A Method to Quantitatively Characterize Tight Glutenite Reservoir Pore Structure

Xuemei Dong, Ting Zhang, Weijiang Yao, Tingting Hu, Jing Li, Chunming Jia, Jian Guan
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引用次数: 2

Abstract

Pore structure is of great importance in tight reservoirs identification and validation evaluation, especially for formations with developed fractured. However, the conventional pore structure evaluation method based on nuclear magnetic resonance (NMR) logging lost its role. This is because the fractures with width lower than 2mm did not have response in the NMR T2 spectrum. Whereas the porosity spectrum, which extracted from the FMI data, was considered to be effective in fractured reservoir pore structure evaluation. In this study, to quantitatively characterize tight glutenite reservoir pore structure in the Jiamuhe Formation in northwest margin of Junggar Basin, northwest China, 90 core samples were drilled for lab mercury injection capillary pressure (MICP) measurement, and the XRMI data (acquired by the Halliburton and be similar with FMI) was processed to acquire the porosity spectrum. The relationship between the MICP curve and the corresponding inverse cumulative curve of porosity spectra was analyzed, and the model of piecewise power function, which can be used to transform the porosity spectrum as pseudo capillary pressure (Pc) curve, was established. By using this model, consecutive pseudoPc curves can be constructed in the intervals with which XRMI data was acquired, and the corresponding pore structure evaluation parameters, such as the average pore throat radius, the maximum pore throat radius, the threshold pressure, and so on, can also be predicted. Meanwhile, a permeability prediction model based on the Swanson parameter, also established. By combining with the constructed consecutive pseudoPc curves, the pore structure evaluation parameters and permeabilities, several hydrocarbon production potential formations were identified, and this was verified by the drill stem test (DST) data.
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致密砂砾岩储层孔隙结构定量表征方法研究
孔隙结构在致密储层识别和有效性评价中具有重要意义,对于裂缝发育的储层尤为重要。然而,传统的基于核磁共振测井的孔隙结构评价方法失去了作用。这是因为宽度小于2mm的裂缝在核磁共振T2谱中没有响应。而从FMI数据中提取的孔隙度谱则被认为是裂缝性储层孔隙结构评价的有效方法。为了定量表征准噶尔盆地西北缘家木河组致密砂砾岩储层孔隙结构,采用90个岩心样品进行室内压汞毛细管压力(MICP)测量,并对哈里伯顿公司采集的与FMI相似的XRMI数据进行处理,获得孔隙度谱。分析了MICP曲线与相应的孔隙度谱逆累积曲线之间的关系,建立了分段幂函数模型,将孔隙度谱转换为拟毛管压力(Pc)曲线。利用该模型,可以在获取XRMI数据的区间内构建连续的伪opc曲线,并预测相应的孔隙结构评价参数,如平均孔喉半径、最大孔喉半径、阈值压力等。同时,建立了基于Swanson参数的渗透率预测模型。结合构建的连续伪opc曲线、孔隙结构评价参数和渗透率,识别出多个具有生产潜力的储层,并通过钻杆测试(DST)数据进行了验证。
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