滨里海盆地S地区盐上层系储层测井解释方法研究

发布时间：2018-02-23 17:50

本文关键词： 岩性识别四性特征解释模型流体识别　出处：《中国石油大学(华东)》2015年硕士论文　论文类型：学位论文

【摘要】：滨里海盆地S地区盐上层系储层岩性复杂,砂岩灰质或泥质胶结,纵向非均质性强,电性曲线受岩性及矿化度的影响较大,无法准确反映储层中真实的流体信息;同时构造单元多,不同区块内储层的物性、电性、含油性以及储层的下限值存在差异,采用相同的解释参数和解释模型在识别岩性及流体性质上精度不高。本论文以S地区A区块和T区块为主要研究对象,开展盐上储层的测井解释方法研究,建立一套盐上层系储层的测井评价体系,提高该地区的测井解释精度。首先从盐上地层的形成机理、沉积相和油气运移、成藏特征入手,对主要研究区块的地层进行了测井响应特征研究,对比了不用层位储层的特征,利用岩心和大量的测井资料分层位分析了该区块油(气)层、水层分布及测井响应特征;分析以三叠系砂岩储层为主的岩心资料,分层位对储层的岩性、物性、电性和含油性特征进行分析,利用岩心相渗分析结果,对高产油层的孔隙结构进行了研究,并针对阵列感应测井资料所反映出的油层、水层和干层的不同侵入特征,剖析了差异产生的原因;深入研究其“四性”关系,结合岩心微观特征,分析了岩石粒度对储层物性、电性和含油性的影响。综合利用岩电参数、岩心资料、水分析资料、地质录井资料和试油资料,采用数学方法分区块建立了三叠系储层泥质含量、孔隙度、渗透率评价模型,在泥质校正的基础上深入分析了粒度、碳酸盐岩含量和泥质含量对储层孔隙度、渗透率的影响;确定了地层水电阻率等饱和度评价模型的关键参数。在阵列感应侵入特征的基础上,选取敏感曲线,利用阵列感应比值法识别流体性质;形成利用岩心相渗分析结果和测井曲线之间的对应关系识别油、水层,以及采用孔隙度-电阻率-含水饱和度、P1/2正态分布、可动油饱和度-视地层水电阻率交会法识别流体性质;对测井系列进行优化设计,最终形成了一套适合该地区的测井解释方法。应用该套解释方法对测井资料进行了二次复查,提高了解释精度,进一步增加了S地区盐上层系储层的特征认识,对提高勘探开发效率有一定的促进作用。
[Abstract]:The lithology of the upper salt reservoirs in the S area of the Caspian Basin is complex, the sandstone limestone or muddy is cemented, the longitudinal heterogeneity is strong, the electric curve is greatly affected by lithology and salinity, and the true fluid information in the reservoir can not be accurately reflected. At the same time, there are many structural units, and there are differences in the physical properties, electrical properties, oil content and the lower limit of the reservoir in different blocks. The accuracy of identifying lithology and fluid properties by using the same interpretation parameters and models is not high. In this paper, A block and T block in S area are taken as the main research objects, and the logging interpretation method of upper salt reservoir is studied. A set of logging evaluation system for the upper salt reservoir is established to improve the logging interpretation accuracy in this area. Firstly, the formation mechanism, sedimentary facies, hydrocarbon migration and reservoir forming characteristics of the upper salt formation are discussed. The logging response characteristics of the main study block are studied, and the characteristics of the non-horizon reservoir are compared. The oil (gas) layer, water layer distribution and logging response characteristics of the block are analyzed by using the core and a large amount of logging data. Based on the core data of the Triassic sandstone reservoir, the characteristics of lithology, physical property, electrical property and oil content of the reservoir are analyzed by stratification, and the pore structure of the high-yielding reservoir is studied by using the results of the core permeability analysis. According to the different intrusive characteristics of oil layer, water layer and dry layer reflected by array induction logging data, the causes of the difference are analyzed, and the relationship of "four properties" is deeply studied, and the relationship between rock particle size and reservoir physical property is analyzed in combination with the microscopic characteristics of core. Comprehensive use of rock electrical parameters, core data, water analysis data, geological logging data and oil test data, mathematical method is used to block the Triassic reservoir muddy content, porosity, permeability evaluation model. On the basis of muddy correction, the effects of particle size, carbonate rock content and mud content on reservoir porosity and permeability are analyzed. The key parameters of the evaluation model of formation water resistivity and equal saturation are determined. On the basis of the invading characteristics of array induction the sensitive curves are selected and the fluid properties are identified by array induction ratio method. The formation uses the correspondence relationship between core facies and permeability analysis results and log curves to identify oil, water layer, and P 1 / 2 normal distribution by using porosity, resistivity and water saturation. The movable oil saturation-apparent formation water resistivity intersection method is used to identify the fluid properties, and a set of logging interpretation methods suitable for this area are formed by optimizing the well logging series. The logging data are rechecked twice by using this set of interpretation methods. The interpretation accuracy is improved, and the recognition of the characteristics of the upper salt reservoirs in S area is further increased, which can promote the efficiency of exploration and development to a certain extent.
【学位授予单位】：中国石油大学(华东)
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：P618.13;P631.81

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