Pore-by-pore modeling, analysis, and prediction of two-phase flow in mixed-wet rocks.,Physical Review E

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Pore-by-pore modeling, analysis, and prediction of two-phase flow in mixed-wet rocks.
Physical Review E ( IF 2.2 ) Pub Date : 2020-08-05 , DOI: 10.1103/physreve.102.023302
Sajjad Foroughi ₁ , Branko Bijeljic ₁ , Qingyang Lin ₁ , Ali Q Raeini ₁ , Martin J Blunt ₁

Affiliation

A pore-network model is an upscaled representation of the pore space and fluid displacement, which is used to simulate two-phase flow through porous media. We use the results of pore-scale imaging experiments to calibrate and validate our simulations, and specifically to find the pore-scale distribution of wettability. We employ energy balance to estimate an average, thermodynamic, contact angle in the model, which is used as the initial estimate of contact angle. We then adjust the contact angle of each pore to match the observed fluid configurations in the experiment as a nonlinear inverse problem. The proposed algorithm is implemented on two sets of steady state micro-computed-tomography experiments for water-wet and mixed-wet Bentheimer sandstone. As a result of the optimization, the pore-by-pore error between the model and experiment is decreased to less than that observed between repeat experiments on the same rock sample. After calibration and matching, the model predictions for capillary pressure and relative permeability are in good agreement with the experiments. The proposed algorithm leads to a distribution of contact angle around the thermodynamic contact angle. We show that the contact angle is spatially correlated over around 4 pore lengths, while larger pores tend to be more oil-wet. Using randomly assigned distributions of contact angle in the model results in poor predictions of relative permeability and capillary pressure, particularly for the mixed-wet case.

中文翻译：

混合湿岩石中两相流的逐孔建模，分析和预测。

孔隙网络模型是孔隙空间和流体驱替的放大表示，用于模拟通过多孔介质的两相流动。我们使用孔隙尺度成像实验的结果来校准和验证我们的模拟，尤其是找到润湿性的孔隙尺度分布。我们使用能量平衡来估计模型中的平均热力学接触角，该接触角用作接触角的初始估计。然后，我们将每个孔的接触角调整为与实验中观察到的流体配置相匹配，作为非线性逆问题。该算法在两组湿态和混合态本特海默砂岩的稳态微计算机断层实验中实现。经过优化，模型和实验之间的逐孔误差减小到小于相同岩石样品重复实验之间观察到的误差。经过校准和匹配后，毛细管压力和相对渗透率的模型预测与实验吻合良好。所提出的算法导致围绕热力学接触角的接触角分布。我们表明，接触角在大约4个孔长度上在空间上相关，而较大的孔往往更油润湿。在模型中使用随机分配的接触角分布会导致相对渗透率和毛细压力的预测不佳，尤其是在混合湿的情况下。毛细管压力和相对渗透率的模型预测与实验吻合良好。所提出的算法导致围绕热力学接触角的接触角分布。我们表明，接触角在大约4个孔长度上在空间上相关，而较大的孔往往更油润湿。在模型中使用随机分配的接触角分布会导致相对渗透率和毛细压力的预测不佳，尤其是在混合湿的情况下。毛细管压力和相对渗透率的模型预测与实验吻合良好。所提出的算法导致围绕热力学接触角的接触角分布。我们表明，接触角在大约4个孔长度上在空间上相关，而较大的孔往往更油润湿。在模型中使用随机分配的接触角分布会导致相对渗透率和毛细压力的预测不佳，尤其是在混合湿的情况下。

更新日期：2020-08-05

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