Prediction of Microscopic Remaining Oil Distribution Using Fuzzy Comprehensive Evaluation

A network model is established through the techniques of image reconstruction, a thinning algorithm, and pore–throat information extraction with the aid of an industrial microfocus CT scanning system. In order to characterize actual rock pore–throat structure, the established model is modified according to the matching of experimental factors such as porosity, permeability, and the relative permeability curve. On this basis, the impacts of wetting angle, pore radius, shape factor, pore–throat ratio, and coordination number as applied to microscopic remaining oil distribution after water flooding are discussed. For a partially wetting condition, the displacement result of a water-wet pore is somewhat better than that of an oil-wet pore as a whole, and the possibility of any remaining oil is relatively low. Taking the comprehensive effects of various factors into account, a prediction method of remaining oil distribution is presented through the use of fuzzy comprehensive evaluation. It is seen that this method can predict whether there is remaining oil or not in the pore space with satisfactory accuracy, which is above 75%. This method thus provides guidance for a better understanding of the microscopic causes of the remaining oil.