Rock Classification in Carbonate Reservoirs Based on Static and Dynamic Petrophysical Properties Estimated from Conventional Well Logs

Abstract

Abstract Rock typing in carbonate reservoirs is challenging due to high spatial heterogeneity and complex pore structure. In extreme cases, conventional rock typing methods such as Leverett's J-function, Winland's R35, and flow zone indicator are inadequate to capture the heterogeneity and complexity of carbonate petrofacies. Furthermore, these methods are based on core measurements, hence are not applicable to uncored reservoir zones. This paper introduces a new method for petrophysical rock classification in carbonate reservoirs that honors multiple well logs and emphasizes the signature of mud-filtrate invasion. The method classifies rocks based on both static and dynamic petrophysical properties. An inversion-based algorithm is implemented to simultaneously estimate mineralogy, porosity, and water saturation from well logs. We numerically simulate the process of mud-filtrate invasion in each rock type and quantify the corresponding effects on nuclear and resistivity measurements to derive invasion-induced well-log attributes, which are subsequently integrated into the rock classification. Under favorable conditions, the interpretation method advanced in this paper can distinguish bimodal from uni-modal behavior in saturation-dependent capillary pressure otherwise only possible with special core analysis. We successfully apply the new method to a mixed clastic-carbonate sequence in the Hugoton gas field, Kansas. Rock types derived with the new method are in good agreement with lithofacies described from core samples. The distribution of permeability and saturation estimated from well-log-derived rock types agrees with routine core measurements, with the corresponding uncertainty significantly reduced when compared to results obtained with conventional porosity-permeability correlations.