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《Natural Gas Industry》 2006-12
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Yang Jin, Zhang Hui (College of Petroleum Engineering, China University of Petroleum·Beijing).  
During the drilling process, it is very important to identify formation lithology near bit while drilling for selecting bit types, for quick establishment of the lithology section, for discovering the oil and gas layers in time, and for locating the coring layer exactly. Drilling practice indicates that there is a direct or indirect relationship between drilling parameters and lithology. Based on the mud logging data and combining with the logging data of the drilled wells, BP neural network is applied to establish a neural network model for lithology identification while drilling. This model was verified in Xinjiang oilfield. Compared with the geological explanation of logging data, the prediction result of the model is much better than ever before and the coincidence rate can reach as high as about 80%.
【Fund】: 国家自然科学基金重大研究计划项目(编号:90410006)
【CateGory Index】: TE21
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