Abstract

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Title:: Identification Method of Sandy-conglomerate Lithology Based on Bacterial Foraging Algorithm

Author(s):: WANG Fei; BIAN Hui-yuan; HAN Xue; ZHANG Yi; ZHANG Yong-hao; 1. School of Geology Engineering and Geomatics, Chang’an University, Xi’an 710054, Shaanxi, China; 2. College of Geology and Environment, Xi’an University of Science and Technology, Xi’an 710054, Shaanxi, China; 3. The First Branch of the Logging Company, Shengli Petroleum Engineering Co. Ltd., Dongying 257200, Shandong, China; 4. CNPC Logging Co. Ltd., Xi’an 710077, Shaanxi, China

Keywords:: well logging interpretaton; sandy-conglomerate; bacterial foraging algorithm; multi-component mineral model; optimization inversion; lithology; porosity; Songliao Basin

Abstract:: Sandy-conglomerate reservoir lithology is complex, composition variation of parent rock is large, pore structure is complex and strong heterogeneity, so that it is difficult to accurately divide lithology and build accurate interpretation model, resulting in low reservoir parameter calculation accuracy. Based on the characteristics of sandy-conglomerate reservoir in Lishu fault of Songliao Basin, a multi-component volume model was established for well logging interpretation, and the stratum was taken as the combination of local homogeneous pore, muddy, quartz, feldspar and rock debris. According to the multi-component volume model, the corresponding log response equation was built, and the bacterial foraging algorithm was taken as the optimal solution of multi-component mineral model, and then the optimized results were compared with the porosity by core analysis and the volume fraction by whole-rock mineral analysis. The results verify that the bacteria foraging algorithm is reliable for the inversion of sandy-conglomerate multi-component mineral model. Based on bacteria foraging algorithm, the result is good for the well logging interpretation of sandy-conglomerate reservoir in Songliao Basin.