综合多学科信息建模——以港东开发区二区六区块储层微相三维分布模型为例  

INTEGRATING DATA FROM MULTIPLE DISCIPLINES IN RESERVOIR MODELING:A CASE FROM THE RESERVOIR MICROFACIES OF NO.6 DISTRICTOF NO.2 REGION,GANGDONG OILFIELD

作　　者：尹艳树[1] 翟瑞[2] 吴胜和[2] 

机构地区：[1]长江大学数学学院,湖北荆州434023 [2]中国石油大学资源与信息学院,北京102249

出　　处：《天然气地球科学》2007年第3期408-411,共4页Natural Gas Geoscience

基　　金：国家自然科学基金(编号:4057207840602013)资助

摘　　要：遵循从点(单井)到面(二维平面分布)再到体(三维空间分布)的研究流程,提出了利用岩心、测井、地震以及动态资料等多学科信息对储层微相分布进行预测的思路,即:通过区域地质背景分析和井点岩心资料细分沉积微相来建立岩电模型;在此基础上,通过单井相分析并结合砂体二维等值线图和地震资料识别的河道(带)来建立储层微相平面分布模型;利用动态资料,确定砂体连通及延展情况,精细解剖砂体,获得不同微相储层的结构特征参数;利用随机模拟方法,预测储层微相三维展布特征。根据以上思路,建立了大港油田港东开发区河流相储层三维分布模型,为油田生产提供了地质依据,也为随后的储层物性预测乃至数值模拟研究提供了必要的支持。A new method is proposed for forecasting the distribution of microfacies by integrating core data, logging data, seismic data and testing data. The flowchart of this method follows the basic idea of from points （well） to surfaces （the 2-D maps） to zones （the 3-D maps）. Firstly, the recognition and core-log response model is constructed by the analysis of sedimentary environments of the region and core data. Secondly, the microfacies of non-core wells are identified according to the core-log response model. Thirdly, the 2-D map of microfacies is forecasted by the 2-D map of sandstone thickness and the information from the analysis of seismic data. The shape parameters of microfacies are achieved by dissecting the microfacies using the testing data. Finally, the 3-D distribution of microfacies is reproduced by reservoir stochastic modeling methods. The 3-D microfacies distribution of the fluvial environments is accomplished in the Gangdong development area, Dagang oilfield. This high precise reservoir model can give more information to oil engineering, and is a basis of physical properties forecasting and reservoir numerical simulation.

关 键 词：多学科信息 综合 储层微相预测 大港油田 

分 类 号：TE122.22[石油与天然气工程—油气勘探]