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作 者:陈国军 潘拓 张帆 高明 毛晨飞 张啸 张文芊 范小秦 CHEN Guojun;PAN Tuo;ZHANG Fan;GAO Ming;MAO Chenfei;ZHANG Xiao;ZHANG Wenqian;FAN Xiaoqin(PetroChina Xinjiang Oilfield Company,Urumqi,Xinjiang 830013,China;CNPC Logging Company,Xi′an,Shaanxi 710077,China)
机构地区:[1]中国石油新疆油田分公司,新疆乌鲁木齐830013 [2]中国石油集团测井有限公司,陕西西安710077
出 处:《特种油气藏》2025年第1期71-78,共8页Special Oil & Gas Reservoirs
基 金:中国石油前瞻性基础性重大科技项目“煤层气勘探开发技术研究”(2021DJ2306)。
摘 要:针对深层煤岩储层孔隙度计算精度较低,浅部煤储层的产能关键因素评价方法难以适用于深层煤岩的产能预测等问题,提出了基于煤岩组分的变骨架孔隙度计算方法,并依据实测声波时差与重构声波时差比的含气饱和度计算模型等,构建了基质品质Q_(m)和结构品质Q_(s)两个模型,结合产能的高低,将煤岩储层划分为3类。研究表明:相较于浅部煤储层,深层煤储层的基质孔隙度、割理孔隙度、含气饱和度、煤体结构等是影响产能的关键因素;利用变骨架法孔隙度、双侧向法割理孔隙度、声波时差法含气饱和度等计算方法,提高了关键参数的计算精度,孔隙度计算精度由68.1%提升至90.5%;基于上述关键参数建立的产能分类评价方法,在深层中低煤阶储层中产能预测效果显著,产能预测符合率达到91.0%。该分类评价方法可为下一步煤层气勘探提供技术支撑。A variable skeleton porosity calculation method based on coal-rock components is proposed in this study to address the issues such as low accuracy in calculating the porosity of deep coal rock reservoirs and the difficulty in applying critical factors methods to evaluate production capacity in deep coal rocks whereas it is applicable in shallow coal reservoirs.Furthermore,two models,namely matrix quality(Q_(m))and structural quality(Q_(s)),are established based on gas saturation calculation models that are developed on the basis of ratios of measured acoustic travel time to reconstructed acoustic travel time.Based on these models and according to production capacity levels,the coal rock reservoirs are classified into three categories.The results show that compared to shallow coal reservoirs,the matrix porosity,cleat porosity,gas saturation,and coal mass structure of deep coal reservoirs are the primary factors affecting production capacity.The accuracy of porosity calculation with key parameters has improved by employing methods such as variable skeleton porosity,dual-lateral cleat porosity,and acoustic travel time method and gas saturation.Theprecision of porosity calculation has increased from 68.1%to 90.5%.The production capacity classification and evaluation method established on these key parameters has significant predictive effectiveness in deep low-medium rank coal reservoirs,achieving a prediction coincidence rate of 91.0%.This classification and evaluation method can provide technical support for the next coalbed methane exploration.
关 键 词:深层煤岩 中低阶煤 变骨架孔隙度 煤体结构 产能预测
分 类 号:TE122[石油与天然气工程—油气勘探]
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