A new technique for determining water saturation based on conventional logs using dynamic electrical rock typing

Abstract

Fluid saturation in a hydrocarbon reservoir is the most significant parameter in evaluating reservoir resources. The possibility of developing a field completely depends on hydrocarbon saturation, which is normally obtained by well-known Archie's equations. Accurate determination of the hydrocarbon saturation depends on the precise estimation of the Archie's parameters, i.e. cementation factor, tortuosity factor and saturation exponent (n). Among these three parameters, experimental determination of saturation exponent is time consuming and expensive which is performed on a limited number of core samples. Although numerous correlations and methods have been presented for predicting the saturation exponent of the Archie's equation, most of them did not consider physics of electricity transmission through the pore structure of the rock. Classification of the reservoir rocks into distinct groups with the same electrical behavior can improve the precision of saturation estimation.In this paper, a new technique was presented to classify rock samples into distinct electrical rock types based on a recently defined parameter which was called dynamic electrical efficiency (ηele,D). Previously, Soleymanzadeh et al. suggested a method of electrical rock typing in water zone on the basis of static electrical efficiency (ηele,s). In fact, the present paper is an extension of Soleymanzadeh et al. work to apply in the hydrocarbon zone. According to the proposed method of electrical rock typing, all the rock samples with the same functionality with respect to the dynamic electrical efficiency, i.e. (ηele,D)1n, constitute an individual electrical rock type. Indeed, all the core samples with the same value of (ηele,D)1n lie on a straight line with the slope of one in the log-log plot of Swiversus1ηele,S1n. Using this method, water saturation can be estimated throughout the reservoir depth without the need to determine saturation exponent at any depth. In order to verify the new proposed technique, electrical data from 25 core samples were used which were categorized into four distinct classes on the basis of the proposed method of electrical rock typing. High value of determination coefficients and slopes near the one confirmed the application of the proposed method. Hence, it was concluded that dynamic electrical efficiency is an appropriate tool for classifying electrical data into distinct electrical rock types. This rock typing approach and correlations between electrical core data and well log data at cored depths can be used to predict initial water saturation at uncored depths. In fact, the findings of this study can help to improve the precision of the estimation of the hydrocarbon in place.