储层岩石分型:地质属性与岩石物理属性的整合:以山山油藏为例

Maojun Qiu, Jiaju Yi
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引用次数: 0

摘要

为了建立支持伊拉克南部f油田评价和开发活动的全油田静态和动态模型,通过综合地质信息和岩石物理性质,对Yamama碳酸盐岩储层进行了全面的储层岩石类型研究。该过程首先包括整合地质信息(MICP、CT、薄片),以找到孔喉尺寸与岩石学信息之间的联系。通过岩心描述和沉积背景资料对这种关系进行了交叉检验。在常规岩心分析(RCAL)中纳入孔隙度和渗透率后,对岩石类型进行了识别,并在交叉图中进一步分组。由于并非所有具有渗透率和孔隙度的桥塞都具有MICP和薄片信息,因此有必要采用岩石织构数(RFN)、流动带指标(FZI)等经验岩石分型方法。根据岩心描述和岩石学描述(包括成岩叠层),确定哪种方法/分类方法可以更好地对具有地质意义的储层岩石类型(RRTs)进行分类。FZI方法与山山储层岩石分型具有较好的匹配性。每个RRT的Sw- height函数也使用Lamda方法创建,并通过有线测井衍生的Sw调整参数。在动态模型初始化过程中,实现了静态模型与动态模型之间Sw分布的相对一致性。通过特殊岩心分析(SCAL)为每个RRT分配相对渗透率。在历史匹配过程中,取得了良好的压力和产量匹配。针对岩心分析数据相对有限的典型基质型碳酸盐岩储层,提出了一种RRT工作流程。通过整合地质属性和岩石物理属性,在动态建模中获得了更好的历史匹配,可用于预测和未来的油藏管理活动。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Reservoir Rock Typing: Integration of Geological Attributes and Petrophysical Properties: Case Study from Yamama Reservoir
To build full-field static and dynamic models for supporting appraisal and development activities in F-Field in the southern part of Iraq, a comprehensive reservoir rock typing study for the Yamama carbonate reservoir was carried out by integrating geological information and petrophysical properties. This process involved first the integration of geological information (MICP, CT, thin section) to find the link between pore-throat sizes and petrographic information. The relationships were cross-checked by core descriptions with the depositional background information. After involving porosity and permeability from routine core analysis (RCAL), the rock types were identified and further grouped in the cross-plots. Because not all the plugs with permeability and porosity have MICP & thin section information, it was necessary to apply empirical rock typing methods, like rock fabrics number (RFN), flow zone indicator (FZI). Winland’s R35, to determine which method/classification could provide a better approach to classify the reservoir rock types (RRTs) with geological meanings based on core descriptions and petrographic description, which includes diagenetic overprints. The FZI method shows a better match with Yamama reservoir Rock Typing. Sw-Height functions for each RRT were also created by using the Lamda method, and the parameters were tuned by wireline log-derived Sw. During the initialization of the dynamic model, the relative consistency of Sw distribution between static and dynamic models was reached. The relative permeability from special core analysis (SCAL) was assigned for each RRT. During the history matching process, a good pressure and production rate match was achieved. This paper presents a RRT workflow for the typical matrix-based carbonate reservoirs with relatively limited core analysis data. By integrating the geological attributes and petrophysical properties, a better history match was achieved in the dynamic modelling, which could be used in forecasts and future reservoir management activities.
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