摘要
针对渤南油田五六区沙三段4砂组2小层(Es342)储层砂体形态弯曲、分叉、砂体规模与展布变化大的特点,利用多点地质统计学建模法对研究层位进行沉积微相模拟。在该区密集井网区精细地层研究的基础上,统计扇三角洲前缘水下分流河道与河口坝砂体长、宽定量数据,结合储层地质知识库的研究,确立不同微相的平面形态与空间组合特征,依此建立定量训练图像。在此基础上,利用SNESIM算法对研究区扇三角洲前缘进行沉积微相模拟。模拟结果表明,利用多点地质统计方法,能够很好地模拟出扇三角洲前缘水下分流河道与河口坝的空间形态特征,得到符合地质意义的沉积微相模型。研究区密集井网的定量研究和训练图像的建立,可以丰富地质知识库,为类似地区利用多点地质统计学进行储层相建模时训练图像的建立提供指导。
The reservoirs of 42 sand formation in Shahejie Group, Eocene of Bonan Oilfield (Es342) are front fan-delta, which are of being meandering and forking with variable sand body distribution and scale. In this regard, the multi-point geostatistics sinmlation (MPS) is applied to model this spatial complicated microfacies. The first and core study is to get quantitative statistical data of underwater distributary channel and sand bar of front fan delta sediment in focused area on the base of stratigraphic study, combining 3D microfacies characteristics acquired from reservoir geological database, the quantitative training image is built. On the basis of established training image, SNESIM algorithm is applied to simulate microfaeies property of studied area. The result shows that MPS can reconstruct paleo-microfacies sand body(underwater distribntary channels and sand bar)reasonably in studied area and the micro- facies model from simulation is coherent to geological knowledge. The study on quantitative measurements of geological bodies in dense-well region and establishing of training image provide a guidance for other regions which have similar geological conditions.
出处
《断块油气田》
CAS
北大核心
2015年第6期760-764,共5页
Fault-Block Oil & Gas Field
基金
国家科技重大专项课题"复杂储层构型精细表征与建模"(2011ZX05009-003)
关键词
多点地质统计学
训练图像
密井网区
储层地质知识库
扇三角洲前缘
渤南油田五六区
multiple-point geostatistics
training image
high density well pattern region
reservoir geological knowledge database
fan delta front
5-6 regions of Bonan 0ilfield