基于阵列感应测井资料的油气层产能预测

在勘探阶段资料较少的情况下．应用测井资料预测产能一直是测井评价中的难题，特别是对低渗透、孔隙结构复杂的储集层产能预测更是如此．其原因主要是常规测井资抖与产能的相关性差。通过对油气层产能影响因素、阵列感应测井探测特性和钻井液滤液对油气层侵入特点的分析，研究储集层中原始流体被冲洗的程度，据此确定地层的渗流特性。由达西定律出发，建立了根据阵列感应测井资料确定储集层渗流特性参数的方法，进而预测（或估计）产能。实际资料证实，该渗流特性参数不但与储集层的孔隙直径和喉道直径关系密切，而且与油气层产能具有较高的相关性（相关系数为0．9343）。据此，可针对具体油气藏，在勘探阶段应用阵列感应测井资料预测油气层产能。

Reservoir productivity prediction by array induction logging data

In the exploration stage, it is very difficult to predict the productivity with logging data because necessary information is unavailable, especially in low permeable reservoir with complex pore texture. The percolation performance of the reservoir fluid is studied by influence factors of reservoir productivity, detection properties of array induction and mud filter invasion characteristics, and by researching the washout level of the original reservoir fluid. The determining of characteristics of percolation flow through porous media is proposed by Darcy Law. Field data prove that the percolation parameters have good relations with pore diameter and throat diameter, and high correlativity with productivity of hydrocarbon reservoir (the correlation coefficient is 0.9343). Productivity of a certain reservoir could be predicted in using array induction logging data during petroleum exploration.