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基于流动单元和阵列声波测井的储层渗透率计算
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Abstract:
对于孔隙结构复杂的储层,现有的基于常规测井的渗透率模型计算精度低,无法满足生产需要。基于孔隙结构对储层进行分类,并根据测井资料的丰富程度提出两类渗透率计算模型:对于常规测井曲线齐全的井,利用测井曲线计算储层流动单元指数FZI,并进行储层分类识别,每一类储层单独建立渗透率模型;对于有阵列声波测井曲线的井,通过交会图筛选渗透率敏感参数,并建立基于阵列声波的渗透率模型。研究结果表明:声波时差(AC)、补偿密度(DEN)、补偿中子(CNL)测井曲线可准确计算流动单元指数FZI并识别I类、II类、III类储层,常规测井和阵列声波测井获得的密度曲线、泥质含量、斯通利波时差和泊松比等参数与渗透率相关性较高,基于这些参数建立的三因子指数模型对I类储层和II类储层适用性较好,双因子幂乘模型对III类储层适用性较好。基于流动单元和基于阵列声波的渗透率模型提高了复杂孔隙结构储层的渗透率计算精度,有效地支撑了气藏的高效勘探与开发。
For reservoir with complex pore structure, the calculation accuracy of existing permeability model based on conventional logging is low and cannot meet production needs. The reservoir is classified based on pore structure, and two permeability calculation models are proposed according to the abundance of logging data. For Wells with complete conventional logging curves, the reservoir flow unit index FZI is calculated by logging curves, and the reservoir is classified and identified. For Wells with array acoustic logging curves, permeability sensitive parameters are screened by cross plot and permeability model based on array acoustic logging is established. The results show that: Acoustic time difference (AC), compensated density (DEN), and compensated neutron (CNL) logs can accurately calculate flow unit index FZI and identify class I, II, and III reservoirs. Density curves, shale content, Stoneley wave time difference, poisson’s ratio and other parameters obtained from conventional and array acoustic logs are highly correlated with permeability. The three-factor exponential model based on these parameters is suitable for class I reservoir and class II reservoir, and the two-factor power model is suitable for class III reservoir. The permeability model based on flow unit and array acoustic wave improves the calculation accuracy of permeability of complex pore structure reservoir and supports efficient exploration and development of gas reservoir effectively.
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