2002Special Oil & Gas ReservoirsRequires access

Identify lithology of volcanic rocks by fuzzy mathematics

Wei Liu

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Abstract

In accordance with low success ratio of lithology identification in volcanic formation, a mode of identifying lithology of volcanics through fuzzy mathematics has been set up. 8 logging parameters reflecting lithology of volcanics were selected and threshold values were determined. Lithologies of volcanics were classified by using this identification mode and maximum subordination principle. 10 types of volcanics were identified by using field data, and they were compared with the result of core analysis, showing 85 % consistency. Therefore, this method has higher accuracy for identification of volcanic lithology, and is quite applicable.

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In accordance with low success ratio of lithology identification in volcanic formation, a mode of identifying lithology of volcanics through fuzzy mathematics has been set up. 8 logging parameters reflecting lithology of volcanics were selected and threshold values were determined. Lithologies of volcanics were classified by using this identification mode and maximum subordination principle. 10 types of volcanics were identified by using field data, and they were compared with the result of core analysis, showing 85 % consistency. Therefore, this method has higher accuracy for identification of volcanic lithology, and is quite applicable.

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Available abstract

In accordance with low success ratio of lithology identification in volcanic formation, a mode of identifying lithology of volcanics through fuzzy mathematics has been set up. 8 logging parameters reflecting lithology of volcanics were selected and threshold values were determined. Lithologies of volcanics were classified by using this identification mode and maximum subordination principle. 10 types of volcanics were identified by using field data, and they were compared with the result of core analysis, showing 85 % consistency. Therefore, this method has higher accuracy for identification of volcanic lithology, and is quite applicable.

Key concepts: Lithology, Volcanic rock, Geology, Identification (biology), Volcano, Fuzzy logic, Geochemistry, Petrology

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