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
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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.
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.
引文
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[2]凌云研究组.基本地震属性在沉积环境解释中的应用研究[J].石油地球物理勘探,2003,38(6):642-653.
[3]薛培华.河流点坝相储层模式概论[M].北京:石油工业出版社,1991.
[4]裘怿楠.储层地质模型[J].石油学报,1991,12(4):55-62.
[5]陈亮,黄述旺,赖泽武.应用截断高斯随机模拟法研究沉积微相[J].石油勘探与开发,1998,25(6):78-80.
[6]张祥忠,熊琦华,蔡毅.应用多级序贯指示模拟方法模拟火烧山油田岩相[J].石油勘探与开发,2003,30(6):81-82.
[7]刘振峰,郝天珧,方辉.用M arkov链模型随机模拟储层岩相空间展布[J].石油学报,2005,26(5):57-60.
[8]李少华,张昌民,林克湘,等.应用改进的布尔方法建立砂体骨架模型[J].石油勘探与开发,2000,27(3):91-92.
[9]吴胜和,李文克.多点地质统计学——理论、应用与展望[J].古地理学报,2005,7(1):137-144.
[10]尹艳树,吴胜和.储层随机建模研究进展[J].天然气地球科学,2006,17(2):210-216.
[11]李少华,汗日明,张昌民,等.结合露头信息建立储层地质模型[J].天然气地球科学,2006,17(3):374-377.
[12]李少华,郭永康,李维锋,等.SN 31储层三维地质建模[J].天然气地球科学,2006,17(6):811-814.
[13]吴胜和,金振奎,黄沧钿,等.储层建模[M].北京:石油工业出版社,1999.
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