2007•Computing Techniques for Geophysical and Geochemical ExplorationRequires access

LINEAR DIMENSION-REDUCING MAPPING METHOD TO IDENTIFY THE LITHOLOGY OF VOLCANIC ROCKS

Shan Gang-yi

Open publisher page 0 citations

Abstract

With the increasing demand for the resources of oil and gas,the development and exploration of volcanic rock reservoirs gradually become the new increase of the output.The study of volcanic rock lithology is the basis of volcanic rock reservoirs.Common methods in identifying volcanic lithology are not very effective.The principal component analysis method has been used to simply identify the lithology of volcanic rocks,and the results are good,but when the information of texture is included in the rock's name,this method is not very effective.The Linear dimension-reducing mapping method is applied to the volcanic rocks samples based on rock slices,whole rock analysis and logging traces.By this method,andesite,basalt,rhyolite and rhyolitic tuff are indentified and classied well.Compared with the method of principal component analysis,the method achieves much better results and it can separate rhyolite from rhyolitic tuff which is very difficult to be divided in the principle component analysis method.

About this research paper

What this paper is about

With the increasing demand for the resources of oil and gas,the development and exploration of volcanic rock reservoirs gradually become the new increase of the output.The study of volcanic rock lithology is the basis of volcanic rock reservoirs.Common methods in identifying volcanic lithology are not very effective.The principal component analysis method has been used to simply identify the lithology of volcanic rocks,and the results are good,but when the information of texture is included in the rock's name,this method is not very effective.The Linear dimension-reducing mapping method is applied to the volcanic rocks samples based on rock slices,whole rock analysis and logging traces.By this method,andesite,basalt,rhyolite and rhyolitic tuff are indentified and classied well.Compared with the method of principal component analysis,the method achieves much better results and it can separate rhyolite from rhyolitic tuff which is very difficult to be divided in the principle component analysis method.

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

With the increasing demand for the resources of oil and gas,the development and exploration of volcanic rock reservoirs gradually become the new increase of the output.The study of volcanic rock lithology is the basis of volcanic rock reservoirs.Common methods in identifying volcanic lithology are not very effective.The principal component analysis method has been used to simply identify the lithology of volcanic rocks,and the results are good,but when the information of texture is included in the rock's name,this method is not very effective.The Linear dimension-reducing mapping method is applied to the volcanic rocks samples based on rock slices,whole rock analysis and logging traces.By this method,andesite,basalt,rhyolite and rhyolitic tuff are indentified and classied well.Compared with the method of principal component analysis,the method achieves much better results and it can separate rhyolite from rhyolitic tuff which is very difficult to be divided in the principle component analysis method.

Key concepts: Rhyolite, Lithology, Geology, Andesite, Volcanic rock, Volcano, Principal component analysis, Basalt

Related papers

Back to paper searchBrowse research topicsOriginal source
LINEAR DIMENSION-REDUCING MAPPING METHOD TO IDENTIFY THE LITHOLOGY OF VOLCANIC ROCKS — Research Paper | ScholarLens