CN-122018001-A - Pre-stack seismic inversion method, device, electronics and storage medium

CN122018001ACN 122018001 ACN122018001 ACN 122018001ACN-122018001-A

Abstract

The pre-stack seismic inversion method, device, electronic equipment and storage medium provided by the application are capable of improving the accuracy of inversion results by acquiring a pre-stack time migration angle gather of a reservoir in a target area, sequentially determining each grid point in the reservoir based on a random path, determining the lithology of the grid point based on a lithology training diagram of the target area, determining a target probability function based on the correspondence between the lithology and a pre-established probability function of different lithology and elastic parameter distribution, randomly sampling based on the target probability function to obtain the elastic parameter of each time sampling point of the grid point, determining a forward seismic record of each time sampling point based on the elastic parameter of each time sampling point, and determining the elastic parameter of each time sampling point of the grid point based on the forward seismic record of each time sampling point and the pre-stack time migration angle gather corresponding to each time sampling point.

Inventors

CHEN TIANSHENG
JI YUXIN
LIN TIAN
DUAN NAN

Assignees

中国石油化工股份有限公司
中国石油化工股份有限公司石油勘探开发研究院

Dates

Publication Date: 20260512
Application Date: 20241112

Claims (10)

1. A method of pre-stack seismic inversion comprising: acquiring a prestack time offset angle gather of a reservoir in a target area; sequentially determining each grid point in the reservoir based on a random path, and determining the lithology of the grid points based on a lithology training diagram of the target area; Determining a target probability function based on the correspondence between the lithofacies and the probability functions of different lithofacies and elastic parameter distribution, which are established in advance; randomly sampling based on the target probability function to obtain an elastic parameter of each time sampling point of the grid point; Determining forward seismic records for each time sampling point based on the elastic parameters of each time sampling point; and determining the elasticity parameter of each time sampling point of the grid point based on the forward seismic record of each time sampling point and the prestack time offset angle gather corresponding to each time sampling point.
2. The method of claim 1, wherein said determining elastic parameters for each time sample point of said grid points based on said forward seismic record for each time sample point and said pre-stack time offset angle gathers corresponding to respective time sample points comprises: determining an error value of an objective function based on the forward seismic record of each time sampling point and the prestack time offset angle gather corresponding to each time sampling point, wherein the objective function is the least square sum of the forward seismic record and the prestack time offset angle gather; and outputting the elastic parameter of each time sampling point under the condition that the error value is smaller than the error threshold value.
3. The method according to claim 2, wherein the method further comprises: updating the lithology of the grid points under the condition that the error value is larger than the error threshold value, and performing iterative computation to obtain updated forward seismic records of each time sampling point; determining an error value of an objective function based on the updated forward seismic record for each time sampling point and the pre-stack time offset angle gathers corresponding to each time sampling point; and under the condition that the error value is smaller than the error threshold value or the iterative computation times reach the iterative computation times threshold value, determining the elasticity parameter corresponding to the forward seismic record of each updated time sampling point as the elasticity parameter of each time sampling point of the grid point.
4. The method of claim 1, wherein the determining the lithology of the grid points based on the lithology training map of the target region comprises: Calculating the similarity between the data events in the lithology training graph and the data events of the grid points by adopting a direct sampling multipoint geostatistical simulation algorithm; and determining the lithofacies corresponding to the lithofacies training diagrams with the similarity larger than the similarity threshold as the lithofacies of the grid points.
5. The method of claim 1, wherein determining forward seismic records for each time sample point based on the elasticity parameters for each time sample point comprises: Determining reflection coefficients of different incident angles corresponding to each time sampling point based on the elasticity parameters of each time sampling point; And carrying out convolution on reflection coefficients and wavelets of different incident angles corresponding to each time sampling point to obtain forward seismic records of each time sampling point.
6. The method of claim 5, wherein determining the reflection coefficient for each time sampling point based on the elasticity parameter for each time point comprises: Inputting the elasticity parameters of each time sampling point into a calculation model, and determining the reflection coefficient corresponding to each time sampling point, wherein the calculation model comprises: R(θ)=A+B sin 2 θ; Wherein, the vs, The average values of the longitudinal wave speed, the transverse wave speed and the density at the two sides of the interface are respectively shown, and Deltavp, deltavs and Deltaρ are the differences among the longitudinal wave speed, the transverse wave speed and the density at the two sides of the interface.
7. The method according to claim 1, wherein the method further comprises: Acquiring logging data of a target area; and establishing a corresponding relation between probability functions of different lithofacies and elastic parameter distribution based on the logging data.
8. A pre-stack seismic inversion apparatus, comprising: The acquisition module is used for acquiring a prestack time offset angle gather of the reservoir stratum in the target area; A first determining module, configured to sequentially determine each grid point in the reservoir based on a random path, and determine a lithology of the grid point based on a lithology training graph of the target area; The second determining module is used for determining a target probability function based on the corresponding relation between the lithofacies and the probability functions of different lithofacies and elastic parameter distribution, which are established in advance; The obtaining module is used for randomly sampling based on the target probability function to obtain the elastic parameter of each time sampling point of the grid point; The third determining module is used for determining forward seismic records of each time sampling point based on the elastic parameter of each time sampling point; And the fourth determining module is used for determining the elasticity parameter of each time sampling point of the grid point based on the forward seismic record of each time sampling point and the prestack time offset angle gather corresponding to each time sampling point.
9. An electronic device comprising a memory and a processor, the memory having stored thereon a computer program which, when executed by the processor, performs the pre-stack seismic inversion method of any one of claims 1 to 7.
10. A storage medium storing a computer program executable by one or more processors for implementing a pre-stack seismic inversion method as claimed in any one of claims 1 to 7.

Description

Pre-stack seismic inversion method, device, electronics and storage medium Technical Field The application relates to the technical field of oil and gas geophysics, in particular to a pre-stack seismic inversion method, a pre-stack seismic inversion device, electronic equipment and a storage medium. Background The exploration and development of oil and gas fields are mostly carried out on reservoirs, and reservoir modeling and random inversion methods are also hot problems of concern in the industry and academia. Geostatistical inversion is an inversion method combining geologic modeling and seismic inversion based on well logging data, seismic data, and geologic data. The conventional geostatistical inversion is mostly poststack inversion based on traditional geostatistics, and the reservoir morphology depiction and accuracy of inversion results are to be improved. Disclosure of Invention In order to solve the problems, the application provides a pre-stack seismic inversion method, a device, electronic equipment and a storage medium, which can improve the accuracy of inversion results obtained by inversion. The application provides a pre-stack seismic inversion method, which comprises the following steps: acquiring a prestack time offset angle gather of a reservoir in a target area; sequentially determining each grid point in the reservoir based on a random path, and determining the lithology of the grid points based on a lithology training diagram of the target area; Determining a target probability function based on the correspondence between the lithofacies and the probability functions of different lithofacies and elastic parameter distribution, which are established in advance; randomly sampling based on the target probability function to obtain an elastic parameter of each time sampling point of the grid point; Determining forward seismic records for each time sampling point based on the elastic parameters of each time sampling point; and determining the elasticity parameter of each time sampling point of the grid point based on the forward seismic record of each time sampling point and the prestack time offset angle gather corresponding to each time sampling point. In some embodiments, the determining the elasticity parameter of each time sampling point of the grid point based on the forward seismic record of each time sampling point and the pre-stack time offset angle gather corresponding to each time sampling point includes: determining an error value of an objective function based on the forward seismic record of each time sampling point and the prestack time offset angle gather corresponding to each time sampling point, wherein the objective function is the least square sum of the forward seismic record and the prestack time offset angle gather; and outputting the elastic parameter of each time sampling point under the condition that the error value is smaller than the error threshold value. In some embodiments, the method further comprises: updating the lithology of the grid points under the condition that the error value is larger than the error threshold value, and performing iterative computation to obtain updated forward seismic records of each time sampling point; determining an error value of an objective function based on the updated forward seismic record for each time sampling point and the pre-stack time offset angle gathers corresponding to each time sampling point; and under the condition that the error value is smaller than the error threshold value or the iterative computation times reach the iterative computation times threshold value, determining the elasticity parameter corresponding to the forward seismic record of each updated time sampling point as the elasticity parameter of each time sampling point of the grid point. In some embodiments, the determining the lithology of the grid points based on the lithology training map of the target region comprises: Calculating the similarity between the data events in the lithology training graph and the data events of the grid points by adopting a direct sampling multipoint geostatistical simulation algorithm; and determining the lithofacies corresponding to the lithofacies training diagrams with the similarity larger than the similarity threshold as the lithofacies of the grid points. In some embodiments, the determining the forward seismic record for each time sample point based on the elasticity parameters for each time sample point includes: Determining reflection coefficients of different incident angles corresponding to each time sampling point based on the elasticity parameters of each time sampling point; And carrying out convolution on reflection coefficients and wavelets of different incident angles corresponding to each time sampling point to obtain forward seismic records of each time sampling point. In some embodiments, the determining the reflection coefficient corresponding to each time sampling point based on the elast