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Data-driven rock physical modeling method and system

A petrophysical modeling and petrophysical modeling technology, applied in electrical digital data processing, instruments, computer-aided design, etc., can solve the problem of difficult to explain the prediction results.

Pending Publication Date: 2021-04-13
TSINGHUA UNIV
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Problems solved by technology

[0008] Third, deep neural network algorithms often face difficulties such as extrapolation and high parameterization, making their predictions difficult to explain

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  • Data-driven rock physical modeling method and system
  • Data-driven rock physical modeling method and system
  • Data-driven rock physical modeling method and system

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[0045] In order to make the purpose, technical solutions and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the present invention. Obviously, the described embodiments are part of the embodiments of the present invention , but not all examples. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0046] figure 1 A schematic flow chart of the data-driven petrophysical modeling method provided by the present invention, such as figure 1As shown, the present invention provides a data-driven petrophysical modeling method, comprising:

[0047] Step 101, constructing a general expression of a petrophysical model based on a rational neural network, the general expression of a petrophysical ...

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Abstract

The invention provides a data-driven rock physics modeling method and system, and the method comprises the steps of constructing a general expression of a rock physics model based on a rational neural network, and enabling the general expression of the rock physics model to be a general expression of rock physics in a rational function form; obtaining a logging data set, obtaining a rock physical model expression through training according to the logging data set, and the rock physical model expression is used for reflecting geological characteristics and lithology requirements of a corresponding region; and based on the rock physics generalized expression and the rock physics model expression, identifying and predicting the direct porosity and the pore fluid volume modulus of the profile data. According to the invention, rapid identification of reservoir parameters is realized through combination of logging and seismic sections, so that a rock physical model application system is faster and more convenient.

Description

technical field [0001] The invention relates to the technical field of geology, in particular to a data-driven petrophysical modeling method and system. Background technique [0002] The research work of using seismic data to model and analyze reservoir structure, lithology, physical properties and other parameters is an important direction of geophysical exploration. The common point of these works is: by extracting as many effective features as possible from the seismic data, including signal amplitude, frequency, attenuation, etc., through mathematical and physical modeling in features and reservoir parameters (velocity, porosity, shale content, etc. ) to establish a connection to realize the identification of reservoir oil and gas pools. [0003] In recent years, deep neural networks have become very accurate and widely used in many application domains, such as image recognition, natural language processing, and time series analysis. Among them, time series analysis ha...

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Application Information

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IPC IPC(8): G06F30/27G06F30/28G06F113/08G06F119/14
CPCG06F30/27G06F30/28G06F2113/08G06F2119/14
Inventor 孙卫涛
Owner TSINGHUA UNIV
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