ScholarLens Back to search
2001•Unpublished venueRequires access

THE STUDY ON RECOGNIZING OOLID RESERVOIR FROM WELL LOGGING INFORMATION

Xia Hongquan

Open publisher page 0 citations

Abstract

Based on well logging response characteristic of oolid reservoir and electrical- lithologic database from log parameters of lithology, automatic classifying formation is realized. By gray conjunction method, oolid formation of each well profile is identified and the log recognition pattern for oolid reservoir is established by combining reservoir parameters and then the programs is developed. The application shows that this method has higher resolution and is able to classify oolid reservoirs of thicker than 0.5 meter and improves the prediction precision in vertical and horizontal direction.

About this research paper

What this paper is about

Based on well logging response characteristic of oolid reservoir and electrical- lithologic database from log parameters of lithology, automatic classifying formation is realized. By gray conjunction method, oolid formation of each well profile is identified and the log recognition pattern for oolid reservoir is established by combining reservoir parameters and then the programs is developed. The application shows that this method has higher resolution and is able to classify oolid reservoirs of thicker than 0.5 meter and improves the prediction precision in vertical and horizontal direction.

Why it matters

A significance statement is not available in the OpenAlex record.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Based on well logging response characteristic of oolid reservoir and electrical- lithologic database from log parameters of lithology, automatic classifying formation is realized. By gray conjunction method, oolid formation of each well profile is identified and the log recognition pattern for oolid reservoir is established by combining reservoir parameters and then the programs is developed. The application shows that this method has higher resolution and is able to classify oolid reservoirs of thicker than 0.5 meter and improves the prediction precision in vertical and horizontal direction.

Key concepts: Lithology, Logging, Well logging, Geology, Reservoir modeling, High resolution, Petroleum engineering, Data mining

Related papers

Related paper 1Related paper 2Related paper 3
Back to paper searchBrowse research topicsOriginal source
THE STUDY ON RECOGNIZING OOLID RESERVOIR FROM WELL LOGGING INFORMATION — Research Paper | ScholarLens