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《Well Logging Technology》 2013-03
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Closeness Degree Methods to Identify Logging Lithology in Coalfield Base on Fuzzy Pattern Recognition

LIAN Zengzeng1,2,TAN Zhixiang2,DENG Kazhong2(1.Key Laboratory of Mine Spatial Information Technologies of National Administration of Surveying,Mapping & Geoinformation,Henan Polytechnic University,Jiaozuo,Henan 454000,China;2.Key Laboratory for Land Environment and Disaster Monitoring of SBSM,China University of Mining and Technology,Xuzhou,Jiangsu 221116,China)  
In order to better solve the problem of logging lithology identification,we use fuzzy pattern recognition method to identify lithology.Combined with actual logging data of a well in the field,we select 7 main lithology identification parameters to establish the standard model of lithology identification based on the fuzzy pattern recognition method.Each sample's and the three standard model's closeness degree are calculated which contains lattice approximate degree,Hamming closeness degree,Euclid approach degree,maximum and minimum closeness and the minimum closeness degree.The closeness degrees based on the above different methods show that all the five identified results are correct.Through analysis and comparison the maximum closeness degree curve by five methods is obtained,we can see the result of Hamming closeness degree method is more stable,accurate and most suitable for lithology identification in this experiment.This study also verifies that the application of fuzzy pattern recognition method to logging lithology identification is practical and scientific.
【Fund】: 河南理工大学矿山空间信息技术国家测绘地理信息局重点实验室开放基金资助项目(编号KLM201107)
【CateGory Index】: P631.81
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