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Reservoir Zonation - A Novel Approach: Use of Core Derived K-?-Swirr Relationship to Define Reservoir Rock Types (RRTs)

机译:水库分区 - 一种新方法:使用核心衍生的K - α - 摇头关系来定义储层岩石类型(RRT)

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Rock typing is an essential reservoir characterization tool to reflect the spatial variation in initial fluid distribution and flow behavior characteristics. Rock typing techniques are generally based on porositypermeability relationships to establish the types of rocks present in the reservoir. These techniques lack in effective segregation of reservoir into definite number of zones/rock-types with clear boundaries. This results in a non-unique rock-typing scheme with arbitrary number of RRTs depending on data manipulation. Moreover, these RRTs do not correspond to separate J-function curves due to negligence to water saturation term. To overcome these problems, a new approach for reservoir zonation is developed which has been tested in a few off-shore sandstone reservoirs. This paper illustrates a robust method of rock typing using a new theoretical development and mathematical formulation. The method integrates irreducible water saturation term with modified Carmen- Kozney equation using a proposed pore-throat dependent water saturation function [S_(wirr) = exp (-ar~t)]. The generalized porosity-permeability-saturation equation [K = A?~3(lnS_(wirr))~B] thus derived is fitted on the Routine Core Analysis (RCAL) data for division of reservoir section into different layers having unique coefficient-exponent set (A, B) representing RRTs. Application of this method resulted in an effective RRT scheme as evident from the unique coefficientexponent sets as well as separate J-function curves. The unique porosity-permeability-saturation relationship existing for each RRT has been thus obtained from the RCAL data. This relationship can be used as an efficient tool for reservoir zonation. Reservoir zonation algorithm, analysis results and validation procedures are discussed using field examples. Reservoir characterization is the key to improve reservoir performance prediction and recovery optimization. This paper presents a novel approach to effectively segregate the reservoir into definite number of RRTs using only RCAL data. This work also presents a theoretically derived K-?-Swirr relationship based on pore scale attributes. Irreducible water saturation, being an eminent parameter describing the internal architecture of the rock, is included in formulation and derivation of a theoretical framework to address classification of RRTs.
机译:摇滚键入是一种必要的储层表征工具,以反映初始流体分布和流动行为特性的空间变化。岩石键入技术通常基于孔隙率关系,以建立储层中存在的岩石类型。这些技术缺乏对水库的有效分离,以明确的区域/岩石类型具有透明的边界。这导致非独特的摇型方案,其具有任意数量的RRT,这取决于数据操纵。此外,由于对水饱和术语的疏忽,这些RRT不对应于单独的J函数曲线。为了克服这些问题,开发了一种新的储层区划方法,已经在一些离岸砂岩储层中进行了测试。本文说明了一种利用新的理论开发和数学制定的岩石打字的鲁棒方法。该方法使用所提出的孔喉依赖性水饱和函数与改性的Carmen-Kozney方程集成了不可缩续的水饱和术语[S_(WIRR)= EXP(-AR〜T)]。由此导出的广义孔隙率 - 渗透率饱和方程[k = a〜3(LNS_(WIRR))〜b]安装在储存器部分的常规核心分析(RCAL)数据中,用于具有独特系数的不同层设置(a,b)表示rrts。该方法的应用导致有效的RRT方案,从唯一的系数展开集以及单独的J函数曲线中是明显的。因此,从RCAL数据获得了每个RRT的独特孔隙率 - 渗透关系。这种关系可以用作水库区分区的有效工具。使用现场示例讨论了水库分区算法,分析结果和验证程序。储层表征是提高水库性能预测和恢复优化的关键。本文介绍了一种新的方法,可以仅使用RCAL数据将库分成明确数量的RRT。这项工作还呈现了基于孔隙率属性的理论上衍生的K - α - 播码关系。不可挽回的水饱和度是描述岩石内部架构的突出参数,包括在理论和推导的理论框架中,以解决rrts分类的理论框架。

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