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Reservoir Characterisation and Evaluation of Micaceous sandstone of Geleki Field,Upper Assam, India - An Integrated Study

机译:印度上阿萨姆邦格勒基油田云母砂岩储层特征与评价-综合研究

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Tipam sandstone, the main hydrocarbon-producingrnreservoir of Geleki Field located in Upper Assam,rnIndia, is of highly complex nature containing goodrnamount of mica (Muscovite) in addition to quartz,rnfeldspar and montmorillonite as inferred fromrnsedimentological studies. Mica complicates logrnanalysis as most lithology indicators reflect it asrnhigh-density shale, resulting in pessimistic reservoirrnevaluation.rnMica is often misinterpreted as shale by commonrnclay indicators used in conventional deterministicrninterpretation models based upon Density-Neutron-GRrnlogs. However, mica should be considered asrnstructural part of the rock not affecting porosity andrnpermeability. Surface of mica is altered byrndiagenesis and acquires surface conductancernleading to reduced resistivity of the formation evenrnat constant porosity. Therefore, if mica is notrnincluded in lithological model the evaluation can bernmisleading. Further, high computed shale volumernwill make good reservoirs either appear worthlessrnor with reduced potential.In the present paper, the influence of mica onrnvarious log responses has been analysed, basedrnupon which a highly micaceous sandstone facie hasrnbeen identified in the upper portion of the reservoir.rnHowever, presence of mica and feldspar inrnmoderate proportions is inferred throughout thernformation. Multi-mineral interpretation model basedrnupon statistical inverse modeling technique hasrnbeen successfully used for realistic evaluation ofrnreservoir parameters leading to identification of newrnhydrocarbon bearing layers.rnOil production from a well tested on the basis of thernpresent integrated study has confirmed the efficacyrnof the suggested model. Extension of the model tornother similar reservoirs can lead to better reservoirrncharacterization and delineation of by-passedrnhydrocarbons.
机译:Tipam砂岩是位于印度上阿萨姆邦的Geleki油田主要的生烃储层,具有极高的复杂性,根据沉积学研究推断,它还含有优质的云母(白云母)以及石英,长石和蒙脱石。云母使测井分析复杂化,因为大多数岩性指标将其反映为高密度页岩,从而导致悲观的储层评价。常规的基于密度-中子-GRrnlogs的常规确定性解释模型中使用的普通粘土指标常常将云母误认为页岩。但是,应将云母视为岩石的结构部分,而不影响孔隙度和渗透率。云母的表面因成岩作用而改变,并获得了表面电导,从而导致即使恒定的孔隙度也降低了地层的电阻率。因此,如果未将云母包括在岩性模型中,则评估可能会产生误导。此外,高计算页岩量将使好的储层显得毫无价值或潜力降低。本文基于云母在储层上部识别出的高云母砂岩相,分析了云母对各种测井响应的影响。 ,在整个信息中推断出云母和长石的比例中等。基于多矿物解释模型的统计反演模型技术已成功用于储层参数的现实评价,从而确定了新的含烃层。在现有综合研究的基础上,经过测试的油井已经证实了该模型的有效性。将模型扩展到其他类似的储层可以导致更好的储层特征和绕过的烃的描述。

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