摘要
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-震-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 lithologie gas reservoir result in the uncertainty of gas reservoir description and predition. Based on the theol7 of multi-point geustatistics, the stochastic modeling method For lithtlogic gas reserw^ir of tile ＂weld seismic-sedimentah＇y mode＂ with multipoint geostatistics as the core is proposed, thai is based on a priori geological knowledge and lakes fall use of multi-dumain information such as well point hard data, seismic data and modern river sedimentary mode. A muhi-poinl geoslatistics ＂training images＂ instead of classical geustatistics ＂variogram＂ will make comprehensive use of various infovtnation creatively to form a detailed geological modeling theory and method for lithologic gas reserwir. In one 3-1） test area of Sulige （,;as Field, a fine geological model for test area is huilt through the muhi-domain information integration of multi-point geostatisties. The evaluation resuh uf model shows that the eombination of well-seismic modeling strategy can effectively reduce the cause of strong tluvial gas reservoir and the uneertainly of lithologie gas reservoir characterization, and improve the complex geometry and the simulation accuracy and computational efficiency of high-sinuosity fluvial reservoir.
出处
《断块油气田》
CAS
2013年第6期723-726,共4页
Fault-Block Oil & Gas Field
基金
国家科技重大专项课题"鄂尔多斯盆地大型岩性地层油气藏勘探开发示范工程"(2008ZX05044-003-16)
关键词
岩性气藏
多点地质统计学
训练图像
井震结合
随机建模
lithologic gas reservoir：, mulli-point geostatistics, training image, well-seismic combination
stochastic modeling
