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A Study on Lithology Identification Methods for Volcanic Rocks

ZHOU Bo1, LI Zhou-bo2, PAN Bao-zhi2   

  1. 1.Heilongjiang Institute of Science and Technology, Harbin 150027,China; 2.College of GeoExploration Science and Technology, Changchun 130026, China
  • Received:2004-10-20 Revised:1900-01-01 Online:2005-05-26 Published:2005-05-26
  • Contact: ZHOU Bo

Abstract: The lithology identification is a basic work in reservoir evaluation by well logging data. It is difficult to evaluate volcanic reservoirs with well logging data because volcanic lithology classification is not unanimous and the recognition methods are not perfect. Volcanic samples should be classified according to TAS (total alkalies vs silica) chart proposed by IUGS. The volcanic lithology can then be recognized by neural network method with well logging data. Only 65 percent volcanic rocks can be identified by conventional methods. With the method proposed, 81.8 percent rocks can easily be recognized.

Key words: volcanic rock, BP neural network, SOM neural network, lithology recognition

CLC Number: 

  • P631.8
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