Integration of conventional well logs and core samples to predict porosity of

To the reservoirs of the oil wells with no cored data, predicting porosity from wireline logs and core samples is an effective approach. Integration of conventional well logs and core samples to predict porosity with large accuracy is a particularly challenging work due to complex logging responses of tight sandstone. Therefore, a novel predicting workflow based on linear interpolation algorithm (LIA) is described to estimate porosity from well logs in the present study. Based on core reposition, porosity correction under overburden pressure, core-log data matching, and calculation of shale content, two multi regression formulas to estimate porosity values are obtained by nearest neighbor algorithm and linear interpolation algorithm respectively. The formulas are applied to the tight sandstone in Chang 9 member of Yanchang Formation in northeast Wuqi Oilfield, Ordos Basin. The comparison results indicate that the porosity predicted from the formula obtained by LIA is in better agreement with the measured porosity, showing a better prediction effect. The application example demonstrates that the LIA formula is of good applicability for the core porosity prediction in the study region. This methodology can further be applied for porosity prediction in other oil regions that have similarities in geological background.