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川中地区龙王庙组颗粒滩储层关键参数计算及评价 被引量:4

Calculation and Evaluation of Key Parameters for Grain Beach Reservoir of Longwangmiao Formation in Central Sichuan Area
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摘要 四川盆地乐山-龙女寺古隆起中段下古生界寒武系龙王庙组主要为局限台地沉积,优质储层主要分布于颗粒滩亚相。颗粒滩储层经历多期改造作用,为典型的深埋藏滩相岩溶储集层,呈现孔隙度低、非均质性强、孔隙结构复杂的特点。从岩心入手,结合高分辨电成像测井资料,根据滩相沉积学理论,建立龙王庙组颗粒滩相识别模式。利用特殊的处理技术,建立储层溶洞、孔隙结构和渗滤能力3个关键参数的计算和评价方法,构建储层品质分级评价模型及标准,并在100余口井的实践中效果显著,测井解释符合率达95.8%。该技术方法为中国单体规模最大的特大型海相碳酸盐岩整装气藏的发现和探明提供支撑。 Lower Palaeozoic Cambrian Longwangmiao formation of Leshan-longnusi palaeohigh midpiece in Sichuan basin is mainly limited platform deposition,and high-quality reservoirs are mainly distributed in granular beach subfacies.After multi-period reworking,the grain beach reservoirs changed to typical deep-buried beach facies karst reservoirs,which have low porosity,high anisotropy,and complex pore structure.Based on the data of cores and high resolution imaging well logging,this paper build the grain beach facies identification method and pattern of Longwangmiao formation according to the theory of beach facies sedimentary.And this paper also build the calculation and evaluation method of karst carve,pore structure and permeability ability based on the special processing technology at the same time.Then this paper build the grading evaluation model and standard of reservoir quality,which is identified by more than 100 wells,and the interpretation coincidence rate reaches 95.8%.This achievement played an important role in the discovery and provement of the extra-large marine facies carbonate integrated gas reservoir with the largest monomer scales in China and the 30 billion cubic metre increasing reserve.
作者 贺洪举 齐宝权 苗清 黄宏 陈邦定 丁邦春 HE Hongju;QI Baoquan;MIAO Qing;HUANG Hong;CHEN Bangding;DING Bangchun(Southwest Branch, China Petroleum Logging CO. LTD., Chongqing 400021, China)
出处 《测井技术》 CAS 2021年第5期514-520,共7页 Well Logging Technology
基金 中国石油重大科技专项“西南油气田天然气上产300亿立方米关键技术研究与应用”(XNS14JS2017-124)。
关键词 颗粒滩 识别模式 溶洞 孔隙结构 渗滤能力 模型 分级标准 川中地区 grain beach identification pattern karst carve pore structure permeability ability model grading standard central Sichuan basin
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