自适应逐次超松弛在大斜度井泥浆侵入模拟中的应用

Application of Self-adaptive Successive Relaxation to Simulating Mud-filtrate Invasion in Highly Deviated Well

为解决泥浆侵入过程中井眼周围孔隙流体分布特征,从而进一步分析储层电性变化,提出利用基于有限差分的自适应逐次超松弛方法(ASOR)对泥浆侵入过程中油水两相流问题进行数值模拟。结果表明,通过自动选择最佳松弛因子,使ASOR对具有复杂边界条件的大型稀疏矩阵求解速度大大提高。与逐次超松弛(SOR)方法相比,ASOR方法在计算时间上可以降低一半;通过计算油水两相流问题,得到泥浆侵入中井眼周围油水分布,结果与实际实验相一致,为斜井的解释与评价提供了理论基础。

In order to determine the pore fluid distributions and changes of electrical property in reservoir around borehole during mud invasion,proposed is an adaptive successive over relaxation iteration method（ASOR） based on the finite difference to solve the oil-water two-phase flow equations.The results show that the speed of ASOR is greatly improved by selecting optimal relaxation factor automatically for large sparse matrix with complex boundary conditions.Accordingly the computing time of ASOR is reduced by a half compared with the successive over relaxation method.The oil-water distribution in the surrounding area of borehole is obtained during mud invasion and is consistent with the experimental result,which offers theoretical basis for interpretation and evaluation of reservoir in the deviated wells.