Reservoir parameter prediction method and system based on Bayesian classification

A technology based on Bayesian classification and reservoir parameters, applied in the direction of specific mathematical models, electrical digital data processing, special data processing applications, etc., can solve the problem that the likelihood function is difficult to obtain accurately

Inactive Publication Date: 2019-01-15
CHINA PETROLEUM & CHEM CORP +1
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Problems solved by technology

However, the current probabilistic inversion method of reservoir physical parameters based on Bayesian theory is difficult to obtain the likelihood function accurately during the calcu

Method used

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  • Reservoir parameter prediction method and system based on Bayesian classification
  • Reservoir parameter prediction method and system based on Bayesian classification
  • Reservoir parameter prediction method and system based on Bayesian classification

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Embodiment 1

[0038] In this embodiment, the method for predicting reservoir parameters based on Bayesian classification according to the present invention may include: step 1, based on known reservoir elastic parameters, establishing a first inversion equation for reservoir physical parameters; step 2, Based on the Bayesian formula, the first inversion equation is transformed into the second inversion equation of the likelihood function of the reservoir elastic parameters; step 3, based on the Bayesian-sequential Gaussian method, the likelihood of the reservoir elastic parameters is solved and step 4, solving the second inversion equation based on the obtained likelihood function value of the reservoir elastic parameter to obtain the reservoir physical parameter value, wherein the reservoir parameter includes the reservoir elastic parameter and the reservoir physical parameter.

[0039] In this embodiment, the inversion equation of reservoir physical property parameters is established throu...

Embodiment 2

[0115] According to an embodiment of the present invention, a reservoir parameter prediction system based on Bayesian classification is provided. The system includes a memory, a processor, and a computer program stored in the memory and operable on the processor. When the processor executes the program The following steps are realized: based on the known elastic parameters of the reservoir, the first inversion equation of the physical property parameters of the reservoir is established; based on the Bayesian formula, the first inversion equation is converted into the second inversion equation of the likelihood function about the elastic parameters of the reservoir The inversion equation; based on the Bayesian-sequential Gaussian method, solving the likelihood function of the reservoir elastic parameter; and solving the second inversion equation based on the obtained reservoir elastic parameter likelihood function value to obtain the reservoir physical property parameter value ,...

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Abstract

The invention discloses a reservoir parameter prediction method and system based on Bayesian classification. The method comprises the following steps of: establishing a first inversion equation of reservoir physical property parameters based on known reservoir elastic parameters; based on the Bayesian formula, transforming the first inversion equation into the second inversion equation about the likelihood function of the reservoir elastic parameter; based on a Bayesian-sequential Gaussian method, solving the likelihood function of reservoir elastic parameters; obtaining reservoir physical parameters by solving the second inversion equation based on the likelihood function of the obtained reservoir elastic parameters. The invention does not need to carry out complex model initialization, fully considers the advantage of stochastic characteristics of geological and geophysical characteristics, and makes the inversion results have more practical geological significance, and it can also solve the problem that the variogram function is not reliable in the case of less well data, or even in the case of uneven distribution of wells in the work area in the geostatistical stochastic simulation method.

Description

technical field [0001] The invention belongs to the field of geophysical exploration in the petrochemical industry, and more specifically relates to a method and system for predicting reservoir parameters based on Bayesian classification. Background technique [0002] At present, the two most commonly used inversion methods of reservoir physical parameters based on conventional P-wave reflection seismic data in China are nonlinear inversion of reservoir physical parameters based on neural network and stochastic simulation method based on geostatistics. Both methods belong to the category of nonlinear inversion. The probabilistic inversion method of reservoir physical parameters based on Bayesian theory does not require complex model initialization, but establishes the probability and statistical relationship between reservoir physical parameters and reservoir elastic parameters based on the reservoir physical model, and then integrates with the stacked The combination of pr...

Claims

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Application Information

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IPC IPC(8): G06F17/50G06N7/00
CPCG06F2111/08G06F30/20G06N7/01
Inventor 周单
Owner CHINA PETROLEUM & CHEM CORP
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