基于多点地质统计学的岩性气藏精细建模方法与应用

Method and application of stochastic modeling for lithologic gas reservoir  based on multiple-point geostatistics

杨勇1,聂海峰2,张雅玲1,谭蓓2,鲜波3

Yang Yong1, Nie Haifeng2, Zhang Yaling1, Tan Bei2, Xian Bo3

1.中国石油长庆油田公司勘探开发研究院袁陕西西安710021曰;2.中国石油塔里木油田塔西南勘探开发公司袁新疆喀什844804;3.中国石油塔里木油田公司勘探开发研究院袁新疆库尔勒841000

(1.Research Institute of Exploration and Development, Changqing Oilfield Company, PetroChina, Xi忆an 710021, China; 2.Kekeya
Operation Area, Taxinan Exploration and Development Company, TarimOilfield Company, PetroChina, Kashgar 844804, China;
3.Research Institute of Exploration and Development, TarimOilfield Company, PetroChina, Korla 841000, China

针对岩性气藏复杂地质特征导致的气藏描述和预测中的不确定性，在对比评价随机建模理论与方法适应性的基础上，提出以多点地质统计学为核心的“井?鄄震?鄄沉积模式”岩性气藏随机建模方法，即以先验地质认识为基础，充分利用井点“硬数据”、三维地震数据及现代河流沉积模式等多域信息，以多点地质统计学的训练图像代替经典地质统计学的变差函数，综合运用各种信息，形成了岩性气藏精细地质建模技术与方法。在苏里格气田某三维试验区，通过多点地质统计学多域信息整合功能，建立试验区精细地质模型。模型评价结果表明，井震结合建模策略可以有效降低河流相岩性气藏储层表征的不确定性，显著提高了模拟精度和运算效率。

The complex geological features of lithologic gas reservoir result in the uncertainty of gas reservoir description and prediction. Based on the theory of multi-point geostatistics, the stochastic modeling method for lithologic gas reservoir of the "well -seismic-sedimentary mode" with multipoint geostatistics as the core is proposed, that is based on a priori geological knowledge and takes full use of multi-domain information such as well point hard data, seismic data and modern river sedimentary mode. A multi-point geostatistics "training images" instead of classical geostatistics "variogram" will make comprehensive use of various information creatively to form a detailed geological modeling theory and method for lithologic gas reservoir. In one 3-D test area of Sulige Gas Field, a fine geological model for test area is built through the multi-domain information integration of multi-point geostatistics. The evaluation result of model shows that the combination of well-seismic modeling strategy can effectively reduce the cause of strong fluvial gas reservoir and the uncertainty of lithologic gas reservoir characterization, and improve the complex geometry and the simulation accuracy and computational efficiency of high-sinuosity fluvial reservoir.

10.6056/dkyqt201306010