特低渗透砂质砾岩储层裂缝识别及预测研究——以准噶尔盆地西北缘红153井区为例
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摘要
储层裂缝识别及预测的常用方法有常规测井及成像测井技术,主要应用于碳酸盐岩和砂岩储层,对特低渗透砂质砾岩储层裂缝研究较少,目前缺乏有效的预测手段。以准噶尔盆地红153井区特低渗透砂质砾岩储层为例,建立了一套集地质、地震、测井等技术手段于一体的砂质砾岩油藏裂缝定量表征方法。首先通过岩心、薄片等资料分析裂缝成因、发育特征及主控因素,开展裂缝特征宏观描述,在此基础上,综合利用岩心资料、成像测井及常规测井资料,建立特低渗透砂质砾岩油藏测井裂缝识别模式和解释模型,进行单井裂缝识别和预测;然后通过提取地震叠前各向异性,并结合地震资料、井资料及该区的沉积特征,开展裂缝密度、裂缝方位等规律预测;最后通过岩心、成像测井以及试油试采等资料对裂缝的识别和预测结果进行验证。应用结果表明,红153井区裂缝识别准确率达71.3%,地震叠前裂缝预测结果和实际生产情况吻合良好。
Common methods of reservoir fracture identification and prediction include conventional well logging and FMI logging technologies, which are mainly applied to carbonate and sandstone reservoirs. However, less studies were carried out, and no effective method for fracture identification and prediction of sandy conglomerate reservoirs with ultra-low permeability. In this study, taking the sandy conglomerate reservoir with ultra-low permeability in Well Hong 153 in the Junggar Basin as an example, a quantitative characterization method has been established, which integrates geological, seismic and well logging techniques. First, the causes, development characteristics and main controlling factors of fractures are analyzed by cores, thin sections and other data to describe fractures at macroscope scale; second, fracture identification and interpretation models are built using core, FMI logging and conventional logging data, which are used for singlewell fracture identification and prediction of sandy conglomerate reservoirs with ultra-low permeability; third, after extracting prestack seismic anisotropic attributes, fracture density and orientation are predicted based on seismic, well and sedimentary data; finally fracture identification and prediction results are verified by core, FMI logging, well and production test data. Application of the method to Well Hong 153 shows that the accuracy of fracture identification is 71.3%, and proves that the fracture prediction results from pre-stack seismic data are in good agreement with the actual production conditions.
Common methods of reservoir fracture identification and prediction include conventional well logging and FMI logging technologies, which are mainly applied to carbonate and sandstone reservoirs. However, less studies were carried out, and no effective method for fracture identification and prediction of sandy conglomerate reservoirs with ultra-low permeability. In this study, taking the sandy conglomerate reservoir with ultra-low permeability in Well Hong 153 in the Junggar Basin as an example, a quantitative characterization method has been established, which integrates geological, seismic and well logging techniques. First, the causes, development characteristics and main controlling factors of fractures are analyzed by cores, thin sections and other data to describe fractures at macroscope scale; second, fracture identification and interpretation models are built using core, FMI logging and conventional logging data, which are used for singlewell fracture identification and prediction of sandy conglomerate reservoirs with ultra-low permeability; third, after extracting prestack seismic anisotropic attributes, fracture density and orientation are predicted based on seismic, well and sedimentary data; finally fracture identification and prediction results are verified by core, FMI logging, well and production test data. Application of the method to Well Hong 153 shows that the accuracy of fracture identification is 71.3%, and proves that the fracture prediction results from pre-stack seismic data are in good agreement with the actual production conditions.
引文
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