Near-surface velocity model construction method and device, electronic equipment and storage medium

Abstract

The application provides a near-surface velocity model construction method and device, electronic equipment and storage medium, and relates to the technical field of geophysical prospecting engineering. First, according to multi-dimensional seismic data, a full-depth velocity initial model is constructed, and a target observation system is obtained. Then, the first arrival waves of each wave field are fused to obtain fused first arrival waves of each wave field, and the full-depth velocity initial model is modified through well-ground joint variable weight first arrival tomographic inversion according to the contribution degree coefficients and depth weighting values of each wave field. Finally, the high-speed top interface of the modified full-depth velocity initial model is determined, the static correction amount is calculated, the accuracy of the modified full-depth velocity initial model is verified, and the target near-surface velocity model is output under the condition that the preset condition is met. The common midpoint stack profile obtained by the application has accurate structure and does not have the problem of long-wavelength static correction. Therefore, the near-surface velocity model constructed by the application has high precision.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of geophysical engineering, and in particular to a near-surface velocity model construction method and device, an electronic device and a storage medium. BACKGROUND

[0002] The Ordos Basin has great oil and gas exploration potential, but the third or fourth system loess layer is distributed on the surface, the surface relief is severe, and the near-surface structure is complex, thus facing a serious long-wavelength static correction problem. The primary consideration for solving the long-wavelength static correction problem is the accuracy of the near-surface velocity model. If the accuracy of the near-surface velocity model is not high, especially in complex loess tableland areas, the long-wavelength static correction problem is likely to occur, which reduces the imaging accuracy of seismic data and seriously affects subsequent oil and gas exploration and development work. Therefore, the long-wavelength static correction problem is solved by constructing an accurate near-surface velocity model in priority.

[0003] In related technologies, micro-logging or multi-information constraint first arrival tomographic inversion methods are commonly used. These methods are based on first arrival diving wave tomographic inversion, and the diving wave is not a real propagating ray, but only an isochronous tool in a mathematical sense, so the accuracy of the constructed near-surface velocity model is not high. SUMMARY

[0004] Embodiments of the present application provide a near-surface velocity model construction method and device, an electronic device and a storage medium, aiming to solve or partially solve the problem that manual string-sensing near-surface velocity model construction is time-consuming and laborious and has low accuracy.

[0005] To solve the above technical problems, the present application is implemented as follows:

[0006] In a first aspect, the embodiments of the present application provide a near-surface velocity model construction method, which comprises the following steps:

[0007] Constructing a full-depth velocity initial model according to multi-dimensional seismic data;

[0008] Fusing a ground acquisition observation system and a well-ground joint acquisition observation system to obtain a target observation system;

[0009] In the target observation system, data fusion is performed on the first arrival waves of each wave field to obtain fused first arrival waves of each wave field;

[0010] According to the fused first arrival waves of each wave field, the contribution degree coefficients of each wave field and the depth weighting values, well-ground joint variable weight first arrival tomographic inversion is performed to modify the full-depth velocity initial model and obtain a full-depth velocity modified model;

[0011] Determining a high-velocity top interface of the full-depth velocity modified model and calculating a static correction amount;

[0012] According to the static correction amount and the static correction-eliminated pre-correction common midpoint data, a common midpoint stack profile is generated, and the accuracy of the full-depth velocity correction model is verified according to the common midpoint stack profile.

[0013] In a case where the accuracy of the full-depth velocity correction model is greater than a threshold or meets an iteration exit condition, a target near-surface velocity model is output.

[0014] Optionally, the step of constructing the full-depth velocity initial model according to the multi-dimensional seismic data comprises:

[0015] According to the surface seismic data, a shallow velocity field of the full-depth velocity initial model is determined.

[0016] According to the vertical seismic profile seismic data, a middle-deep velocity field of the full-depth velocity initial model is determined.

[0017] The shallow velocity field, the middle-deep velocity field and a preset grid model are fused to construct the full-depth velocity initial model.

[0018] Optionally, the step of fusing the surface acquisition observation system and the well-to-surface joint acquisition observation system to obtain the target observation system comprises:

[0019] The layout relationship and coordinate positions of the shot points and the geophones in the surface acquisition observation system and the well-to-surface joint acquisition observation system are determined.

[0020] According to the shot points in the surface acquisition observation system and the shot points in the well-to-surface joint acquisition observation system, a shot point set of the target observation system is determined, and the shot point set of the target observation system is divided into sections according to wave fields, wherein the wave fields comprise a wave field of a surface seismic first arrival wave, a wave field of a vertical seismic profile first arrival wave and a wave field of a first multiple wave from a surface reflection of a vertical seismic profile.

[0021] According to the geophones in the surface acquisition observation system and the geophones in the well-to-surface joint acquisition observation system, a geophone set of the target observation system is determined, and the geophone set of the target observation system is divided into sections according to wave fields.

[0022] According to the layout relationship and coordinate positions of the shot points and the geophones in the surface acquisition observation system and the well-to-surface joint acquisition observation system, the section numbers of the shot point set of the target observation system and the section numbers of the geophone set of the target observation system, the target observation system is fused and generated.

[0023] According to the shot point elevation value, well depth correction is performed on each shot point in the shot point set of the target observation system.

[0024] Optionally, the step of fusing the first arrival waves of the wave fields comprises:

[0025] The first arrival density of each wave field in a preset work area range is determined.

[0026] According to the first arrival density of each wave field in the preset work area range, a contribution degree coefficient of each wave field is determined;

[0027] According to the contribution degree coefficient of each wave field, data fusion is performed on the first arrival wave of each wave field.

[0028] Optionally, according to the fused first arrival wave of each wave field, the contribution degree coefficient of each wave field, and the depth weighting value, joint well-ground inversion is performed on the first arrival layer by using variable weight, and the step of modifying the full-depth velocity initial model comprises:

[0029] A target horizon in the work area range is determined, and an inversion elevation threshold is determined according to the target horizon;

[0030] The shortest path method is used to perform ray tracing on the fused first arrival wave of each wave field, to obtain a real path of each wave field, and to generate a ray path matrix;

[0031] According to the ray path matrix, the contribution degree coefficient of each wave field, the depth weighting value, and the inversion elevation threshold, a linear equation set of tomographic inversion is constructed;

[0032] The full-depth velocity initial model is modified by using the linear equation set of tomographic inversion.

[0033] Optionally, the step of determining a high-velocity top interface of the full-depth velocity modified model and calculating a static correction amount comprises:

[0034] The high-velocity top interface is obtained by extracting a boundary according to the velocity value of the high-velocity layer and performing smoothing processing according to a preset radius;

[0035] The static correction amount is obtained according to the datum plane and the replacement velocity according to a static correction amount calculation formula;

[0036] The static correction amount calculation formula is:

[0037]

[0038] Wherein, Δt is a shot point or receiver static correction amount (ms); h i and v i are the depth upper dimension (m) and the velocity value (m / s) in the i-th grid below the shot point or receiver, respectively; E d is the datum plane elevation (m); E g is the high-velocity top interface elevation (m); V r is the replacement velocity of the datum plane (m / s).

[0039] Optionally, the common midpoint stack profile comprises a full offset profile and a split offset profile, and the step of verifying the accuracy of the full-depth velocity modified model according to the common midpoint stack profile comprises:

[0040] determine whether the full-depth velocity correction model has a long-wavelength static correction problem according to flatness of a structural form of the full-offset profile and the partial-offset profile;

[0041] determine accuracy of the corrected full-depth velocity correction model according to a result of the determination of whether the full-depth velocity correction model has the long-wavelength static correction problem.

[0042] In a second aspect, an embodiment of the present application provides a near-surface velocity model construction device, which comprises:

[0043] a construction module configured to construct a full-depth velocity initial model according to multi-dimensional seismic data;

[0044] an observation system fusion module configured to fuse a surface acquisition observation system and a well-ground joint acquisition observation system to obtain a target observation system;

[0045] a first arrival wave fusion module configured to perform data fusion on first arrival waves of each wave field in the target observation system to obtain fused first arrival waves of each wave field;

[0046] a model correction module configured to perform well-ground joint variable-weight first-break tomographic inversion on the full-depth velocity initial model according to the fused first arrival waves of each wave field, according to a contribution degree coefficient and a depth weighting value of each wave field;

[0047] a calculation module configured to determine a high-velocity top interface of the corrected full-depth velocity initial model and calculate a static correction amount;

[0048] a verification module configured to generate a common midpoint stack profile according to the static correction amount and a pre-moveout common midpoint data of a static correction elimination, and verify accuracy of the corrected full-depth velocity initial model according to the common midpoint stack profile;

[0049] an output module configured to output a target near-surface velocity model when the full-depth velocity correction model accuracy is greater than a threshold value or meets an iteration exit condition.

[0050] Optionally, the construction module comprises:

[0051] a shallow layer velocity field construction submodule configured to determine a shallow layer velocity field of the full-depth velocity initial model according to surface seismic data;

[0052] a middle-deep layer velocity field construction submodule configured to determine a middle-deep layer velocity field of the full-depth velocity initial model according to vertical seismic profile seismic data;

[0053] a velocity field fusion submodule configured to fuse the shallow layer velocity field, the middle-deep layer velocity field and a preset grid model to construct the full-depth velocity initial model.

[0054] Optionally, the observation system fusion module comprises:

[0055] a parameter determination sub-module configured to determine the layout relationship and coordinate positions of the shot points and the geophones in the surface acquisition observation system and the well-to-surface acquisition observation system;

[0056] a shot point set division sub-module configured to determine the shot point set of the target observation system according to the shot points in the surface acquisition observation system and the shot points in the well-to-surface acquisition observation system, and to divide the shot point set of the target observation system into sections according to the wave fields, wherein the wave fields comprise the wave field of the surface seismic first arrival wave, the wave field of the vertical seismic profile first arrival wave, and the wave field of the first multiple wave from the surface reflection of the vertical seismic profile;

[0057] a geophone set division sub-module configured to determine the geophone set of the target observation system according to the geophones in the surface acquisition observation system and the geophones in the well-to-surface acquisition observation system, and to divide the geophone set of the target observation system into sections according to the wave fields;

[0058] an observation system fusion sub-module configured to fuse the layout relationship and coordinate positions of the shot points and the geophones in the surface acquisition observation system and the well-to-surface acquisition observation system, the section numbers of the shot point set of the target observation system, and the section numbers of the geophone set of the target observation system, to generate the target observation system;

[0059] a shot point verification sub-module configured to perform well depth correction on each shot point in the shot point set of the target observation system according to the shot point elevation value.

[0060] Optionally, the first arrival wave fusion module comprises:

[0061] a first arrival density determination sub-module configured to determine the first arrival density of each wave field in the preset work area range;

[0062] a contribution degree coefficient determination sub-module configured to determine the contribution degree coefficient of each wave field according to the first arrival density of each wave field in the preset work area range;

[0063] a first arrival wave fusion sub-module configured to perform data fusion on the first arrival waves of each wave field according to the contribution degree coefficient of each wave field.

[0064] Optionally, the model correction module comprises:

[0065] a parameter determination sub-module configured to determine the target horizon in the work area range, and to determine the inversion elevation threshold according to the target horizon;

[0066] a ray path matrix determination sub-module configured to perform ray tracing on the fused first arrival waves of each wave field by using the shortest path method, to obtain the real paths of each wave field, and to generate a ray path matrix

[0067] a matrix construction sub-module, configured to construct a linear equation set of the tomographic inversion according to the ray path matrix, the contribution degree coefficient of each wave field, the depth weighting value and the inversion elevation threshold value;

[0068] a correction sub-module, configured to correct the full-depth velocity initial model by using the linear equation set of the tomographic inversion.

[0069] Optionally, the checking module comprises:

[0070] a first checking sub-module, configured to determine whether the full-depth velocity correction model has a long-wavelength static correction problem according to the flatness of the construction form of the full-offset profile and the split-offset profile;

[0071] a second checking sub-module, configured to determine the accuracy of the corrected full-depth velocity correction model according to the determination result of whether the full-depth velocity correction model has the long-wavelength static correction problem.

[0072] A third aspect of the embodiments of the present application provides an electronic device, and the electronic device comprises:

[0073] at least one processor; and a memory connected with the at least one processor in communication; wherein

[0074] The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method steps of the first aspect of the embodiments of the present application.

[0075] A fourth aspect of the embodiments of the present application provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the method steps of the first aspect of the embodiments of the present application.

[0076] The embodiment of the present application comprises the following advantages: firstly, according to multi-dimensional seismic data, a full-depth velocity initial model is constructed, and a surface acquisition observation system and a well-ground joint acquisition observation system are fused to obtain a target observation system. Then, in the target observation system, data fusion is performed on the first arrival wave of each wave field to obtain fused first arrival waves of each wave field, and according to the fused first arrival waves of each wave field, according to the contribution degree coefficient and the depth weighting value of each wave field, well-ground joint variable weight first arrival tomographic inversion is performed to correct the full-depth velocity initial model. Finally, the high-velocity top interface of the corrected full-depth velocity initial model is determined, the static correction amount is calculated, and according to the static correction amount and the dynamic correction before the common midpoint data for eliminating static correction, a common midpoint stack profile is generated, and according to the common midpoint stack profile, the accuracy of the corrected full-depth velocity initial model is verified, and in the case that the accuracy of the full-depth velocity correction model is greater than a threshold value or meets an iteration exit condition, a target near-surface velocity model is output. The common midpoint stack profile obtained by the present application has accurate structure and does not have the problem of long-wavelength static correction. Therefore, the near-surface velocity model constructed by the present application has high precision. BRIEF DESCRIPTION OF DRAWINGS

[0077] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0078] Figure 1 is a step flow chart of a near-surface velocity model construction method in the embodiment of the present application;

[0079] Figure 2 is a schematic diagram of a common midpoint stack profile in the embodiment of the present application;

[0080] Figure 3 is a schematic diagram of a near-surface velocity model generated in the embodiment of the present application;

[0081] Figure 4 is a module schematic diagram of a near-surface velocity model construction device in the embodiment of the present application. DETAILED DESCRIPTION

[0082] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0083] In existing geological exploration, micro-logging or multi-information constrained first-arrival tomography inversion methods are mainly used to construct near-surface velocity models. However, the above methods require constraining information such as deep micro-logging and surface outcrops. A single constraining information is an isolated point with a limited control range. When there is less constraining information and the near-surface structure is complex, the inverted near-surface velocity model has low accuracy.

[0084] Based on this, the inventors proposed the inventive concept of the present application: constructing an initial model of full-depth velocity, integrating ground acquisition with well-ground joint acquisition, and using the first arrival wave of ground seismic, the first arrival wave of VSP (Vertical Seismic Profile) and the wave field of the first multiple wave reflected by VSP from the surface to perform unified well-ground joint variable-weighted first arrival tomographic inversion, making full use of the real rays of the wave field of the VSP first arrival wave and the first multiple wave reflected by VSP from the surface to perform inversion, thereby improving the accuracy of the near-surface model.

[0085] See also Figure 1 , Figure 1 A flowchart of a method for constructing a near-surface velocity model according to an embodiment of the present application is shown. The method includes:

[0086] S101: Construct an initial full-depth velocity model based on multi-dimensional seismic data.

[0087] In this embodiment, the multi-dimensional seismic data mainly includes two-dimensional seismic data, namely, surface seismic data and vertical seismic profile seismic data, and the steps of constructing the full-depth velocity initial model based on the surface seismic data and the vertical seismic profile seismic data can be:

[0088] S101-1: Determine the shallow velocity field of the initial full-depth velocity model based on surface seismic data.

[0089] In this implementation, tomographic inversion is a nonlinear model inversion technique that uses the travel times and paths of seismic first-arrival rays to invert the medium's velocity structure, unconstrained by vertical and horizontal variations in surface and near-surface structures. Multiple iterations of tomographic inversion are performed on the received seismic data to obtain the near-surface velocity field. Therefore, the near-surface velocity model derived from tomographic inversion of the first-arrival waves of the surface seismic data is selected, and the high-velocity top interface is extracted based on the velocity values ​​of the high-velocity layer. The velocity field from the surface to the high-velocity top interface is used as the shallow velocity field for the initial full-depth velocity model.

[0090] S101-2: Determine the mid-depth velocity field of the initial full-depth velocity model based on vertical seismic profile seismic data.

[0091] In the embodiment, a fine layer velocity field obtained by 3D-VSP (well-to-surface) inversion is selected, time-depth conversion is performed on the vertical seismic profile seismic data to convert the vertical seismic profile seismic data from the time domain to the depth domain, and thus a velocity field in the depth domain is generated as a middle-depth velocity field of the full-depth velocity initial model.

[0092] S101-3: The shallow layer velocity field, the middle-depth velocity field and the preset grid model are fused to construct the full-depth velocity initial model.

[0093] In the embodiment, in the process of tomographic inversion, the grid parameters of the tomographic inversion include parameters in two directions of InLine and CrossLine. First, a large grid is selected for gridding, and a certain elevation below the ground surface is selected as a demarcation point, the elevation must be less than the minimum elevation value of the high-velocity top interface of the near-surface velocity model, a small grid is used above the demarcation point, a large grid is used at the demarcation point and below the demarcation point, the size of the grid in the depth direction is an integer multiple of the size of the small grid, and the size of the grid in the Inline and CrossLine directions is the same for the large and small grids. Finally, the shallow, middle-depth and deep velocity fields are fused in the grid body, and small-radius smoothing is performed, so as to construct the full-depth velocity initial model.

[0094] S102: The ground acquisition observation system and the well-to-surface acquisition observation system are fused to obtain a target observation system.

[0095] In the embodiment, the ground acquisition observation system refers to that the shot points are excited on the ground, and the geophones are also arranged on the ground. The well-to-surface acquisition observation system refers to that the shot points are excited on the ground, and the geophones are arranged in the exploration well. Therefore, the shot points and the geophones of the two observation systems are independent of each other. In order to make the seismic data obtained by the observation systems in the same format, the two observation systems need to be placed in the same observation system, and the specific steps can be as follows:

[0096] S102-1: The arrangement relationship and the coordinate position of the shot points and the geophones in the ground acquisition observation system and the well-to-surface acquisition observation system are determined.

[0097] In the embodiment, the design scheme of the ground acquisition observation system and the well-to-surface acquisition observation system includes design parameters such as the number of shot points, the number of geophones, and the arrangement relationship of the shot points and the geophones in the ground acquisition observation system. Therefore, the arrangement relationship and the coordinate position of the shot points and the geophones in the two systems can be obtained according to the design scheme of the ground acquisition observation system and the well-to-surface acquisition observation system.

[0098] S102-2: The shot point set of the target observation system is determined according to the shot points in the ground acquisition observation system and the shot points in the well-to-surface acquisition observation system, and the shot point set of the target observation system is divided into sections according to the wave field.

[0099] In the embodiment, the wave fields used in the application mainly include three kinds: the wave field of the first arrival wave of surface seismic, the wave field of the first arrival wave of VSP and the wave field of the first multiple reflected from the surface of VSP, so the shot points in the acquisition observation system and the shot points in the well-ground joint acquisition observation system are taken together as the shot point set of the fused target observation system, then the file numbers of the shot point set are divided into three sections, i.e. the first arrival wave section of surface seismic, the first arrival wave section of VSP and the first multiple reflected from the surface section of VSP, each section is distinguished by a prefix to form a unified section number, so as to realize the section division of the shot point set of the target observation system.

[0100] S102-3: According to the geophone points in the surface acquisition observation system and the geophone points in the well-ground joint acquisition observation system, the geophone point set of the target observation system is determined, and the geophone point set of the target observation system is sectioned according to the wave field.

[0101] In the embodiment, the geophone points in the acquisition observation system and the geophone points in the well-ground joint acquisition observation system are taken together as the geophone point set of the fused target observation system, then the file numbers of the geophone point set are divided into three sections, i.e. the first arrival wave section of surface seismic, the first arrival wave section of VSP and the first multiple reflected from the surface section of VSP, each section is distinguished by a prefix to form a unified section number, so as to realize the section division of the geophone point set of the target observation system.

[0102] S102-4: According to the layout relationship and coordinate position of the shot points and geophone points in the surface acquisition observation system and the well-ground joint acquisition observation system, the section number of the shot point set of the target observation system and the section number of the geophone point set of the target observation system, the target observation system is generated by fusion.

[0103] In the embodiment, the observation system is fused according to the unified section number of the shot point set, the unified section number of the geophone point set and the shot-geophone position and arrangement relationship of each wave field to generate a unified target observation system.

[0104] S102-5: According to the shot elevation value, each shot point in the shot point set of the target observation system is subjected to well depth correction.

[0105] In the embodiment, after obtaining the target observation system, each shot point in the shot point set is subjected to well depth correction by using the formula shown in formula 1

[0106] E new =-D(1)

[0107] Wherein, E is the shot elevation value (m); D is the well depth at the shot point (m); E new is the shot elevation value after well depth correction (m).

[0108] S103: In the target observation system, data fusion is performed on the first arrival of each wave field to obtain a fused first arrival of each wave field.

[0109] In the embodiment, in the target observation system, the first arrival of the picked-up surface seismic, the first arrival of the VSP first arrival, and the first arrival of the first multiple wave from the surface reflection of the VSP can be imported. Since the first arrivals of the wave fields are independent of each other and have different formats, it is necessary to convert the first arrivals of the wave fields to the same format. The specific steps can be as follows:

[0110] S103-1: Determine the first arrival density of each wave field in the preset work area.

[0111] In the embodiment, the maximum distance from the shot point to the VSP wellhead is divided into several annular regions, and then the first arrival density of each wave field is counted in each small region.

[0112] S103-2: Determine the contribution degree coefficient of each wave field according to the first arrival density of each wave field in the preset work area.

[0113] In the embodiment, after obtaining the first arrival density of each wave field, the contribution degree coefficient of each wave field is determined according to the formulas shown in formulas 2, 3, and 4.

[0114] The contribution degree coefficient of the surface seismic first arrival is:

[0115]

[0116] Wherein, g is the contribution degree coefficient; Q1 is the first arrival density threshold of the surface seismic first arrival; q is the first arrival density of the wave field in each small region; and c1 is the suppression coefficient.

[0117] The contribution degree coefficient of the VSP first arrival is:

[0118]

[0119] Wherein, g is the contribution degree coefficient; Q2 is the first arrival density threshold of the VSP first arrival; q is the first arrival density of the wave field in each small region; and c2 is the enhancement coefficient.

[0120] The contribution degree coefficient of the first multiple wave from the surface reflection of the VSP is:

[0121]

[0122] Wherein, g is the contribution degree coefficient; Q3 is the first arrival density threshold of the first multiple wave from the surface reflection of the VSP; q is the first arrival density of the wave field in each small region; and c3 is the enhancement coefficient.

[0123] S103-3: Fuse the first arrival wave of each wave field according to the contribution degree coefficient of each wave field.

[0124] After obtaining the contribution degree coefficient of each wave field, the first arrival wave of each wave field is fused by using the weighted summation method according to the contribution degree coefficient corresponding to each first arrival wave of each wave field, so as to obtain the fused first arrival wave of each wave field.

[0125] S104: According to the fused first arrival wave of each wave field, the contribution degree coefficient of each wave field, and the depth weighting value, perform joint well-ground variable weight first arrival tomographic inversion to modify the full-depth velocity initial model.

[0126] In the embodiment, after obtaining the fused first arrival wave fused by the first arrival wave of each wave field, tomographic inversion needs to be performed according to the fused first arrival wave, and the specific steps include:

[0127] S104-1: Determine the target horizon in the work area range, and determine the inversion elevation threshold according to the target horizon.

[0128] In the embodiment, the horizon in the work area range that can be continuously tracked is determined as the target horizon, and the elevation at a certain depth below the target horizon is determined as the minimum inversion elevation, that is, the threshold of the inversion elevation. Selecting the minimum inversion elevation can reduce the data amount and improve the calculation efficiency.

[0129] S104-2: Perform ray tracing on the fused first arrival wave of each wave field by using the shortest path method to obtain the real path of each wave field, and generate a ray path matrix.

[0130] In the embodiment, the first arrival ray tracing method uses the shortest path method. The shortest path method selects the minimum travel time path between the shot point and the receiver point as the real path according to Fermat's principle. For the first arrival wave of surface seismic and VSP, the shortest path method can be directly used for ray tracing. For the first multiple wave of VSP from the surface reflection, it is first propagated to the surface to form different sub-sources, and then propagated from the sub-sources to the receiver. The shortest path of the whole process is the real path, and a ray path matrix L is generated according to the real path of each wave field.

[0131] S104-3: Construct a linear equation set of tomographic inversion according to the ray path matrix, the contribution degree coefficient of each wave field, the depth weighting value, and the inversion elevation threshold.

[0132] S104-4: Modify the full-depth velocity initial model through the linear equation set of tomographic inversion.

[0133] In the embodiments of S104-3 to S104-4, the linear equation set of tomographic inversion is as follows:

[0134] T = LS (5)

[0135] L = (l ij ) n×m (6)

[0136] where T is the traveltime vector; L is the raypath matrix, l ij is the element of the i-th row and j-th column in the raypath matrix L; S is the slowness vector.

[0137] The different slowness changes are caused by the different shallow and deep velocities, the slowness changes in the shallow layer are large, and the slowness changes in the deep layer are small, therefore, a weighting function is used to enhance the inversion stability:

[0138]

[0139] where w is the weighting function; E k is the elevation threshold; E is the elevation of the grid; c(E) is the function of E.

[0140] The weighted joint iterative reconstruction method is used to correct the slowness, as shown in equations (8)-(10).

[0141] The traveltime residual of the p-th iteration is:

[0142]

[0143] where, is the traveltime residual of the i-th ray in the p-th iteration; l ij is the element of the i-th row and j-th column in the raypath matrix L; t i is the traveltime of the i-th ray; is the slowness of the j-th grid after the p-1-th modification.

[0144] The slowness residual of the p-th iteration is:

[0145]

[0146] where, is the slowness residual of the j-th grid in the p-th iteration; w j is the weighting value on the depth of the j-th grid; g is the contribution degree coefficient of each wavefield type; B j is the number of non-zero elements in the j-th column of the raypath matrix L; is the traveltime residual of the i-th ray in the p-th iteration; l ij is the element of the i-th row and j-th column in the raypath matrix L.

[0147] In the p-th iteration, the slowness residual is used to correct the velocity model:

[0148]

[0149] wherein, is the slowness of the jth grid at the pth time; is the slowness residual of the jth grid at the pth time; is the slowness of the jth grid at the (p-1)th time.

[0150] S105: Determine the high-velocity top boundary of the full-depth velocity correction model, and calculate the static correction amount.

[0151] In the embodiment, first, the high-velocity top boundary is extracted according to the velocity value of the high-velocity layer, smoothed according to a certain radius, and then the static correction amount is calculated according to formula (11) through the datum surface and the replacement velocity.

[0152]

[0153] In the formula, Δt is the static correction amount of the shot point or the receiver point (ms); h i and v i are the depth upper dimension (m) and the velocity value (m / s) of the ith grid below the shot point or the receiver point, respectively; E d is the elevation of the datum surface (m); E g is the elevation of the high-velocity top boundary (m); V r is the replacement velocity of the datum surface (m / s).

[0154] S106: Generate the common midpoint stack profile according to the static correction amount and the dynamic correction pre-elimination static amount common midpoint data, and verify the accuracy of the corrected full-depth velocity initial model according to the common midpoint stack profile.

[0155] In the embodiment, after the static correction, denoising, amplitude compensation, deconvolution, and inverse static correction, the CMP (Common Middle Point) data are the dynamic correction pre-elimination static amount CMP data, which can be processed by static correction, dynamic correction, cutting, stacking, cutting, residual static correction of reflection wave, and post-stack filtering to generate the CMP stack profile. The CMP stack profile includes two profiles, i.e., the full-offset profile and the split-offset profile. After obtaining the CMP stack profile, the steps for judging the accuracy of the surface velocity model can be as follows:

[0156] S106-1: Determine whether the full-depth velocity correction model has a long-wavelength static correction problem according to the flatness of the structural form of the full-offset profile and the split-offset profile;

[0157] S106-2: Determine the accuracy of the corrected full-depth velocity correction model according to the judgment result of whether the full-depth velocity correction model has a long-wavelength static correction problem.

[0158] In the embodiments of S106-1 to S106-2, there are mainly full-offset and partial-offset profiles, and the long-wavelength static correction problem is identified by the structural configuration on the profile and the difference thereof, so as to verify the accuracy of the corrected full-depth velocity initial model. Alternatively, the accuracy of the corrected full-depth velocity initial model is verified by using the time-depth curve or interpretation result of the deep micro-logging.

[0159] As an example, as shown in FIG. 3, the upper diagram is a near-surface velocity model diagram obtained by using a conventional method, and the lower diagram is a near-surface velocity model diagram obtained by using the method of the present application. Therefore, the near-surface velocity model obtained by using the conventional method is concave below the high-velocity top interface, and the near-surface velocity model is inaccurate. The near-surface velocity model obtained by using the method of the present application is flat at the high-velocity top interface, and the near-surface velocity model is accurate. Figure 2 Figure 2 The stacking profile obtained by using the conventional method has an inaccurate structural configuration and a long-wavelength static correction problem, and the stacking profile obtained by using the method of the present application has an accurate structural configuration and no long-wavelength static correction problem. Therefore, the present application can improve the imaging accuracy of seismic data, and further improve the subsequent well location prediction or drilling success rate.

[0160] S107: In the case where the accuracy of the full-depth velocity correction model is greater than a threshold value or meets an iteration exit condition, a target near-surface velocity model is output.

[0161] In the embodiments, when the accuracy of the obtained surface velocity model is greater than a preset threshold value, that is, the iteration error curve meets the convergence accuracy or reaches the preset iteration number requirement, the near-surface velocity model obtained in the last iteration is output as the target near-surface velocity model, so as to output the near-surface velocity model in a specified format, such as a file format and a Segy format. If the iteration error curve does not meet the convergence accuracy or does not reach the preset iteration number requirement, the steps of S104 to S107 are repeatedly iterated.

[0162] As an example, as shown in FIG. 3, the upper diagram is a near-surface velocity model diagram obtained by using a conventional method, and the lower diagram is a near-surface velocity model diagram obtained by using the method of the present application. Therefore, the near-surface velocity model obtained by using the conventional method is concave below the high-velocity top interface, and the near-surface velocity model is inaccurate. The near-surface velocity model obtained by using the method of the present application is flat at the high-velocity top interface, and the near-surface velocity model is accurate.

[0163] The embodiments of the present application also provide a near-surface velocity model construction device, which is shown in FIG. 4 and specifically refers to Figure 4 The device can include the following modules:

[0164] The construction module 401 is configured to construct a full-depth velocity initial model according to multi-dimensional seismic data.

[0165] The observation system fusion module 402 is configured to fuse a ground acquisition observation system and a well-ground joint acquisition observation system to obtain a target observation system.​

[0166] a first arrival wave fusion module 403, configured to perform data fusion on the first arrival waves of the wave fields in the target observation system to obtain fused first arrival waves of the wave fields;

[0167] a model correction module 404, configured to correct the initial full-depth velocity model according to the fused first arrival waves of the wave fields, the contribution degree coefficients of the wave fields and the depth weighting values, by performing well-ground joint variable-weight first arrival tomographic inversion;

[0168] a calculation module 405, configured to determine a high-velocity top interface of the corrected initial full-depth velocity model and calculate a static correction amount;

[0169] a verification module 406, configured to generate a common midpoint stack profile according to the static correction amount and the common midpoint data before the moveout correction amount is eliminated, and verify the accuracy of the corrected initial full-depth velocity model according to the common midpoint stack profile;

[0170] an output module 407, configured to output the target near-surface velocity model when the accuracy of the full-depth velocity correction model is greater than a threshold value or meets an iteration exit condition.

[0171] In an implementation, the construction module comprises:

[0172] a shallow velocity field construction sub-module, configured to determine a shallow velocity field of the initial full-depth velocity model according to the surface seismic data;

[0173] a middle-deep velocity field construction sub-module, configured to determine a middle-deep velocity field of the initial full-depth velocity model according to the vertical seismic profile seismic data;

[0174] a velocity field fusion sub-module, configured to fuse the shallow velocity field, the middle-deep velocity field and a preset grid model to construct the initial full-depth velocity model.

[0175] In an implementation, the observation system fusion module comprises:

[0176] a parameter determination sub-module, configured to determine the layout relationship and coordinate positions of the shot points and the geophones in the surface acquisition observation system and the well-ground joint acquisition observation system;

[0177] a shot point set division sub-module, configured to determine a shot point set of the target observation system according to the shot points in the surface acquisition observation system and the shot points in the well-ground joint acquisition observation system, and divide the shot point set of the target observation system into sections according to wave fields, wherein the wave fields comprise a wave field of surface seismic first arrival waves, a wave field of vertical seismic profile first arrival waves and a wave field of the first multiple waves from the surface reflection in the vertical seismic profile;

[0178] The detection point set division sub-module is configured to determine a detection point set of the target observation system according to detection points in the ground acquisition observation system and detection points in the well-ground joint acquisition observation system, and to perform sectional division on the detection point set of the target observation system according to wave fields.

[0179] The observation system fusion sub-module is configured to fuse the sectional numbers of the shot point set of the target observation system and the sectional numbers of the detection point set of the target observation system according to the layout relationship and coordinate positions of the shot points and the detection points in the ground acquisition observation system and the well-ground joint acquisition observation system, to generate the target observation system.

[0180] The shot point verification sub-module is configured to perform well depth correction on each shot point in the shot point set of the target observation system according to the shot point elevation value.

[0181] In an available implementation, the first arrival wave fusion module includes:

[0182] The first arrival density determination sub-module is configured to determine the first arrival density of each wave field in the preset work area range.

[0183] The contribution degree coefficient determination sub-module is configured to determine the contribution degree coefficient of each wave field according to the first arrival density of each wave field in the preset work area range.

[0184] The first arrival wave fusion sub-module is configured to perform data fusion on the first arrival waves of each wave field according to the contribution degree coefficient of each wave field.

[0185] In an available implementation, the model correction module includes:

[0186] The parameter determination sub-module is configured to determine a target horizon in the work area range, and to determine an inversion elevation threshold according to the target horizon.

[0187] The ray path matrix determination sub-module is configured to perform ray tracing on the fused first arrival waves of each wave field by using the shortest path method, to obtain the real path of each wave field, and to generate a ray path matrix.

[0188] The matrix construction sub-module is configured to construct a linear equation set of tomographic inversion according to the ray path matrix, the contribution degree coefficient of each wave field, the depth weighting value, and the inversion elevation threshold.

[0189] The correction sub-module is configured to correct the full-depth velocity initial model by using the linear equation set of tomographic inversion.

[0190] In an available implementation, the verification module includes:

[0191] The first verification sub-module is configured to determine whether the full-depth velocity correction model has a long-wavelength static correction problem according to the flatness of the configuration form of the full-offset profile and the split-offset profile.

[0192] The second checking sub-module is configured to determine the accuracy of the corrected full-depth velocity correction model according to the determination result of whether the full-depth velocity correction model has the long-wavelength static correction problem.

[0193] Based on the same inventive concept, the embodiments of the present application also propose an electronic device, which comprises:

[0194] at least one processor; and a memory connected with the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the reconstruction method of three-dimensional seismic data according to the embodiments of the present application.

[0195] In addition, to achieve the above-mentioned purpose, the embodiments of the present application also propose a computer readable storage medium storing a computer program, and the computer program is executed by a processor to implement the near-surface velocity model construction method according to the embodiments of the present application.

[0196] In addition, to achieve the above-mentioned purpose, the embodiments of the present application also propose a computer readable storage medium storing a computer program, and the computer program is executed by a processor to implement the near-surface velocity model construction method according to the embodiments of the present application.

[0197] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the embodiments of the present application can be in the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the embodiments of the present application can be in the form of a computer program product implemented on one or more computer-usable vehicles (including but not limited to disk memory, CD-ROM, optical memory, etc.) containing computer-usable program code.

[0198] The embodiments of the present application are described with reference to flowcharts and / or block diagrams according to the method, terminal device (system), and computer program product of the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of the flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal device to produce a machine, so that the instructions executed by the computer or other programmable data processing terminal device produce a device for implementing the functions specified in the flowcharts and / or block diagrams. Figure 1 The system that implements the functions specified in one flow or multiple flows and / or blocks Figure 1 The system that implements the functions specified in one flow or multiple flows and / or blocks

[0199] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the flow Figure 1 one or more flow or blocks and / or Figure 1 one or more blocks or blocks specified in the flow.

[0200] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal apparatus to cause a series of operational steps to be performed on the computer or other programmable terminal apparatus to produce a computer implemented process such that the instructions executed on the computer or other programmable terminal apparatus provide steps for implementing the flow Figure 1 one or more flow or blocks and / or Figure 1 one or more blocks or blocks specified in the flow.

[0201] Finally, it should be noted that, in this document, relational terms such as first and second and the like can be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. "And / or" indicates that either of the two following conditions can be selected, or both can be selected. In addition, the terms "comprise", "contain" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal device including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such a process, method, article or terminal device. Without more limitations, the element defined by the statement "comprises a" does not exclude the presence of additional identical elements in the process, method, article or terminal device that includes the element.

[0202] The above describes in detail the near-surface velocity model construction method, device, electronic equipment and storage medium provided by the present application. The principles and implementation modes of the present application are described by using specific examples. The above example is only used to help understand the method and core idea of the present application. Meanwhile, for those skilled in the art, according to the idea of the present application, the specific implementation mode and application range will be changed. In summary, the content of the specification should not be understood as a limitation of the present application.

Claims

1. A method for constructing a near-surface velocity model, characterized in that: The method comprises: Based on multi-dimensional seismic data, an initial full-depth velocity model is constructed; Integrate the ground acquisition observation system and the well-ground joint acquisition observation system to obtain the target observation system; In the target observation system, data fusion is performed on the first arrival waves of each wave field to obtain fused first arrival waves of each wave field; Performing well-ground joint variable-weighted first-arrival tomographic inversion based on the fused first arrival waves of each wave field, the contribution coefficient of each wave field, and the depth weighted value, and correcting the full-depth velocity initial model to obtain a full-depth velocity correction model; determining a high-speed top interface of the full-depth velocity correction model and calculating a static correction amount; generating a common midpoint stacking section based on the static correction amount and the common midpoint data before dynamic correction after eliminating the static correction amount, and verifying the accuracy of the full-depth velocity correction model based on the common midpoint stacking section; When the accuracy of the full-depth velocity correction model is greater than a threshold or an iteration exit condition is met, a target near-surface velocity model is output.

2. The method for constructing a near-surface velocity model according to claim 1, wherein: The steps to construct an initial full-depth velocity model based on multi-dimensional seismic data include: Determining the shallow velocity field of the full-depth velocity initial model based on surface seismic data; Determining the mid-depth velocity field of the full-depth velocity initial model based on vertical seismic profile seismic data; The shallow velocity field, the mid-deep velocity field and the preset grid model are fused to construct the full-depth velocity initial model.

3. The method for constructing a near-surface velocity model according to claim 1, wherein: The steps of integrating the surface acquisition observation system and the well-ground joint acquisition observation system to obtain the target observation system include: Determine the layout relationship and coordinate positions of shot points and receiver points in the surface acquisition observation system and the well-ground joint acquisition observation system; Determining a shot point set of the target observation system based on the shot points in the surface acquisition observation system and the shot points in the well-ground joint acquisition observation system, and segmenting the shot point set of the target observation system based on a wave field, wherein the wave field includes: a wave field of a surface seismic first arrival wave, a wave field of a vertical seismic profile first arrival wave, and a wave field of a first multiple wave reflected from the surface of the vertical seismic profile; Determine the set of detection points of the target observation system based on the detection points in the ground acquisition observation system and the detection points in the well-ground joint acquisition observation system, and divide the set of detection points of the target observation system into sections based on the wave field; generating the target observation system based on the layout relationship and coordinate positions of the shot points and the receiver points in the surface acquisition observation system and the well-ground joint acquisition observation system, the segment numbers of the shot point set of the target observation system, and the segment numbers of the receiver point set of the target observation system; A well depth correction is performed on each shot point in the shot point set of the target observation system according to the shot point elevation value.

4. The method for constructing a near-surface velocity model according to claim 1, wherein: The steps of data fusion for the first arrival waves of each wave field include: Determine the first arrival density of each wave field within the preset working area; Determining the contribution coefficient of each wave field according to the first arrival density of each wave field within a preset working area; Data fusion is performed on the first arrivals of the wave fields according to the contribution coefficients of the wave fields.

5. The method for constructing a near-surface velocity model according to claim 1, wherein: The steps of performing well-ground joint variable-weighted first-break tomographic inversion based on the fused first arrival waves of each wave field, the contribution coefficient of each wave field, and the depth weighted value, and correcting the full-depth velocity initial model include: Determine a target horizon within the work area, and determine an inversion elevation threshold based on the target horizon; Performing ray tracing on the fused first arrival waves of the respective wave fields using the shortest path method to obtain the true paths of the respective wave fields and generate a ray path matrix; Constructing a linear equation group for tomographic inversion according to the ray path matrix, the contribution coefficients of the respective wave fields, the depth weighted value, and the inversion elevation threshold; The full-depth velocity initial model is modified by the linear equations of the tomographic inversion.

6. The method for constructing a near-surface velocity model according to claim 1, wherein: The steps of determining the high-speed top interface of the full-depth velocity correction model and calculating the static correction amount include: Extract the boundary according to the velocity value of the high-speed layer, and perform smoothing according to the preset radius to obtain the high-speed top interface; According to the reference surface and the replacement speed, the static correction amount is obtained according to the static correction amount calculation formula; The static correction calculation formula is: Where Δt is the static correction value of the shot point or receiver point, h i and v i are the depth dimension of the ith grid below the shot point or receiver point and the velocity value within the grid, E d is the datum elevation, E g is the elevation of the high-speed top interface, V r Replace velocity with reference surface.

7. The method for constructing a near-surface velocity model according to claim 1, wherein: The common midpoint stacked section includes a full-offset section and a sub-offset section. The step of verifying the accuracy of the full-depth velocity correction model based on the common midpoint stacked section includes: Determining whether the full-depth velocity correction model has a long-wavelength static correction problem based on the flatness of the structural morphology of the full-offset section and the sub-offset section; The accuracy of the corrected full-depth velocity correction model is determined based on a determination result of whether the full-depth velocity correction model has a long-wavelength static correction problem.

8. A near-surface velocity model construction device, characterized in that: The device comprises: A construction module for constructing an initial full-depth velocity model based on multi-dimensional seismic data; The observation system fusion module is used to fuse the ground acquisition observation system and the well-ground joint acquisition observation system to obtain the target observation system; A first arrival wave fusion module is used to perform data fusion on the first arrival waves of each wave field in the target observation system to obtain fused first arrival waves of each wave field; a model correction module for performing well-ground joint variable-weighted first-break tomographic inversion based on the fused first arrival waves of each wave field, the contribution coefficient of each wave field, and the depth weighted value, to correct the full-depth velocity initial model and obtain a full-depth velocity correction model; a calculation module, configured to determine a high-speed top interface of the full-depth velocity correction model and calculate a static correction amount; a verification module, configured to generate a common midpoint stacking section based on the static correction amount and the common midpoint data before dynamic correction in which the static correction amount is eliminated, and verify the accuracy of the full-depth velocity correction model based on the common midpoint stacking section; The output module is used to output a target near-surface velocity model when the accuracy of the full-depth velocity correction model is greater than a threshold or an iteration exit condition is met.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the near-surface velocity model construction method according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method for constructing a near-surface velocity model according to any one of claims 1 to 7 is implemented.

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