基于流动单元的碳酸盐岩油藏剩余油分布规律  

A study on remaining oil distribution in a carbonate oil reservoir based on reservoir flow units

作　　者：范子菲[1] 李孔绸[1] 李建新[1] 宋珩[1] 何伶[1,2] 吴学林[1] 

机构地区：[1]中国石油勘探开发研究院 [2]长江大学

出　　处：《石油勘探与开发》2014年第5期578-584,共7页Petroleum Exploration and Development

基　　金：中国石油天然气股份有限公司重大科技专项(2011E-2504)

摘　　要：让纳若尔裂缝孔隙性碳酸盐岩油田Г北油藏储集层类型复杂多样,根据孔隙类型及其组合方式和不同孔隙组合的孔渗关系,将储集层划分为孔洞缝复合型、裂缝孔隙型、孔隙型和裂缝型4种类型,并实现了储集层类型的测井识别。孔洞缝复合型和裂缝型同类型储集层之间动用程度差异小,裂缝孔隙型和孔隙型同类型储集层之间动用程度差异较大,为了更准确地评价储集层动用的难易程度,优选了影响储集层动用程度的关键参数,裂缝孔隙型储集层为:储集层品质指数、饱和度中值喉道半径、总渗透率、裂缝渗透率与基质渗透率之比;孔隙型储集层为:储集层品质指数、饱和度中值喉道半径和基质渗透率。综合考虑基质和裂缝建立双重介质储集层流动单元划分方法,以关键参数作为聚类变量,利用神经网络聚类分析技术,将4种储集层类型划分为6类流动单元。建立流动单元三维地质模型和数值模拟模型,表征剩余油分布规律。根据剩余油研究结果,Г北油藏2013年投产8口井,初期日产油为周围老井的2.3倍。Reservoir F north, which belongs to Zhanzhol, Kazakhstan a fracture-pore typed carbonate oilfield, has a variety of reservoir types. According to the combination pattern of different voids and the relationship between porosity and permeability, carbonate reservoirs are classified into four types which are fracture-cavity-pore typed, fracture-pore typed, pore typed and fracture typed, and the identification of which by well logging data is realized. There is a little difference in the producing degree within the same reservoir type for fracture-cavity-pore typed and fracture typed reservoirs. However, there are large differences in the producing degree for fracture-pore typed and pore typed reservoirs. In order to appraise the producing degree of reservoirs more exactly, key parameters affecting the producing degree of fracture-pore typed and pore typed reservoirs are selected separately, which, for the fracture-pore typed are reservoir quality index （RQI）, pore throat radius at mercury saturation of 50% （R50）, total permeability （Kf＋Km）, and the ratio of fracture permeability to matrix permeability （Kf/Km）, and for the pore typed are RQI, R50, and matrix permeability （Kin）. With the integrated consideration of matrix and fracture, a flow unit classification method for dual medium reservoir is established, and taking these parameters as clustering variants, four types of reservoirs are further divided into six kinds of reservoir flow units by the means of neural network clustering technology. Based on reservoir flow unit modeling, a numerical simulation model is built with each type of reservoir flow units adopting its corresponding relative permeability curve, based on which, the distribution regularity of remaining oil of reservoir Г north is studied and demonstrated. Eight new wells are designed according to the research result, and put into production in 2013 with the initial daily oil production rate being 2.3 times that of nearby old wells.

关 键 词：碳酸盐岩油藏 储集层类型 流动单元 神经网络聚类分析 流动单元模型 剩余油 

分 类 号：TE344[石油与天然气工程—油气田开发工程]