Petroleum Science >2010,??Issue 4:??472-476 DOI: https://doi.org/10.1007/s12182-010-0095-8
Controlling the uncertainty in reservoir stochastic simulation Open?Access
文章信息
作者：Cui Yong,Chi Bo,Chen Guo,Ouyang Cheng and Xia Bairu
作者單位：
China University of Geosciences, Beijing 100083, China;Research Institute of Daqing Oilfi eld Company Ltd., Heilongjiang 163712, China;Geological Exploration & Development Research Institute, PetroChina Chuanqing Drilling Engineering Company, Chengdu, Sichuan 610051, China;Geological Exploration & Development Research Institute, PetroChina Chuanqing Drilling Engineering Company, Chengdu, Sichuan 610051, China;China University of Geosciences, Beijing 100083, China
投稿時(shí)間：2009-08-31
引用方式：Yong, C., Bo, C., Guo, C. et al. Pet. Sci. (2010) 7: 472. https://doi.org/10.1007/s12182-010-0095-8
文章摘要
Unexpected noise in reservoir stochastic simulation realization may be too high to make the realization useful, especially when there is a lack of hard data. Through discussing the uncertainties, we present two ways to control the uncertainty ratio that is brought by the algorithm of stochastic simulation. By reasonably reducing the random value of the stochastic simulation result, the unexpected values introduced by the residual that associates with random series can be controlled. Another way when the data disperse unevenly is to control the stochastic simulation order by grouping the points that need to be simulated to make those points which can be simulated by more neighborhood hard data calculated fi rst. Both methods do not go against the core stochastic simulation algorithm.
關(guān)鍵詞
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Reservoir stochastic simulation, hard data, Kriging algorithm, residual, realization