Reservoir parameter inversion and fracture simulation method and device based on Markov chain

Generating a heterogeneous reservoir grid model through the Markov chain method solves the problem of insufficient homogeneity and regularity of the reservoir model in the existing technology, and realizes more accurate sewing mesh distribution simulation and reservoir parameter inversion play.

CN119221921APending Publication Date: 2024-12-31CHINA PETROLEUM & CHEMICAL CORP +1
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Patent Information

Application Number
CN202310785414.9
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2023-06-29
Publication Date
2024-12-31

AI Technical Summary

Technical Problem

The existing reservoir models show a large degree of homogeneity on small scales, which is difficult to provide support for the refined seam distribution simulation, and lose the distribution regularity of reservoir parameters.

Method used

The reservoir parameter inversion and fracture simulation method based on the Markov chain is used to preprocess the logging and well recording data, define the state matrix and the transfer probability matrix, and random transfer is carried out to generate a heterogeneous reservoir grid model. The distribution regularity of reservoir parameters is retained.

Benefits of technology

The generated heterogeneous reservoir grid model is more in line with the actual situation and can maintain high accuracy and accuracy on different scales. It is suitable for refined seam spreading simulation and characterizes the seam pattern under reservoir heterogeneity.

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Abstract

The invention discloses a Markov chain-based reservoir parameter inversion and fracture simulation method and device. The method comprises the following steps of S1, determining an initial parameter matrix C; s2, determining an initial state matrix S0; s3, determining a transition probability matrix P; s4, determining prediction matrixes S1, S2, S3... Sn; s5, determining a reservoir parameter inversion matrix S; s6, dividing all elements in S0 into M sections; s7, selecting N elements as fracturing injection points, and adding the N elements into the F; s8, the elements meeting the conditions are placed in the Temp matrix; s9, elements in the Temp matrix are selected and added into the F; s10, repeating the step S8 and the step S9; and S11, determining positions corresponding to all elements in F in S, and further determining a fracture network. The defects that a reservoir grid model shows a large degree of homogeneity, the reservoir loses distribution regularity, and support is difficult to provide for refined seam network distribution simulation are overcome.
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