interface to obtain the free interface factor.

7. The method according to claim 2, characterized in that The free interface multiple wave prediction model is expressed as: Where M X (x s ,y s ,x r ,y r ,f) is the free interface multiple wave record of the predicted converted wave component data, X(x s ,y s ,x k ,y k ,f) is the input converted wave component data, A(f) is the free interface factor, H(x k ,y k ,x r ,y r ,f) is the free interface multiple wave prediction factor, x s With y s represents the spatial coordinates of the shot point, x r With y r represents the spatial coordinates of the receiving point, f is the frequency, x k With y k Represents the spatial coordinates of the receiving point in wave field X and the shot point in H that participate in the summation operation.

8. A multiple wave prediction device for a converted wave free interface, used to implement the multiple wave prediction method for a converted wave free interface according to any one of claims 1 to 7, characterized in that: The device comprises: A down-going wave extraction module is used to obtain seismic signals and extract down-going wave records of longitudinal wave components of seismic signals; A longitudinal wave migration processing module is used to determine a downgoing wave imaging data volume based on the downgoing wave record of the longitudinal wave component based on Kirchhoff migration; The first factor determination module is used to determine the P-wave component de-migration seismic record based on Kirchhoff de-migration and the down-going wave imaging data volume, and use the P-wave component de-migration seismic record as a free interface multiple wave prediction factor; A second factor determination module is used to determine the free interface factor based on the P-wave component back-migration seismic record and the preset reflection coefficient of the free interface; The prediction model building module is used to build a free interface multiple wave prediction model based on a free interface factor and a free interface multiple wave prediction factor.

9. An electronic 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 for predicting multiple waves of a converted wave free interface according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method for predicting multiple waves of a converted wave free interface according to any one of claims 1 to 7 is implemented.

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