SH徐深气田井壁裂缝三维延拓预测技术研究

发布时间：2018-04-22 00:25

本文选题：储层裂缝识别 + 井壁裂缝空间延拓　；参考：《东北石油大学》2017年硕士论文

【摘要】：徐深气田构造位置位于松辽盆地北部深层构造单元东南断陷区徐家围子断陷升平-兴城构造带上,具有火山活动与构造运动双重成因机制。该区发育可观的油气储集岩类,具有良好的开发前景。徐深气田火山岩储层具有埋藏深、低孔低渗、非均质性严重等特点,孔缝类型主要以气孔、溶蚀孔、裂缝型组合以及气孔、裂缝型组合为主,天然裂缝分布、地应力变化复杂,现有的基于构造应力场法、非线性理论、地震方法对于获得井周裂缝的密度分布、高密度区等信息都具有不同程度的局限性,加之气藏开发初期井网密度较低,分布不均匀,不易分析井筒周围裂缝密度状况,储层裂缝的刻画也仅仅局限在井控范围内,对于天然裂缝的分布、现今地应力场的认识带来了一定的困难。如此情况下,亟需研发新技术,综合利用多领域、多方法预测储层裂缝,指导油气田开发。本文在岩石力学、构造力学及相关的裂缝面延伸等理论基础上,通过对区块基础资料与测井资料的收集,并结合井壁裂缝空间延拓技术建立智能神经网络模型,应用测井资料结合进行井壁裂缝识别与统计分析,进行井壁裂缝空间延拓,地应力场分析。最终获得井壁裂缝高密度区分布规律,应力场分布规律。
[Abstract]:The structural location of Xushen gas field is located in the Shengping Xingcheng structural belt of Xujiaweizi fault depression in the southeastern fault depression of the deep structural unit in the northern Songliao Basin, which has the dual genetic mechanism of volcanic activity and tectonic movement. There are considerable oil and gas reservoir rocks in this area, which have a good development prospect. The volcanic rock reservoirs in Xushen gas field are characterized by deep burial, low porosity and low permeability, serious heterogeneity and so on. The types of pore fractures are mainly porosity, corrosion pore, fracture type combination and porosity, fracture type combination, natural fracture distribution, complex variation of in-situ stress, etc. On the basis of tectonic stress field method, nonlinear theory and seismic method, there are some limitations in obtaining density distribution of fracture around well and high density area. In addition, the density of well pattern is low and the distribution is uneven in the early stage of gas reservoir development. It is difficult to analyze the fracture density around the wellbore, and the description of reservoir fracture is confined to the well control range. It is difficult to understand the field of in-situ stress for the distribution of natural fractures. In this case, it is urgent to develop new technology, make comprehensive use of many fields and methods to predict reservoir fractures, and guide the development of oil and gas fields. Based on the theories of rock mechanics, structural mechanics and related fracture surface extension, this paper establishes an intelligent neural network model by collecting the block foundation data and logging data, and combining with the spatial extension technology of wellbore fractures. The logging data are used to identify and analyze the borehole wall fractures, and the spatial extension and stress field analysis of the borehole wall fractures are carried out. Finally, the distribution law of high density area and stress field of wellbore fracture are obtained.
【学位授予单位】：东北石油大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TE37;P618.13

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