阅读说明：本技术 一种基于虚拟井的叠前数据处理方法及装置 (Pre-stack data processing method and device based on virtual well ) 是由 杨志力 王彬 鲁银涛 吴敬武 李丽 张强 杨涛涛 孙国忠 于 2019-10-31 设计创作，主要内容包括：本发明提供一种基于虚拟井的叠前数据处理方法及装置,所述方法包括：根据目标区域的每个虚拟井点的原始地震记录数据,获得每个虚拟井点的角道集地震记录数据；其中,所述虚拟井点有预设数量；根据每个虚拟井点的角道集地震记录数据,获得每个虚拟井点的虚拟井数据；根据所述预设数量的虚拟井点的虚拟井数据,构建所述目标区域的初始数据体模型；根据所述目标区域的角道集地震记录数据以及所述目标区域的初始数据体模型,获得所述目标区域的最终叠前参数数据体模型。所述装置用于执行上述方法。本发明实施例提供的基于虚拟井的叠前数据处理方法及装置,提高了目标区域的叠前参数数据的准确性。(The invention provides a method and a device for processing prestack data based on a virtual well, wherein the method comprises the following steps: obtaining angle gather seismic record data of each virtual well point according to the original seismic record data of each virtual well point of the target area; wherein the virtual well points have a preset number; acquiring virtual well data of each virtual well point according to the angle gather seismic record data of each virtual well point; constructing an initial data volume model of the target area according to the virtual well data of the virtual well points with the preset number; and obtaining a final pre-stack parameter data volume model of the target area according to the angle gather seismic record data of the target area and the initial data volume model of the target area. The device is used for executing the method. The method and the device for processing the pre-stack data based on the virtual well improve the accuracy of the pre-stack parameter data of the target area.)

1. A method for processing prestack data based on virtual wells is characterized by comprising the following steps:

obtaining angle gather seismic record data of each virtual well point according to the original seismic record data of each virtual well point of the target area; wherein the virtual well points have a preset number;

acquiring virtual well data of each virtual well point according to the angle gather seismic record data of each virtual well point;

constructing an initial data volume model of the target area according to the virtual well data of the virtual well points with the preset number;

and obtaining a final pre-stack parameter data volume model of the target area according to the angle gather seismic record data of the target area and the initial data volume model of the target area.

2. The method of claim 1, wherein obtaining virtual well data for each virtual well point from the angle gather seismic record data for each virtual well point comprises:

establishing an initial geological model of each virtual well point according to the velocity data corresponding to the angle gather seismic record data of each virtual well point;

randomly generating n groups of random geological models of each virtual well point based on the initial geological model;

obtaining synthetic seismic record data of each virtual well point according to the n groups of random geological models of each virtual well point and the Zorni Privitz equation;

and obtaining the virtual well data of each virtual well point according to the synthetic seismic record data of each virtual well, the angle gather seismic record data of each virtual well point and a genetic algorithm.

3. The method of claim 1, wherein constructing an initial data volume model of the target region from the virtual well data for the preset number of virtual well points comprises:

and constructing an initial data volume model of the target area based on the virtual well data of the preset number of virtual well points and an interpolation method.

4. The method of any one of claims 1 to 3, wherein obtaining a final pre-stack parametric data volume model for the target region from the angle gather seismic recording data for the target region and the initial data volume model for the target region comprises:

and correcting the initial data volume model of the target area according to the angle gather seismic record data of the target area and a preset formula to obtain a final pre-stack parameter data volume model of the target area.

5. A pre-stack data processing apparatus based on virtual wells, comprising:

the first obtaining unit is used for obtaining angle gather seismic record data of each virtual well point according to the original seismic record data of each virtual well point of the target area; wherein the virtual well points have a preset number;

the second obtaining unit is used for obtaining the virtual well data of each virtual well point according to the angle gather seismic record data of each virtual well point;

the construction unit is used for constructing an initial data volume model of the target area according to the virtual well data of the preset number of virtual well points;

and the third obtaining unit is used for obtaining a final pre-stack parameter data volume model of the target area according to the angle gather seismic record data of the target area and the initial data volume model of the target area.

6. The apparatus of claim 5, wherein the second obtaining unit comprises:

the establishing subunit is used for establishing an initial geological model of each virtual well point according to the velocity data corresponding to the angle gather seismic record data of each virtual well point;

a generating subunit, configured to randomly generate n sets of geological model parameters for each virtual well point based on the initial geological model;

the first obtaining subunit is used for obtaining synthetic seismic record data of each virtual well point according to the n groups of geological model parameters of each virtual well point and the Zorni Prizz equation;

and the second obtaining subunit is used for obtaining the virtual well data of each virtual well point according to the synthetic seismic record data of each virtual well, the angle gather seismic record data of each virtual well point and a genetic algorithm.

7. The apparatus according to claim 5, wherein the construction unit is specifically configured to:

and constructing an initial data volume model of the target area based on the virtual well data of the preset number of virtual well points and an interpolation method.

8. The apparatus according to any one of claims 5 to 7, wherein the third obtaining unit is specifically configured to:

and correcting the initial data volume model of the target area according to the angle gather seismic record data of the target area and a preset formula to obtain a final pre-stack parameter data volume model of the target area.

9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the method of any of claims 1 to 4 are implemented when the computer program is executed by the processor.

10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 4.

Technical Field

The invention relates to the technical field of geological exploration, in particular to a prestack data processing method and device based on a virtual well.

Background

In marine oil exploration, development of reservoir prediction and oil-gas bearing prediction of a target area is very important research work.

The marine oil exploration is a high-risk and high-investment work, few wells are drilled in a marine deepwater area, even no wells are drilled, so that logging information is scarce, exploration is carried out in the marine area, if early analysis and prediction work such as reservoir prediction, oil-gas content prediction and the like is not carried out, wells are directly drilled, the risk is too high, well drilling failure is likely to be caused, and therefore the reservoir prediction and the oil-gas content prediction of a target area are required, and the risk of well drilling failure can be effectively reduced. The virtual well technology is a good method for solving the problem that no well or few well zones lack real logging information in reservoir prediction and oil-gas-bearing prediction, the traditional virtual well construction technology is based on wave impedance information obtained by seismic inversion of a wave impedance data volume, and the virtual well constructed by utilizing the wave impedance information has the defects of low resolution and detail omission, so that the traditional virtual well construction technology has large errors.

Therefore, how to provide a method for processing prestack data based on a virtual well is an important issue to be solved in the field, which is to improve the accuracy of the prestack data of the target area.

Disclosure of Invention

Aiming at the problems in the prior art, the embodiment of the invention provides a method and a device for processing prestack data based on a virtual well.

In one aspect, the invention provides a prestack data processing method based on a virtual well, which comprises the following steps:

obtaining angle gather seismic record data of each virtual well point according to the original seismic record data of each virtual well point of the target area; wherein the virtual well points have a preset number;

acquiring virtual well data of each virtual well point according to the angle gather seismic record data of each virtual well point;

constructing an initial data volume model of the target area according to the virtual well data of the virtual well points with the preset number;

and obtaining a final pre-stack parameter data volume model of the target area according to the angle gather seismic record data of the target area and the initial data volume model of the target area.

In another aspect, the present invention provides a pre-stack data processing apparatus based on a virtual well, comprising:

the first obtaining unit is used for obtaining angle gather seismic record data of each virtual well point according to the original seismic record data of each virtual well point of the target area; wherein the virtual well points have a preset number;

the second obtaining unit is used for obtaining the virtual well data of each virtual well point according to the angle gather seismic record data of each virtual well point;

the construction unit is used for constructing an initial data volume model of the target area according to the virtual well data of the preset number of virtual well points;

and the third obtaining unit is used for obtaining a final pre-stack parameter data volume model of the target area according to the angle gather seismic record data of the target area and the initial data volume model of the target area.

In yet another aspect, the present invention provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor executes the program to implement the steps of the virtual well-based prestack data processing method according to any of the above embodiments.

In yet another aspect, the present invention provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the virtual well-based pre-stack data processing method according to any of the above embodiments.

According to the pre-stack data processing method and device based on the virtual well, angle gather seismic record data of each virtual well point is obtained according to original seismic record data of each virtual well point of a target area, then virtual well data of each virtual well point are obtained according to the angle gather seismic record data of each virtual well point, an initial data volume model of the target area is constructed according to the virtual well data of a preset number of virtual well points, a final pre-stack parameter data volume model of the target area is obtained according to the angle gather seismic record data of the target area and the initial data volume model of the target area, pre-stack parameter data of the target area are obtained through the virtual well data, and accuracy of the pre-stack parameter data of the target area is improved.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts. In the drawings:

fig. 1 is a schematic flow chart of a method for processing prestack data based on a virtual well according to an embodiment of the present invention.

Fig. 2 is a schematic flow chart of a method for processing prestack data based on a virtual well according to another embodiment of the present invention.

Fig. 3 is a schematic structural diagram of a pre-stack data processing apparatus based on a virtual well according to an embodiment of the present invention.

Fig. 4 is a schematic structural diagram of a pre-stack data processing apparatus based on a virtual well according to another embodiment of the present invention.

Fig. 5 is a schematic physical structure diagram of an electronic device according to an embodiment of the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the embodiments of the present invention are further described in detail below with reference to the accompanying drawings. The exemplary embodiments and descriptions of the present invention are provided to explain the present invention, but not to limit the present invention. It should be noted that the embodiments and features of the embodiments in the present application may be arbitrarily combined with each other without conflict.

Fig. 1 is a schematic flow diagram of a virtual well-based pre-stack data processing method according to an embodiment of the present invention, and as shown in fig. 1, the virtual well-based pre-stack data processing method according to the embodiment of the present invention includes:

s101, obtaining angle gather seismic record data of each virtual well point according to the original seismic record data of each virtual well point of a target area; wherein the virtual well points have a preset number;

specifically, original seismic record data of a target area are acquired through field acquisition, a preset number of typical positions are selected in the target area, each typical position is used as a virtual well point, and the preset number of virtual well points can be obtained. The server may obtain raw seismic record data for each virtual well point from the raw seismic record data for the target area, and then process the raw seismic record data for each virtual well point to obtain angle gather seismic record data for each virtual well point. The typical position is selected according to actual conditions, and the embodiment of the invention is not limited. The execution subject of the pre-stack data processing method based on the virtual well provided by the embodiment of the invention comprises but is not limited to a server.

For example, the server performs prestack data preprocessing such as prestack denoising, multiple wave suppression, true amplitude restoration and the like on the original seismic record data of each virtual well point acquired in the field to obtain preprocessed original seismic record data of each virtual well point, and then performs angle gather extraction on the preprocessed original seismic record data of each virtual well point to obtain angle gather seismic record data of each virtual well point. The pre-stack denoising specific process may include: and (3) carrying out 2-by-4 stacking on the original seismic record data to obtain a common offset stacking super gather, wherein the common offset stacking super gather can effectively suppress random noise.

S102, acquiring virtual well data of each virtual well point according to the angle gather seismic record data of each virtual well point;

specifically, after obtaining the angle gather seismic record data of each virtual well point, the server may perform pre-stack seismic waveform inversion according to the angle gather seismic data of each virtual well point, so as to obtain the virtual well data of each virtual well point.

For example, the server establishes an initial geological model of each virtual well point according to velocity data corresponding to angle gather seismic record data of each virtual well point, then randomly generates n groups of random geological models of each virtual well point based on the initial geological model, then obtains synthetic seismic record data of each virtual well point according to the n groups of random geological models of each virtual well point and the zornillitz equation, and then obtains virtual well data of each virtual well point according to the synthetic seismic record data of each virtual well, the angle gather seismic record data of each virtual well point and a genetic algorithm.

S103, constructing an initial data volume model of the target area according to the virtual well data of the virtual well points with the preset number;

specifically, after obtaining the virtual well data of each virtual well point, the server may construct an initial data volume model of the target area according to the virtual well data of the preset number of virtual well points.

For example, the server may construct an initial data volume model of the target region based on the virtual well data and interpolation of the preset number of virtual well points.

And S104, obtaining a final pre-stack parameter data volume model of the target area according to the angle gather seismic record data of the target area and the initial data volume model of the target area.

Specifically, the server processes the raw seismic record data of the target area, and may obtain angle gather seismic record data of the target area. And the server can obtain a final pre-stack parameter data volume model of the target area according to the angle gather seismic record data of the target area and the initial data volume model of the target area, so that the pre-stack data of the target area is processed. The final prestack parameter data volume model of the target area comprises longitudinal wave velocity, transverse wave velocity and density parameters, multiple elastic parameter data volumes such as Poisson's ratio, shear modulus and Lame constant can be obtained by combining the longitudinal wave velocity, the transverse wave velocity and the density parameters with theoretical relations among rock elastic parameters, and then the reservoir and fluid of the target area can be predicted by combining the reservoir of the target area and characteristics of the reservoir containing fluid. The specific acquisition process of the angle gather seismic record data of the target area is similar to the specific acquisition process of the angle gather seismic record data of each virtual well point, and is not repeated here.

For example, the server may correct the initial data volume model of the target area according to the angle gather seismic recording data of the target area and a preset formula, so as to obtain a final pre-stack parameter data volume model of the target area. The preset formula is set according to actual experience, and the embodiment of the invention is not limited.

According to the pre-stack data processing method based on the virtual well, angle gather seismic record data of each virtual well point is obtained according to original seismic record data of each virtual well point of a target area, then virtual well data of each virtual well point is obtained according to the angle gather seismic record data of each virtual well point, an initial data volume model of the target area is constructed according to virtual well data of a preset number of virtual well points, a final pre-stack parameter data volume model of the target area is obtained according to the angle gather seismic record data of the target area and the initial data volume model of the target area, pre-stack parameter data of the target area are obtained through the virtual well data, and accuracy of the pre-stack parameter data of the target area is improved. In addition, pre-stack parameter data of the target area can be obtained without logging in the target area, so that the cost of geological exploration can be reduced.

Fig. 2 is a schematic flow chart of a virtual well-based pre-stack data processing method according to another embodiment of the present invention, and as shown in fig. 2, the obtaining virtual well data of each virtual well point according to the angle gather seismic record data of each virtual well point includes:

s1021, establishing an initial geological model of each virtual well point according to the velocity data corresponding to the angle gather seismic record data of each virtual well point;

specifically, velocity analysis is performed on the original seismic record data of each virtual well point, so that velocity data corresponding to the angle gather seismic record data of each virtual well point can be obtained, then, analysis processing is performed on the velocity data corresponding to the angle gather seismic record data of each virtual well point, so that an initial geological model of each virtual well point can be established, and the initial geological model is isotropic and elastic. Wherein the initial geological model comprises geological model parameters including compressional velocity V_pTransverse wave velocity V_sAnd a density parameter ρ.

S1022, randomly generating n groups of random geological models of each virtual well point based on the initial geological model;

in particular, the server, after obtaining the initial geological model, may randomly generate n sets of random geological models for each virtual well point, each set of geological model parameters including information about compressional velocity V_pRandom geological model of, with respect to shear wave velocity V_sAnd a random geological model with respect to the density parameter p. Therein, with respect to the longitudinal wave velocity V_pRandom geological model of (i.e. maintaining shear wave velocity V)_sAnd the density parameter rho is unchanged, and the longitudinal wave velocity V is randomly generated_pWith respect to the transverse wave velocity V_sAnd a random geological model for the density parameter ρ; about transverse wavesVelocity V_sIs to maintain the velocity V of longitudinal wave_pAnd the density parameter rho is unchanged, and the transverse wave velocity V is randomly generated_s(ii) a Stochastic geologic model, i.e. preserving shear velocity V, with respect to density parameter ρ_sKeeping the density parameter rho unchanged, and randomly generating the density parameter rho; n is a positive integer, and the value of n is set according to actual needs, which is not limited in the embodiments of the present invention.

S1023, obtaining synthetic seismic record data of each virtual well point according to the n groups of random geological models of each virtual well point and the Zorni Pritz equation;

specifically, after obtaining n sets of geological model parameters of each virtual well point, the server inputs the geological model parameters of the n sets of random geological models of each virtual well point into a Zoeppritz (Zoeppritz) equation, that is, the compressional velocity V of each set of random geological models_pTransverse wave velocity V_sAnd the density parameter p are input into the Zoeppritz equation, synthetic seismic record data of each virtual well point can be obtained, and the synthetic seismic record data comprises longitudinal wave velocity V_pTransverse wave velocity V_sAnd a density parameter ρ.

S1024, obtaining virtual well data of each virtual well point according to the synthetic seismic record data of each virtual well, the angle gather seismic record data of each virtual well point and a genetic algorithm.

Specifically, after obtaining synthetic seismic record data for each virtual well, the server may obtain virtual well data for each virtual well point according to the synthetic seismic record data for each virtual well, the angle gather seismic record data for each virtual well point, and a Genetic Algorithm (GA).

For example, the objective function for the GA is set to:

where i is 1,2,3 …, n, i represents the ith group member, which in the present embodiment refers to the number of angle gather seismic records of the virtual well pointData or synthetic seismic record data, nt representing the number of seismic trace time sample points, seis_iAn ith population member, syn, in the angle gather seismic record data representing the virtual well point_jiSynthetic seismic record data representing a jth stochastic model of an ith population member of the virtual well point. n represents the number of population samples, and the larger n, the more search points, the higher the search efficiency should be, but in practice, the more search points are added, which also increases the amount of calculation, so that in actual use, the appropriate number of population samples n needs to be selected. The objective function objects are a standard for describing an optimal solution, and are also a basis for calculating fitness, and generally a standard is a fitting degree or an error between a calculated value and an actually measured value. And setting the inversion accuracy epsilon as a convergence ending condition, wherein the inversion accuracy epsilon is set according to actual experience, and the embodiment of the invention is not limited.

Determining longitudinal wave velocity V of geological model parameter_pTransverse wave velocity V_sAnd a search range and a search interval of the density parameter rho, performing integer coding on the geological model parameter according to the search range and the search interval, setting j to be 0, and generating an initial random model overall P for fitting the geological model according to the geological model parameter_jPopulation of stochastic model P_jComprising three types of stochastic models, i.e. with respect to the velocity V of longitudinal waves_pRandom geological model of, with respect to shear wave velocity V_sAnd a random geological model with respect to the density parameter p. And (3) collecting the angle traces of the random model total of each virtual well into a synthetic seismic record, namely synthetic seismic record data of each virtual well.

According to the search range and the search interval, the value number of each geological model parameter is determined to be n, all geological model parameters are subjected to integer coding for saving space, and the following conditions are met:

X＝X_min+D_xCode (2)

Code＝(X-X_min)/D_x (3)

wherein X represents a geological model parameter, X_minRepresenting the minimum of the parameter, Code representing the Code value, D_xIndicating the search accuracy of the parameter X. Coded for multi-parameter, complex non-linear problemsThe quality directly affects the calculation efficiency. The embodiment of the invention effectively reduces the length of the code by adopting an integer coding scheme and accelerates the calculation speed. [ X ]_min,X_max]For a given range of values of the address model parameter X, X_minAnd X_maxThe value of (a) is set according to actual needs, and the embodiment of the invention is not limited. It can be understood that X is the velocity V of the longitudinal wave_pTransverse wave velocity V_sOr a density parameter p.

Suppose that n random models are generated, i.e. with respect to the velocity V of the longitudinal wave_pRandom geological model of, about, transverse wave velocity V_sN random geological models and n random geological models with respect to the density parameter p, respectively.

And (3) comparing the synthetic seismic record data of each virtual well with the angle gather seismic record data of each virtual well point, and calculating an objective function value through a formula (1). Corner gather seismic record data seis and synthetic seismic record data syn_jThe matching degree between the two is called the fitting degree of the model, if the random model is far away from the actual situation, the angle gather seismic record data seis and the corresponding synthetic seismic record data syn_jThe match will be poor. Conversely, if the selected stochastic model is close to reality, the corner gather seismic record data seis and the corresponding synthetic seismic record data syn are made_jCan be well matched.

The fitness function can be obtained by conversion according to the objective function value, and the fitness function fitness is calculated as follows:

wherein i is 1,2,3 …, n, objects_iExpressing the value of the objective function of the ith population member, sigma the variance of the population objective function, fitness_iRepresenting the fitness value of the ith population member. The fitness function is obtained by converting the objective function and is used for describing the function of the individual adaptive survival ability.

Comparing synthetic seismic record data syn for each virtual well_jAnd the angle of each virtual well pointGather seismic data sei, calculate and save objective function value objects_iAnd converting the objective function value to obtain a fitness function value fitness_i；

If objects_iObjects satisfying the end condition_iIf the parameter is less than epsilon, ending the measurement of the longitudinal wave velocity V of the geological model parameter_pTransverse wave velocity V_sAnd processing the density parameter rho and outputting the result, thereby obtaining the virtual well data of the virtual well point. If the end condition is not met, the overall random model P of the virtual well is calculated according to the value of the objective function and the fitness function transformed by the objective function_jPerforming regeneration, crossover and mutation operations to update P_jLet j equal j +1, generate a new random model population P_jAnd recalculating the objective function value until the objective function value meets the end condition.

On the basis of the foregoing embodiments, further, the constructing an initial data volume model of the target region according to the virtual well data of the preset number of virtual well points includes:

and constructing an initial data volume model of the target area based on the virtual well data of the preset number of virtual well points and an interpolation method.

Specifically, after the server obtains the virtual well data of each virtual well point, interpolation is performed by selecting methods such as kriging and least squares under the constraint of an interpretation horizon according to the virtual well data of the preset number of virtual well points, an initial data volume model of the target area is constructed, and each position point on the initial data volume model corresponds to a longitudinal wave velocity V_pTransverse wave velocity V_sAnd a density parameter ρ. When the initial data volume model is constructed, the distance and the number of interpolation are set according to parameters of actual seismic records, and the embodiment of the invention is not limited.

On the basis of the foregoing embodiments, further, the obtaining a final pre-stack parameter data volume model of the target area according to the angle gather seismic recording data of the target area and the initial data volume model of the target area includes:

and correcting the initial data volume model of the target area according to the angle gather seismic record data of the target area and a preset formula to obtain a final pre-stack parameter data volume model of the target area.

Specifically, the server calculates a deviation between the angle gather seismic record data of the target area and an initial data volume model of the target area according to the preset formula, and if the change rate of the deviation is smaller than a set value, the initial data volume model of the target area is used as a final pre-stack parameter data volume model of the target area. And if the change rate of the deviation is greater than or equal to a set value, adjusting the initial data volume model of the target area, recalculating the deviation between the angle gather seismic record data of the target area and the adjusted initial data volume model of the target area until the change rate of the recalculated deviation is less than the set value or the recalculation times reach a preset number, and taking the initial data volume model of the target area which is adjusted for the last time as the final pre-stack parameter data volume model of the target area. The set value is set according to actual experience, for example, the set value is between 0.05 and 0.1, and the embodiment of the invention is not limited; the preset times are set according to actual experience, for example, the preset times are 10 times, and the embodiment of the present invention is not limited.

For example, the preset formula is:

wherein J (L) represents the deviation of the angle gather seismic recording data of the target area from the calculated data volume model of the target area, W_θiRepresenting an angle of incidence of theta_i(i-1, 2,3, …, M),angle gather seismic recording data representing the target area,C₃＝c₃，c₁＝1+tan²θ，c₂＝-8γ²sin²θ，L＝[L_P L_S L_D]^T，L_p＝ln(Z_p)，L_S＝ln(Z_S)＝kln(Z_p)+k_c+ΔL_S，L_D＝ln(ρ)＝mln(Z_p)+m_c+ΔL_D，k_cindicating data ln (Z)_p) And ln (Z)_S) Intercept of fitted straight line, m_cIndicating data ln (Z)_p) And the intercept of a line fitted with ln (p), Z_p＝V_pP, μ is a regularization parameter and 0.7 < μ < 1.3,is a potential function andt is a dimensionless quantity, M represents the total number of angle gathers, Q represents the number of lithological layers,ΔL_srepresenting the influence factor of oil and gas in a rock fluid, Δ L, related to transverse waves_DRepresenting the density-related hydrocarbon-bearing influence factor of the rock fluid. Wherein the computed data volume model of the target region comprises an initial data volume model and an adjusted initial data volume model of the target region.

In the above predetermined formula, k, m, Δ L_sAnd Δ L_DAs unknowns, with respect to k, m, Δ L_sAnd Δ L_DThe following expressions exist:

ln(Z_S)＝kln(Z_p)+k_c+ΔL_S (3)

ln(ρ)＝mln(Z_p)+m_c+ΔL_D (4)

wherein, ln (Z)_S)＝ln(Z_p) + ln (γ). Equation (3) can be viewed as relating to ln (Z)_P) And ln (Z)_S) Due to the longitudinal wave velocity V in the initial data volume model of the target region_pTransverse wave velocity V_sAnd density parameter ρ is known, based on formula Z_p＝V_pρ can be used to obtain ln (Z)_P) Based on ln (Z)_S)＝ln(Z_p) + ln (γ) andcan find ln (Z)_S) Then, k can be obtained by fitting data to equation (3). In obtaining ln (Z)_P) And ln (Z)_S) Then, in a Cartesian coordinate system, in ln (Z)_P) As abscissa and in ln (Z)_S) The data points, which are the ordinate, are distributed in two blocks: the method comprises the steps that data points of a dense area are background values, namely the dense area is a background value distribution area, the data points of a sparse area are abnormal values caused by oil and gas, namely the sparse area is an abnormal value distribution area caused by oil and gas, fitting is carried out on the data points of the dense area to obtain a first linear equation, fitting is carried out on the data points of the sparse area to obtain a second linear equation, and the absolute value of the difference between the intercept value of the first linear equation on the ordinate and the intercept value of the second linear equation on the ordinate is delta L_s. Similarly, m and Δ L can be obtained based on the formula (4)_D。

K, m, Δ L_sAnd Δ L_DThe longitudinal wave velocity V of the current initial data volume model can be obtained by substituting the longitudinal wave velocity V into the preset formula_pTransverse wave velocity V_sAnd J (L) corresponding to the density parameter rho, comparing the change rate of the J (L) with the set value, and if the change rate of the J (L) is more than or equal to the set value, then at the current Z_PAdding a value of delta Zp which can be the corresponding Z_p1% of the initial value, and then recalculating j (l) until the rate of change of the recalculated j (l) is less than the set value or the number of recalculations of j (l) is greater than the preset number. The rate of change of the recalculated J (L) is less than the set value or recalculatedAnd J (L) times are more than the modified initial data volume model corresponding to the preset times, namely the final pre-stack parameter data volume model of the target area.

Fig. 3 is a schematic structural diagram of a pre-stack data processing apparatus based on a virtual well according to an embodiment of the present invention, and as shown in fig. 3, the pre-stack data processing apparatus based on a virtual well according to an embodiment of the present invention includes a first obtaining unit 301, a second obtaining unit 302, a building unit 303, and a third obtaining unit 304, where:

the first obtaining unit 301 is configured to obtain angle gather seismic record data of each virtual well point according to the original seismic record data of each virtual well point of the target area; wherein the virtual well points have a preset number; the second obtaining unit 302 is configured to obtain virtual well data of each virtual well point according to the angle gather seismic record data of each virtual well point; the building unit 303 is configured to build an initial data volume model of the target area according to the virtual well data of the preset number of virtual well points; the third obtaining unit 304 is configured to obtain a final pre-stack parametric data volume model of the target area according to the angle gather seismic recording data of the target area and the initial data volume model of the target area.

Specifically, original seismic record data of a target area are acquired through field acquisition, a preset number of typical positions are selected in the target area, each typical position is used as a virtual well point, and the preset number of virtual well points can be obtained. The first obtaining unit 301 may obtain raw seismic record data of each virtual well point from the raw seismic record data of the target area, and then process the raw seismic record data of each virtual well point, so as to obtain angle gather seismic record data of each virtual well point. The typical position is selected according to actual conditions, and the embodiment of the invention is not limited.

After obtaining the angle gather seismic record data of each virtual well point, the second obtaining unit 302 may perform pre-stack seismic waveform inversion according to the angle gather seismic data of each virtual well point, so as to obtain the virtual well data of each virtual well point.

After obtaining the virtual well data of each of the virtual well points, the constructing unit 303 may construct an initial data volume model of the target region according to the virtual well data of the preset number of virtual well points.

The third obtaining unit 304 processes the raw seismic record data of the target area, and may obtain angle gather seismic record data of the target area. The third obtaining unit 304 may obtain a final pre-stack parameter data volume model of the target area according to the angle gather seismic recording data of the target area and the initial data volume model of the target area, so as to implement processing of pre-stack data of the target area. The final prestack parameter data volume model of the target area comprises longitudinal wave velocity, transverse wave velocity and density parameters, multiple elastic parameter data volumes such as Poisson's ratio, shear modulus and Lame constant can be obtained by combining the longitudinal wave velocity, the transverse wave velocity and the density parameters with theoretical relations among rock elastic parameters, and then the reservoir and fluid of the target area can be predicted by combining the reservoir of the target area and characteristics of the reservoir containing fluid. The specific acquisition process of the angle gather seismic record data of the target area is similar to the specific acquisition process of the angle gather seismic record data of each virtual well point, and is not repeated here.

According to the pre-stack data processing device based on the virtual well, angle gather seismic record data of each virtual well point is obtained according to the original seismic record data of each virtual well point of a target area, then virtual well data of each virtual well point is obtained according to the angle gather seismic record data of each virtual well point, an initial data volume model of the target area is constructed according to the virtual well data of a preset number of virtual well points, and a final pre-stack parameter data volume model of the target area is obtained according to the angle gather seismic record data of the target area and the initial data volume model of the target area, so that pre-stack parameter data of the target area are obtained through the virtual well data, and accuracy of the pre-stack parameter data of the target area is improved. In addition, pre-stack parameter data of the target area can be obtained without logging in the target area, so that the cost of geological exploration can be reduced.

Fig. 4 is a schematic structural diagram of a pre-stack data processing apparatus based on a virtual well according to another embodiment of the present invention, and as shown in fig. 4, the second obtaining unit 302 includes a creating subunit 3021, a generating subunit 3022, a first obtaining subunit 3023, and a second obtaining subunit 3024, where:

the establishing subunit 3021 is configured to establish an initial geological model of each virtual well point according to velocity data corresponding to the angle gather seismic record data of each virtual well point; the generation subunit 3022 is configured to randomly generate n sets of geomodel parameters for each virtual well point based on the initial geomodel; the first obtaining subunit 3023 is configured to obtain synthetic seismic record data of each virtual well point according to the n sets of geological model parameters of each virtual well point and the zornillitz equation; the second obtaining subunit 3024 is configured to obtain virtual well data for each virtual well point from the synthetic seismic record data for each virtual well, the angle gather seismic record data for each virtual well point, and the genetic algorithm.

Specifically, the velocity analysis is performed on the original seismic record data of each virtual well point, so that velocity data corresponding to the angle gather seismic record data of each virtual well point can be obtained, the establishing subunit 3021 performs analysis processing on the velocity data corresponding to the angle gather seismic record data of each virtual well point, and an initial geological model of each virtual well point can be established, where the initial geological model is isotropic elastic. Wherein the initial geological model comprises geological model parameters including compressional velocity V_pTransverse wave velocity V_sAnd a density parameter ρ.

After obtaining the initial geological model, the generation subunit 3022 may randomly generate n sets of random geological models for each virtual well point, each set of geological model parameters including information about compressional velocity V_pRandom geological model of, with respect to shear wave velocity V_sAnd a random geological model with respect to the density parameter p. Therein, with respect to the longitudinal wave velocity V_pRandom geological model of (i.e. maintaining shear wave velocity V)_sAnd density parameter ρ notRandomly generating longitudinal wave velocity V_pWith respect to the transverse wave velocity V_sAnd a random geological model for the density parameter ρ; with respect to transverse wave velocity V_sIs to maintain the velocity V of longitudinal wave_pAnd the density parameter rho is unchanged, and the transverse wave velocity V is randomly generated_s(ii) a Stochastic geologic model, i.e. preserving shear velocity V, with respect to density parameter ρ_sKeeping the density parameter rho unchanged, and randomly generating the density parameter rho; n is a positive integer, and the value of n is set according to actual needs, which is not limited in the embodiments of the present invention.

After obtaining the n sets of geomodel parameters for each virtual well point, the first obtaining subunit 3023 inputs the geomodel parameters of the n sets of random geomodels for each virtual well point into the Zoeppritz (Zoeppritz) equation, i.e., the compressional velocity V of each set of random geomodels_pTransverse wave velocity V_sAnd the density parameter p are input into the Zoeppritz equation, synthetic seismic record data of each virtual well point can be obtained, and the synthetic seismic record data comprises longitudinal wave velocity V_pTransverse wave velocity V_sAnd a density parameter ρ.

After obtaining synthetic seismic record data for each virtual well, the second obtaining subunit 3024 may obtain virtual well data for each virtual well point according to the synthetic seismic record data for each virtual well, the angle gather seismic record data for each virtual well point, and a Genetic Algorithm (GA).

On the basis of the foregoing embodiments, further, the building unit 303 is specifically configured to:

and constructing an initial data volume model of the target area based on the virtual well data of the preset number of virtual well points and an interpolation method.

Specifically, after obtaining the virtual well data of each virtual well point, the constructing unit 303 performs interpolation by using interpolation methods such as kriging and least squares under the constraint of an interpretation horizon according to the virtual well data of the preset number of virtual well points, to construct an initial data volume model of the target region, where each position point on the initial data volume model corresponds to a longitudinal wave velocity V_pTransverse wave velocity V_sAnd a density parameter ρ. When the initial data volume model is constructed, the distance and the number of the interpolation are set according to actual needs, and the embodiment of the invention is not limited.

On the basis of the foregoing embodiments, further, the third obtaining unit 304 is specifically configured to:

and correcting the initial data volume model of the target area according to the angle gather seismic record data of the target area and a preset formula to obtain a final pre-stack parameter data volume model of the target area.

Specifically, the third obtaining unit 304 calculates a deviation between the angle gather seismic record data of the target area and the initial data volume model of the target area according to the preset formula, and if a change rate of the deviation is smaller than a set value, the initial data volume model of the target area is used as the final pre-stack parameter data volume model of the target area. And if the change rate of the deviation is larger than or equal to a set value, adjusting the initial data volume model of the target area, recalculating the deviation between the angle gather seismic record data of the target area and the initial data volume model of the target area until the change rate of the recalculated deviation is smaller than the set value or the recalculation times reach a preset number, and taking the initial data volume model of the target area which is adjusted last time as the final pre-stack parameter data volume model of the target area. The set value is set according to actual experience, for example, the set value is between 0.05 and 0.1, and the embodiment of the invention is not limited; the preset times are set according to actual experience, for example, the preset times are 10 times, and the embodiment of the present invention is not limited.

The embodiment of the apparatus provided in the embodiment of the present invention may be specifically configured to execute the processing flows of the above method embodiments, and the functions of the apparatus are not described herein again, and refer to the detailed description of the above method embodiments.

Fig. 5 is a schematic physical structure diagram of an electronic device according to an embodiment of the present invention, and as shown in fig. 5, the electronic device may include: a processor (processor)501, a communication Interface (Communications Interface)502, a memory (memory)503, and a communication bus 504, wherein the processor 501, the communication Interface 502, and the memory 503 are configured to communicate with each other via the communication bus 504. The processor 501 may call logic instructions in the memory 503 to perform the following method: obtaining angle gather seismic record data of each virtual well point according to the original seismic record data of each virtual well point of the target area; wherein the virtual well points have a preset number; acquiring virtual well data of each virtual well point according to the angle gather seismic record data of each virtual well point; constructing an initial data volume model of the target area according to the virtual well data of the virtual well points with the preset number; and obtaining a final pre-stack parameter data volume model of the target area according to the angle gather seismic record data of the target area and the initial data volume model of the target area.

In addition, the logic instructions in the memory 503 may be implemented in the form of software functional units and stored in a computer readable storage medium when the logic instructions are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.

The present embodiment discloses a computer program product comprising a computer program stored on a non-transitory computer readable storage medium, the computer program comprising program instructions which, when executed by a computer, enable the computer to perform the method provided by the above-mentioned method embodiments, for example, comprising: obtaining angle gather seismic record data of each virtual well point according to the original seismic record data of each virtual well point of the target area; wherein the virtual well points have a preset number; acquiring virtual well data of each virtual well point according to the angle gather seismic record data of each virtual well point; constructing an initial data volume model of the target area according to the virtual well data of the virtual well points with the preset number; and obtaining a final pre-stack parameter data volume model of the target area according to the angle gather seismic record data of the target area and the initial data volume model of the target area.

The present embodiment provides a computer-readable storage medium, which stores a computer program, where the computer program causes the computer to execute the method provided by the above method embodiments, for example, the method includes: obtaining angle gather seismic record data of each virtual well point according to the original seismic record data of each virtual well point of the target area; wherein the virtual well points have a preset number; acquiring virtual well data of each virtual well point according to the angle gather seismic record data of each virtual well point; constructing an initial data volume model of the target area according to the virtual well data of the virtual well points with the preset number; and obtaining a final pre-stack parameter data volume model of the target area according to the angle gather seismic record data of the target area and the initial data volume model of the target area.

As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may 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 instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In the description herein, reference to the description of the terms "one embodiment," "a particular embodiment," "some embodiments," "for example," "an example," "a particular example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.