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《Progress in Geophysics》 2006-01
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Synthetic predication of favorable fracture zone from seismic and log data

LI Jun,HAO Tian-yao,ZHAO Bai-min(Institute of Geology and Geophysics,Chinese Academy of Sciences,Beijing 100029,China)  
The paper presents a new approach,which uses seismic and log data synthetically,to identify fractures of carbonatite in pre-Cenozoic relic basin.Log data can indicate fractures′ positions of strata exactly,but its data are sparse and not even in space;Nevertheless,seismic data are dense and even in space.The technique of artifical neural network of seismic multi-attributes can combine log and seismic data well.Therefore it can take advantages of their respective advantage to predict the favorable fracture zone of sections and surfaces.This way is proved to have higher precision than general ways after processing and prediction of real data.
【Fund】: 中国科学院知识创新重大项目(KZCX1-SW-18-01)资助
【CateGory Index】: P631.4;P631.81
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