A system and method for intelligent analysis of sandy conglomerate particle size

Abstract

The invention relates to an intelligent analysis system and method for glutenite particle size. The system is provided with a data reading module, a data cleaning module, a data classification module, an automatic drawing module of particle size maps, an automatic generation module of cumulative particle size probability curves and a deposition The environmental analysis module, all modules work together, use artificial intelligence drawing technology to automatically draw the particle size histogram, frequency curve and particle size frequency cumulative curve of the sandy conglomerate that needs to be analyzed, and finally can be based on clustering algorithms and different classification algorithms. The representative sedimentary environment is automatically classified, replacing the traditional intuitive classification method, and automatically and intelligently analyzes the grain size of glutenite, which improves work efficiency.

Description

technical field [0001] The invention belongs to the field of oil reservoir analysis, and in particular relates to an intelligent analysis system and method for sandy conglomerate particle size. Background technique [0002] In the process of reservoir analysis, grain size analysis has always been the basic method for analyzing the sedimentary environment, but the conventional grain size analysis process is cumbersome, requiring manual sorting of a lot of data and manual drawing of many basic maps. After the maps are drawn, Researchers need to manually classify the types of sedimentary facies according to the type of particle size cumulative probability curve drawn manually. Usually, a set of procedures is time-consuming and labor-intensive, and if another attribute is changed, the maps have to be redrawn, and the repeatability is low. . Contents of the invention [0003] In order to solve the existing technical problems, the present invention proposes an intelligent analy...

AI Technical Summary

Problems solved by technology

[0002] In the process of reservoir analysis, grain size analysis has always been the basic method for analyzing the sedimentary environment, but the conventional grain size analysis process is cumbersome, requiring manual sorting of a lot of data and manual drawing of many basic maps. After the maps are drawn, Researchers need to manually classify the types of sedimentary facies according to the type of particle size cumulative probability curve drawn manually. Usually, a set of procedures is time-consuming and labor-intensive, and if another attribute is changed, the maps have to be redrawn, and the repeatability is low.

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