CN-122017957-A - Method, medium and system for predicting regional porosity

CN122017957ACN 122017957 ACN122017957 ACN 122017957ACN-122017957-A

Abstract

The invention relates to the field of petroleum exploration, in particular to a method, medium and system for predicting regional porosity, wherein the method comprises the steps of establishing a prior model of porosity parameters based on a single well porosity curve in a region to be predicted, performing wave equation forward modeling on a petrophysical model and a convolution equation of the region to be evaluated, and establishing a likelihood function model based on the relation between simulation data of the wave equation forward modeling and actual earthquake response signals; and solving the prediction model to obtain a porosity distribution result of the region to be evaluated. The method realizes quantitative prediction of the porosity parameters of the region, and can predict the favorable region of the reservoir according to the predicted porosity plan. In addition, due to the beneficial limit of regional porosity, the prediction result of the method can be used for further beneficial region division of the reservoir, analyzing the beneficial range of the reservoir and reducing the exploration risk.

Inventors

HE GANG
LUO FUSONG
HAN BO
LI YULAN
DING WEI
Bahetiyar Ainivar

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西北油田分公司

Dates

Publication Date: 20260512
Application Date: 20241111

Claims (10)

1. A method for predicting regional porosity, comprising the steps of: S1, establishing a prior model of porosity parameters based on a single well porosity curve in a region to be predicted, performing wave equation forward modeling on a petrophysical model and a convolution equation of the region to be evaluated, and establishing a likelihood function model based on the relation between simulation data of the wave equation forward modeling and actual earthquake response signals; Taking a posterior function model formed by the product of the prior model and the likelihood function model as a prediction model for representing the relation between porosity and seismic wave signals; S2, according to the seismic wave response signals of the region to be evaluated and the single well porosity curve, obtaining a porosity distribution result of the region to be evaluated by solving the prediction model.
2. A method for predicting regional porosity according to claim 1, wherein the prior model for establishing the porosity parameter is specifically to establish the corresponding seismic noise gaussian function by taking the seismic noise signal as the noise distribution as the mean value 0; The current seismic noise gaussian function is converted into a porosity parameter gaussian function by taking the principle that the porosity parameter meets the seismic noise characteristics, so that the current porosity parameter Gao Sihan is counted as a priori model.
3. A method for predicting regional porosity in accordance with claim 1, wherein the posterior function model is represented by the expression: Where m represents the porosity, d represents the seismic response data, i represents the number of porosity prediction points in the region to be evaluated, N represents the total number of porosity prediction points, P (m|d) represents the posterior function, G represents the convolution wavelet matrix, σ represents the covariance matrix of the seismic noise, σ m represents the covariance matrix of the porosity, Δm i represents the ith porosity variation, and m T represents the porosity transpose matrix.
4. A method for predicting regional porosity according to claim 3, wherein step S2 comprises the steps of: S21, carrying out maximum posterior probability solution on the posterior function model according to the seismic wave response signals of the region to be evaluated and single well porosity data in the single well porosity curve to obtain a porosity expected value; S22, converting the posterior function model into an objective function representing the relation between the porosity unit change amount and the earthquake response value unit change amount based on the porosity expected value; S23, solving an objective function by adopting an MCMC method according to the seismic wave response signal of the region to be evaluated and the single well porosity data to obtain a distribution prediction result of the porosity unit variation; S24, obtaining a porosity distribution result of the region to be evaluated based on the single well porosity data and the distribution prediction result of the porosity unit variation.
5. The method for predicting regional porosity of claim 4, wherein the objective function in step S22 is represented by: wherein I represents a priori constraint matrix, G T is a transformation matrix of a convolution wavelet matrix, and Deltad is unit variation of an actual seismic response value.
6. A method for predicting regional porosity in accordance with any one of claims 1-5, wherein in step S1 the single well porosity curve is obtained by: for a region to be evaluated with logging data, calculating a single well porosity curve based on the logging curve; for the non-porosity zone, a single well porosity curve is calculated based on the petrophysical model.
7. A method for predicting regional porosity according to any one of claims 1-5, wherein in step S1, the seismic response signals and the single well porosity curve are subjected to standard pre-processing including outlier processing, inter-well consistency correction and well shock calibration.
8. A computer readable storage medium, characterized in that the computer readable storage medium stores a computer program which, when executed by a processor, implements a method for predicting regional porosity as claimed in any one of claims 1-7.
9. A system for predicting regional porosity, characterized in that it is adapted to a method for predicting regional porosity according to any one of claims 1-7, comprising: a prediction model building module configured to build a prediction model characterizing a relationship between porosity and seismic wave signals based on a single well porosity curve within a region to be predicted; And the porosity prediction module is configured to obtain a porosity distribution result of the region to be evaluated by solving the prediction model according to the seismic wave response signal of the region to be evaluated and the single well porosity curve.
10. The system for predicting regional porosity of claim 9, wherein the system for predicting regional porosity further comprises: A data preprocessing module configured to perform standard preprocessing of the seismic response signals and the single well porosity curve, the standard preprocessing including outlier processing, inter-well consistency correction, and well shock calibration.

Description

Method, medium and system for predicting regional porosity Technical Field The invention relates to the field of petroleum exploration, in particular to a method, medium and system for predicting regional porosity. Background The porosity and the permeability are the basic characteristics of a reservoir, the porosity is one of the important parameters of reservoir physical properties, and the distribution rules of the porosity and the permeability control the distribution state of underground oil gas, the oil gas reserves and the productivity and the establishment of an oil gas field development scheme have profound effects, so the porosity and the permeability are the essential parameters in the oil gas field development process. Numerous experimental and exploration results have demonstrated that formations are heterogeneous, particularly lithologic formations, with more pronounced heterogeneity, so that the response of a well log to physical parameters (e.g., porosity, saturation, permeability, etc.) is necessarily a complex function that is nonlinear in nature and cannot be expressed exactly by relational expressions. With the development of exploration, it is necessary to predict physical parameters such as porosity more precisely. Thus, a more accurate porosity prediction scheme is needed. Disclosure of Invention To avoid the above problems of the prior art, it is an object of the present invention to provide a method, medium and system for predicting regional porosity. In order to achieve the above purpose, the invention provides a method for predicting regional porosity, comprising the following steps: S1, establishing a prior model of porosity parameters based on a single well porosity curve in a region to be predicted, performing wave equation forward modeling on a petrophysical model and a convolution equation of the region to be evaluated, and establishing a likelihood function model based on the relation between simulation data of the wave equation forward modeling and actual earthquake response signals; Forming a posterior function model by using the product of the prior model and the likelihood function model as a prediction model for representing the relation between the porosity and the seismic wave signal; S2, according to the seismic wave response signals of the region to be evaluated and the single well porosity curve, obtaining a porosity distribution result of the region to be evaluated by solving the prediction model. The invention further provides that the prior model for establishing the porosity parameter is specifically that a corresponding seismic noise gaussian function is established by taking a seismic noise signal as a mode that noise distribution is 0 as a mean value; The current seismic noise gaussian function is converted into a porosity parameter gaussian function by taking the principle that the porosity parameter meets the seismic noise characteristics, so that the current porosity parameter Gao Sihan is counted as a priori model. The invention is further arranged that the posterior function model is represented by the following expression: Where m represents the porosity, d represents the seismic response data, i represents the number of porosity prediction points in the region to be evaluated, N represents the total number of porosity prediction points, P (m|d) represents the posterior function, G represents the convolution wavelet matrix, σ represents the covariance matrix of the seismic noise, σ m represents the covariance matrix of the porosity, Δm i represents the ith porosity variation, and m T represents the porosity transpose matrix. The invention further provides that the step S2 specifically comprises the following steps: S21, carrying out maximum posterior probability solution on the posterior function model according to the seismic wave response signals of the region to be evaluated and single well porosity data in the single well porosity curve to obtain a porosity expected value; S22, converting the posterior function model into an objective function representing the relation between the porosity unit change amount and the earthquake response value unit change amount based on the porosity expected value; S23, solving an objective function by adopting an MCMC method according to the seismic wave response signal of the region to be evaluated and the single well porosity data to obtain a distribution prediction result of the porosity unit variation; S24, obtaining a porosity distribution result of the region to be evaluated based on the single well porosity data and the distribution prediction result of the porosity unit variation. The present invention is further configured such that the objective function in step S22 is represented by the following formula: wherein I represents a priori constraint matrix, G T is a transformation matrix of a convolution wavelet matrix, and Deltad is unit variation of an actual seismic response value. The invention is furthe