多趋势融合的概率体约束方法及其在储层建模中的应用

doi:10.7623/syxb201506010

石油学报 ›› 2015, Vol. 36 ›› Issue (6): 730-739.DOI: 10.7623/syxb201506010

多趋势融合的概率体约束方法及其在储层建模中的应用

林承焰¹, 陈仕臻¹, 张宪国¹, 刘文婧², 商建霞³

1. 中国石油大学山东省油藏地质重点实验室中国石油大学地球科学与技术学院山东青岛 266580;
2. 中国石油集团东方地球物理勘探有限责任公司河北涿州 072751;
3. 中海石油(中国)有限公司湛江分公司广东湛江 524057

收稿日期:2014-12-06 修回日期:2015-04-18 出版日期:2015-06-25 发布日期:2015-08-06
通讯作者: 陈仕臻,男,1987年8月生,2010年获中国石油大学(华东)地质学专业学士学位,现为中国石油大学(华东)地球科学与技术学院博士研究生,主要从事三维地质建模方面的研究工作。Email:csz0808@foxmail.com
作者简介:林承焰,男,1963年9月生,1985年毕业于华东石油学院,1997年获石油大学(北京)油气地质与勘探专业博士学位,现为中国石油大学(华东)教授、博士生导师,主要从事储层地质学及油藏描述的教学与科研工作。Email:lincy@upc.edu.cn
基金资助:
国家重大科技专项(2011ZX05009-003)、国家自然科学基金项目(No.41202092)、中央高校基本科研业务费专项资金项目(14CX06016A)和中海石油(中国)有限公司湛江分公司科研合作课题资助。

Probability constraint method based on multiple trend integration and its application in reservoir modeling

Lin Chengyan¹, Chen Shizhen¹, Zhang Xianguo¹, Liu Wenjing², Shang Jianxia³

1. Reservoir Geology Key Laboratory of Shandong Province, China University of Petroleum; School of Geosciences, China University of Petroleum, Shandong Qingdao 266580, China;
2. CNPC Geophysical Company Limited, Hebei Zhuozhou 072751, China;
3. Zhanjiang Branch, CNOOC China Limited, Guangdong Zhanjiang 524057, China

Received:2014-12-06 Revised:2015-04-18 Online:2015-06-25 Published:2015-08-06

摘要/Abstract

摘要：

对于井数少且以地震资料为主的海上油田,虽然已经投入较长时间的开发,但是由于井间和油藏边部等缺少井控部位的认识程度偏低,会严重影响后续开发方案的实施。已有的建模约束方法不能解决模拟过程中面临的边界内部参数控制不到位、单一趋势考虑不全面、多个趋势难以同时整合的问题,在海上油田应用效果较差。针对上述问题,为了准确反映砂体和储层参数在空间的分布,提出了多趋势融合的概率体约束方法。以南海珠江口盆地W油田地质模型建立为例,综合应用地震、测井、地质和开发动态等资料,分别采用块克里金插值和基于位置的加权线性组合方法,整合多个类型和级次的趋势建立了离散变量和连续变量的概率体,并将其作为约束条件应用于沉积相和孔、渗参数的模拟过程。与常规建模约束方法相比,多趋势融合的概率体约束方法克服了边界约束建模的局限性和单一趋势约束建模的不足,达到了对多个趋势同时整合的目的,对落实相带边界和减小参数在井间分布的不确定性效果明显,具有良好的应用前景。

关键词: 多趋势融合, 概率体约束, 储层建模, 海上油田, 少井条件

Abstract:

The offshore oilfields have been developed for a long time, which have a small number of wells and rich seismic data. However, the implementation of follow-up development plans will be seriously affected because of the less understanding of cross-well area and reservoir edge in lack of well control. The existing modeling constraint method cannot solve problems in the simulation process, such as inadequate control of inner-boundary parameters, incomprehensive considerations on sole trend and difficulties in simultaneously integrating multiple trends. Thus, this method has a poor application effect in offshore oilfields. In order to solve the above problems and accurately reflect the spatial distribution of sand body and reservoir parameters, this study proposes a probability constraint method based on multiple trend integration. Taking the geological modeling of Oilfield W in the South China Sea as a case, and using seismic, logging, geological and development dynamics data, Block Kriging interpolation and position-based weighted linear combination method was adopted to integrate multiple types and levels of trends, so as to establish the probability for discrete and continuous variables. Further, probability was used as a constraint applied in the simulation processes of sedimentary facies, porosity and permeability parameters. Compared with conventional modeling constraint method, the probability constraint method overcomes the limitation of boundary-controlled modeling and the deficiency of single-trend constraint modeling, so as to achieve simultaneous integration of multiple trends. Moreover, this method is most favorable for determination of the facies edge and reduction of uncertainty in cross-well distribution of parameters, showing a good application prospect.

Key words: multiple trend integration, probability constraint, reservoir modeling, offshore oilfield, condition of less wells

中图分类号:

TE19

林承焰, 陈仕臻, 张宪国, 刘文婧, 商建霞. 多趋势融合的概率体约束方法及其在储层建模中的应用[J]. 石油学报, 2015, 36(6): 730-739.

Lin Chengyan, Chen Shizhen, Zhang Xianguo, Liu Wenjing, Shang Jianxia. Probability constraint method based on multiple trend integration and its application in reservoir modeling[J]. Acta Petrolei Sinica, 2015, 36(6): 730-739.

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多趋势融合的概率体约束方法及其在储层建模中的应用

Probability constraint method based on multiple trend integration and its application in reservoir modeling

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