Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

A seismic lithofacies prediction method and device based on naive Bayesian classification

A technology of Bayesian classification and prediction method, applied in the field of seismic lithofacies prediction device based on naive Bayesian classification, which can solve the problems of lack of theoretical support of rock physics, uncertainty analysis of prediction results, and unsatisfactory prediction accuracy and other issues, to achieve the effect of facilitating quantitative evaluation, reducing human error, and strong applicability

Inactive Publication Date: 2017-12-12
CHINA PETROLEUM & CHEM CORP +1
View PDF6 Cites 5 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] Using seismic attributes to predict lithofacies, many scholars at home and abroad have proposed corresponding research methods, including multi-attribute cluster analysis, multi-parameter intersection and neural network prediction, etc., but lack the theoretical support of rock physics and the uncertainty analysis of prediction results. Unsatisfactory prediction accuracy

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A seismic lithofacies prediction method and device based on naive Bayesian classification
  • A seismic lithofacies prediction method and device based on naive Bayesian classification
  • A seismic lithofacies prediction method and device based on naive Bayesian classification

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0043] figure 2 A flow chart of a seismic lithofacies prediction method based on naive Bayesian classification is shown according to an embodiment of the present invention. In this embodiment, the method includes:

[0044] Step 101, based on the geological deposition characteristics and logging curve characteristics of the study area, determine the lithofacies division scheme, and select one or more elastic parameters sensitive to lithofacies characteristics from various elastic parameters through logging intersection and statistical analysis;

[0045] Step 102, performing Naive Bayes classification statistics based on the lithofacies characteristics and the one or more elastic parameters of the well log to determine the conditional probability distribution of the elastic parameters under various lithofacies characteristics;

[0046] Step 103, obtaining the one or more elastic parameters of the work area to be predicted based on the inversion of the pre-stack seismic sub-ang...

Embodiment 2

[0057] According to another embodiment of the present invention, a device for predicting seismic lithofacies based on naive Bayesian classification is disclosed, the device includes:

[0058] The well logging analysis unit is used to determine the lithofacies division scheme based on the geological deposition characteristics and logging curve characteristics of the research area, and select one or more of the lithofacies sensitive to the lithofacies from various elastic parameters through logging intersection and statistical analysis. multiple elastic parameters;

[0059] A probability determination unit, configured to perform Naive Bayesian classification statistics based on the lithofacies characteristics and the one or more elastic parameters of the well log, so as to determine the one or more elastic parameters under various lithofacies characteristics The conditional probability distribution of ;

[0060] The work area analysis unit is used to obtain the one or more elas...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention relates to the field of seismic reservoir prediction, in particular to a seismic lithofacies prediction method and device based on naive Bayesian classification. This method applies Bayesian classification to reservoir prediction research, based on rock physical analysis and elastic parameter inversion, and uses naive Bayesian classification statistics to predict lithology, fluid, etc., reducing multiple solutions for reservoir prediction It can also quantitatively evaluate the uncertainty of prediction results, which can significantly improve the accuracy of seismic lithofacies prediction.

Description

technical field [0001] The present invention relates to the field of seismic reservoir prediction, more specifically, to a method for predicting seismic lithofacies based on naive Bayesian classification and a device for predicting seismic lithofacies based on naive Bayesian classification. Background technique [0002] Using seismic attributes to predict lithofacies, many scholars at home and abroad have proposed corresponding research methods, including multi-attribute cluster analysis, multi-parameter intersection, and neural network prediction, etc., but lack the support of rock physics theory and the uncertainty analysis of prediction results. The prediction accuracy is unsatisfactory. Contents of the invention [0003] The invention proposes a method capable of more accurately predicting seismic lithofacies, and the invention also proposes a corresponding device. [0004] According to one aspect of the present invention, a seismic lithofacies prediction method based...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G01V1/50
CPCG01V1/50G01V2210/6169
Inventor 杨勤林田建华朱博华曹少蕾李洋董清源郑连弟刘瑞红
Owner CHINA PETROLEUM & CHEM CORP
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com