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A laboratory study to estimate pore geometric parameters of sandstones using complex conductivity and nuclear magnetic resonance for permeability prediction

机译:利用复电导率和核磁共振预测渗透率的砂岩孔隙几何参数实验室研究

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摘要

We estimate parameters from the Katz and Thompson permeability model using laboratory complex electrical conductivity (CC) and nuclear magnetic resonance (NMR) data to build permeability models parameterized with geophysical measurements. We use the Katz and Thompson model based on the characteristic hydraulic length scale, determined from mercury injection capillary pressure estimates of pore throat size, and the intrinsic formation factor, determined from multi-salinity conductivity measurements, for this purpose. Two new permeability models are tested, one based on CC data and another that incorporates CC and NMR data. From measurements made on forty-five sandstone cores collected from fifteen different formations, we evaluate how well the CC relaxation time and the NMR transverse relaxation times compare to the characteristic hydraulic length scale and how well the formation factor estimated from CC parameters compares to the intrinsic formation factor. We find: (1) the NMR transverse relaxation time models the characteristic hydraulic length scale more accurately than the CC relaxation time (R2 of 0.69 and 0.39 and normalized root mean square errors (NRMSE) of 0.16 and 0.20, respectively); (2) the CC estimated formation factor is well correlated with the intrinsic formation factor (NRMSE=0.23). We demonstrate that that permeability estimates from the joint-NMR-CC model (NRMSE=0.13) compare favorably to estimates from the Katz and Thompson model (NRMSE=0.074). This model advances the capability of the Katz and Thompson model by employing parameters measureable in the field giving it the potential to more accurately estimate permeability using geophysical measurements than are currently possible.
机译:我们使用实验室复数电导率(CC)和核磁共振(NMR)数据从Katz和Thompson渗透率模型估算参数,以建立用地球物理测量参数化的渗透率模型。为此,我们基于特征水力长度尺度(由孔喉尺寸的汞注入毛细管压力估计值确定)和固有形成因子(由多盐度电导率测量确定)来使用Katz和Thompson模型。测试了两个新的渗透率模型,一个基于CC数据,另一个基于CC和NMR数据。通过对从15个不同地层中收集的45个砂岩岩心进行的测量,我们评估了CC弛豫时间和NMR横向弛豫时间与特征水力长度尺度的对比程度以及根据CC参数估算的地层因子与本征水力尺度的对比程度形成因素。我们发现:(1)NMR横向弛豫时间比CC弛豫时间更准确地模拟了特征水力长度尺度(R2为0.69和0.39,归一化均方根误差(NRMSE)分别为0.16和0.20); (2)CC估计形成因子与内在形成因子具有很好的相关性(NRMSE = 0.23)。我们证明,联合NMR-CC模型(NRMSE = 0.13)的渗透率估计值与Katz和Thompson模型(NRMSE = 0.074)的估计值相比具有优势。该模型通过采用可在现场测量的参数来提高Katz和Thompson模型的能力,从而使它有可能比目前可能的方法更精确地使用地球物理测量方法来估算渗透率。

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