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首页> 外文期刊>Journal of Petroleum Science & Engineering >Combine the capillary pressure curve data with the porosity to improve the prediction precision of permeability of sandstone reservoir
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Combine the capillary pressure curve data with the porosity to improve the prediction precision of permeability of sandstone reservoir

机译:将毛管压力曲线数据与孔隙度相结合,提高砂岩储层渗透率的预测精度

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摘要

Permeability is a critical parameter that reflects the nature of reservoir, playing a crucial role in the development of oil field. It is difficult to accurately calculate the permeability parameter in reservoir evaluation. Capillary pressure curve represents pore-throat size and distribution of reservoir rocks, and as for the porous sandstone, absolute permeability of rock depends primarily on the pore throat distribution. This paper has improved the estimation model for permeability established by Swanson, adding porosity factor, and has successfully established the absolute permeability estimation model for sandstone using Capillary-Parachor parameters. The permeability of 30 rock samples is estimated by using the above-described two kinds of model respectively. The result shows that the permeability estimated by the improved model is in good agreement with the value of permeability of core testing, and has made some improvement in the precision when compared to the permeability estimation model established by Swanson. (C) 2015 Elsevier B.V. All rights reserved.
机译:渗透率是反映储层性质的关键参数,在油田开发中起着至关重要的作用。在储层评价中很难准确计算渗透率参数。毛细压力曲线代表孔喉的大小和储集岩的分布,对于多孔砂岩,岩石的绝对渗透率主要取决于孔喉的分布。本文对斯旺森建立的渗透率估算模型进行了改进,增加了孔隙度因子,并利用毛细管-参量参数成功建立了砂岩的绝对渗透率估算模型。通过分别使用上述两种模型来估计30个岩石样品的渗透率。结果表明,与斯旺森建立的渗透率估算模型相比,改进模型估算的渗透率与岩心测试的渗透率值吻合良好,精度有所提高。 (C)2015 Elsevier B.V.保留所有权利。

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