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Unravelling Potential of a Volcanic Reservoir Through Enhanced Facies Understanding-A Case Study from Barmer Basin, India

机译:通过增强的面部理解的火山水库的解开潜力 - 印度竞技池盆地的案例研究

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The Raageshwari Deep Gas (RDG) Field, situated in the southern part of Barmer Basin, is a tight gascondensate reservoir comprising of Volcanics with basic lava flows (basalts) and stacked silicic pyroclastic flows (felsic) interbedded with basalts, and overlying clastic Fatehgarh Formation. The field is currently being developed using deviated wells with multi-stage hydraulic fracturing. The volcanic rocks pose a significant challenge in reservoir zone identification and trend prediction. Variability in mineralogy, lithofacies, thickness of reservoir subunits and areal distributions of pores/vesicles and fractures results in marked reservoir heterogeneity. This paper demonstrates a comprehensive facies characterization for pay zone identification, building a robust reservoir model and execution of multistage hydro-fracturing. The facies characterization methodology integrates cores, mudlogs (gas shows and chromatographs), wireline logs, hydraulic fracturing and production data. Conventional (sand-shale) petrophysical workflows are not applicable to volcanic rocks that are fundamentally different in nature. Hence a new unconventional work flow was established and validated in pilot wells. It was evident that the key parameter to address would be permeability given the tight nature of the formation (micro-pores). An initial facies classification was conceptualized integrating basic suite of logs and core data. New learnings on well performance behavior were assimilated with NMR log data in further refining the facies model. Higher gas counts and higher productivity was found to be associated with higher NMR bins indicative of larger pores and hence better facies. The pay zones identified based on refined facies model helped in optimizing hydraulic fracturing of around 100 zones in 15 wells in recently concluded Hydro-frac campaign. The pin pointing of better producible zones in an approximately 700 m thick volcanic package facilitated reduction in operational costs. Multiple perforations (clusters) were combined in each fracturing stage; injectivity of individual cluster was checked during mini-frac and post fracture temperature analysis resulting in an optimized hydrofrac job. Production logging was carried out to confirm contribution from stimulated intervals. It was observed that almost all fractured intervals were contributing to production validating the petrophysical work. Improved facies classification was also built into the reservoir model thus improving the property distribution and reservoir predictability away from the wellbore. This study facilitated in building a robust history matched reservoir simulation model for realistic production forecasting.
机译:所述拉格什沃里深层气(RDG)字段,位于巴尔梅尔盆地的南部,是一个严密的gascondensate储层包含火山岩的基本熔岩流(玄武岩)和堆叠硅酸火山碎屑流(英质)与玄武岩互,和上覆碎屑法泰赫加尔形成。该油田目前正在采用斜井多级水力压裂开发。火山岩构成水库区识别和趋势预测一个显著的挑战。变异矿物学,岩相,储层亚基的厚度和分布区孔/囊泡和在标记储层非均质性骨折结果的分布。本文阐述了对油层识别的综合相特征,构建多级水力压裂的稳健油藏模型和执行。岩相表征方法集成芯,mudlogs(气体节目和色谱仪),电缆测井,水力压裂和生产数据。常规(砂泥岩)岩石物理工作流程并不适用于火山岩是在本质上根本不同。因此,一个新的非常规工作流程建立和试验井验证。很明显,对地址的关键参数将被赋予渗透性的地层的性质紧(微孔)。初始相分类被概念化积分日志和核心数据的基本套件。上以及性能表现新学在进一步细化相模型NMR测井资料同化。发现较高的气体数量和更高的生产率更高的NMR箱指示毛孔变大,从而更好地相待相关。薪酬区基础上,在最近结束的水力压裂活动15口井优化大约100区的水力压裂帮助改进相模型识别。在一个约700微米厚的火山包促进了操作成本减少更好可生产区的指向销。多个穿孔(簇)合并在每个压裂阶段;单个集群的注入期间小型压裂和后断裂温度分析从而得到优化hydrofrac作业检查。生产测井进行从刺激间隔确认的贡献。据观察,几乎所有断裂的间隔促进生产验证的岩石物性的工作。改进相分类也被内置到储层模型从而提高财产分配和储层预测从井筒路程。这项研究在建设现实的产能预测一个强大的历史拟合油藏模拟模型提供便利。

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