石油学报 ›› 2012, Vol. 33 ›› Issue (5): 854-858.DOI: 10.7623/syxb201205016

• 油田开发 • 上一篇    下一篇

储层建模过程中的网格化及其地质意义

崔 勇 1 夏柏如 1 陈 果 2 罗志华 1   

  1. 1 中国地质大学工程技术学院 北京 100083;2 川庆钻探公司勘探开发地质研究院 四川成都 610051
  • 收稿日期:2012-02-16 修回日期:2012-06-29 出版日期:2012-09-25 发布日期:2012-11-27
  • 通讯作者: 崔 勇
  • 作者简介:崔 勇,男,1971年10月生,2001年获石油大学(北京)博士学位,现为中国地质大学(北京)博士后,主要从事油气储层与油气藏工程研究。

Gridding and its geological meaning in reservoir modeling

CUI Yong 1 XIA Bairu 1 CHEN Guo 2 LUO Zhihua 1   

  • Received:2012-02-16 Revised:2012-06-29 Online:2012-09-25 Published:2012-11-27

摘要:

使用地质统计学工具建立储层模型时,网格化过程基本上决定了如何表征储层宏观的非均质性。在构造网格时,需要充分考虑储层的地质规律,而不能简单地对地层单元进行等单元插值细分。在构造网格过程中,需要考虑的地质因素主要有地层剥蚀、地层上超、过井断层以及小层系的划分。常规的网格包括笛卡尔正交坐标网格和非规则的三角网格,二者各具不同的优势。在强调网格化的数学表达时,数据的地质特征往往会在一定程度上被忽略。笔者从储层沉积背景与现有的储层地质数据的特殊性出发,给出了油藏建模过程中进行网格化所要考虑的必要因素,并在此基础上,完善了网格化的过程,使网格化过程与储层地质特征紧密联系在一起。

关键词: 储层建模, 网格化, 实现, 非均质性, 地质特征

Abstract:

Describing reservoir heterogeneity is always an important part in reservoir modeling. Gridding basically determines how to characterize the macroscopic heterogeneity of reservoirs when a reservoir model is built by using geostatistics. Thus, when grids are created, we should fully consider geological laws of reservoirs instead of simply dividing stratum units into even interpolation subsections. Geological factors deserving consideration in creating grids are stratum denudation, stratum onlap, faults across wells and division of sublayer systems. Conventional grids include the Cartesian orthogonal coordinate and irregular triangle grids, both have their own individual advantages. When mathematical algorithm is used to build grids, geological properties of the data may always be ignored to some extent, which is not what we expect. How to describe the data correctly in grids deserves more attention in reservoir modeling. Here, we took sedimentary settings of reservoirs and spatial properties of the data into full consideration and proposed essential factors that must be considered in gridding. Based on these, we improved the process of gridding and combined it with geological properties of the data closely.

Key words: reservoir modeling, gridding, realization, heterogeneity;geological property