A Skeleton-Based Multiple Point Geostatistics for Reservoir Stochastic Modeling
This paper first dives into the newly published multiple point geostatistics, that is, the Snesim and Simpat. The study shows, that both the Snesim and the Simpat face the problem of reproducing continuous shape due to the random selection of data patterns. An intelligent choice of data patterns may solve this problem. Based on this consideration, the paper designs a new multiple point geostatistics algorithm, skeleton-based multiple point geostatistics. The core idea is to use the skeletons of reservoir objects to restrict the selection of data patterns. So the algorithm of skeleton-based multiple point geostatistics consists of two parts, firstly, constructing the skeleton of the reservoir objects; secondly, forecasting the distributions of reservoir objects using multiple point geostatistics. The paper proves the skeleton-based multiple point geostatistics can reproduce the continuous and curvilinear reservoir objects through die modeling of several conceptual fluvial models. During the tests of the skeleton-based multiple point geostatistics, the paper points out the new method has the ability of solving stationary problem by reservoir skeleton, which has been puzzling geostatistical scientists for years.
Yanshu Yin Changmin Zhang Taiju Yin Shaohua Li
Faculty of Information and mathematics, Yangzle University,1＃ Nanhu Road, Jingzhou,Hubei,China
国际会议
The 12th Conference of the International Association for Mathematical Geology(第12届国际数学地质大会)
北京
英文
587-590
2007-08-26（万方平台首次上网日期，不代表论文的发表时间）