石油学报 ›› 2018, Vol. 39 ›› Issue (9): 1051-1062.DOI: 10.7623/syxb201809009

• 油田开发 • 上一篇    下一篇

多尺度缝洞型碳酸盐岩油藏不确定性建模方法

邓晓娟1, 李勇1, 刘志良2, 王琦1, 刘卓涛3, 于清艳4   

  1. 1. 中国石油勘探开发研究院油田开发研究所 北京 100083;
    2. 中国石油塔里木油田公司勘探开发研究院 新疆库尔勒 841000;
    3. 中国石油工程建设有限公司北京设计分公司 北京 100085;
    4. 中国地质大学能源学院 北京 100083
  • 收稿日期:2018-01-01 修回日期:2018-08-01 出版日期:2018-09-25 发布日期:2018-09-28
  • 通讯作者: 邓晓娟,女,1989年3月生,2011年获长江大学学士学位,2014年获中国石油勘探开发研究院硕士学位,现为中国石油勘探开发研究院工程师,主要从事油气藏开发地质研究。Email:DXJ5288@petrochina.com.cn
  • 作者简介:邓晓娟,女,1989年3月生,2011年获长江大学学士学位,2014年获中国石油勘探开发研究院硕士学位,现为中国石油勘探开发研究院工程师,主要从事油气藏开发地质研究。Email:DXJ5288@petrochina.com.cn

Uncertainty modeling method of multi-scale fracture-cave carbonate reservoir

Deng Xiaojuan1, Li Yong1, Liu Zhiliang2, Wang Qi1, Liu Zhuotao3, Yu Qingyan4   

  1. 1. Oil Field Development Institute, PetroChina Research Institute of Petroleum Exploration and Development, Beijing 100083, China;
    2. Research Institute of Exploration and Development, PetroChina Tarim Oilfield Company, Xinjiang Korla 841000, China;
    3. Beijing Design Branch, China Petroleum Engineering & Construction Corporation, Beijing 100085, China;
    4. School of Energy Resources, China University of Geosciences, Beijing 100083, China
  • Received:2018-01-01 Revised:2018-08-01 Online:2018-09-25 Published:2018-09-28

摘要:

缝洞型碳酸盐岩油藏储集空间类型多、尺度悬殊且分布随机,定量表征孔、洞、缝的三维空间分布十分困难,同时该类型油藏储集空间的分布又存在较大的不确定性。忽略这些不确定性、采用偏离实际的地质模型,会导致开发效果不理想或选择不合适的开发方式。为了降低开发风险,建模过程中应充分重视不确定性的分析。以塔里木盆地哈拉哈塘油田奥陶系缝洞型碳酸盐岩油藏为例,提出了多尺度缝洞型碳酸盐岩油藏不确定性建模方法。该方法首先确定了储层有效孔隙度下限、大型溶洞与溶蚀孔洞孔隙度界限、表征裂缝的属性体界限3个主要的不确定性地质参数;其次,针对缝洞型碳酸盐岩油藏的特点,按照储集体类型和尺度划分为大型溶洞、溶蚀孔洞、大尺度裂缝、小尺度裂缝4种储层类型;在整合多类数据和分析缝洞分布规律基础上,采用成因控制建模方法,考虑3个主要的不确定性地质参数影响,分别建立4种储层类型的不同分布可能性的多个储集体离散模型,并将4类储集体离散模型按不同优先次序的多种同位条件赋值算法融合成多个等概率多尺度缝洞储集体三维离散分布模型;最后,通过动、静态多信息结合方法对多个离散分布模型进行优选,形成乐观、较可能、悲观3个离散分布模型,综合反映了建模研究的不确定性以指导开发调整。

关键词: 缝洞型储层, 碳酸盐岩油藏, 不确定性, 地质建模, 动、静态结合

Abstract:

The fracture-cave carbonate reservoir is characterized by various reservoir types, multi-scaled differences and random distribution. It is always a worldwide technical difficulty to quantitatively characterize the 3D space distribution of pore, cavity and fracture. Meanwhile, there are great uncertainties in the reservoir space distribution of this type of reservoir. If these uncertainties are ignored, the geological model deviated from the actual situation will be used, thus obtaining unideal development effect, or a wrong development mode will be applied. Therefore, much attention should be paid to uncertainty analysis during the modeling in order to reduce development risks. On this basis, taking the Ordovician fracture-cave carbonate reservoir in Halahatang oilfield of Tarim Basin as an example, an uncertainty modeling method of multi-scale fracture-cave carbonate reservoir is proposed in this study. Firstly, three key uncertainty geological parameters are determined by this method, i.e., the lower limit of effective reservoir porosity, the porosity limit for large cavity and dissolution pore, and the attribute threshold for characterizing fractures. Then based on the characteristics of fracture-cave carbonate reservoir, the reservoir can be classified into large cavity, dissolution pore, large-scale fracture and small-scale fracture according to reservoir body type and scale. Through integrating multiclass data and analyzing the distribution law of fracture-cavity system, the genetic control modeling method considering the influences of three major uncertainty geological parameters is used to establish multiple discrete models for four types of reservoir bodies with different distributions. Meanwhile, according to multiple homotopic conditional assignment algorithms with different priorities, the four kinds of discrete models are merged into multiple equal-probability 3D discrete distribution models of multi-scale fracture-cave reservoir bodies. Finally, multiple discrete distribution models are optimized by dynamic and static multi-information combination method; the upside(optimistic),expected(the most probable)and downside(the pessimistic)distribution models are formed to comprehensively reflect the uncertainty of modeling research and guide the development adjustment to obtain favorable results.

Key words: fracture-cave reservoir, carbonate reservoir, uncertainty, geological modeling, dynamic and static combination

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