• 责任者：Yang Yong (Research Institute of Exploration and Development ; Changqing Oilfield Company ; PetroChina ; Xi’an 710021 ; China) ; Nie Haifeng
• 刊名：Fault-Block Oil and Gas Fields
• 出版年：2013
• 卷期：20(6)
• 关键词：岩性油气藏 ; lithologic reservoir ; 地质统计学 ; geostatistics ; 鄂尔多斯盆地 ; Ordos Basin
• 页码：p.723-726
• 图表：3 illus., 17 refs.
• 分类号：1003
• issnNo：ISSN1005-8907
• isbnNo：CN41-1219/TE

     The complex geological features of lithologie gas reservoir result in the uncertainty of gas reservoir description and predition. Based on the theol7 of multi-point geustatistics, the stochastic modeling method For lithtlogic gas reserw~ir of tile ＂weld seismic-sedimentah＇y mode＂ with multipoint geostatistics as the core is proposed, thai is based on a priori geological knowledge and lakes fall use of multi-dumain information such as well point hard data, seismic data and modern river sedimentary mode. A muhi-poinl geoslatistics ＂training images＂ instead of classical geustatistics ＂variogram＂ will make comprehensive use of various infovtnation creatively to form a detailed geological modeling theory and method for lithologic gas reserwir. In one 3-1） test area of Sulige （,;as Field, a fine geological model for test area is huilt through the muhi-domain information integration of multi-point geostatisties. The evaluation resuh uf model shows that the eombination of well-seismic modeling strategy can effectively reduce the cause of strong tluvial gas reservoir and the uneertainly of lithologie gas reservoir characterization, and improve the complex geometry and the simulation accuracy and computational efficiency of high-sinuosity fluvial reservoir.