A Novel Technique for Generation of Accurate Capillary Pressure Pc Curves from Conventional Logs and Routine Core Data and New Pc Endpoint Functions after Considering the Sedimentary Environment and Pore Throat Size Distribution Shape PTSDS

Abstract

Abstract This paper presents an innovative method for derivation of Pc curves from log saturations, introduces better relations for end points of Pc curves and a better model for Pc curves. The influence of sedimentary and diagenesis environment on PTSDS and the effect of PTSDS on Pc curves are discussed and considered. This paper presents distinctive Pc models for diverse geologic zones. Examples demonstrate the improved accuracy using the proposed procedures. This paper also discusses the classification of reservoir rock based on a distinct and specific linear relationship that exists between Flow Zone Index (FZI) and 1/ (Swir.φ) in a geological zone. This classification separates zones that have similar geology or PTSDS. Functions for entry pressure (Pe) and irreducible water saturation (Swir) in each class are found and a Pc curve model is constructed for each class. In the absence of good SCAL data, Pc models are generated from log saturations and routine core analysis data. Pc models provide Pc curves for all saturation regions in the reservoir model. Reservoir rock classification is crucial for Pc curve generation. End points of Pc curves that are Pe and Swir depend both on PTSDS and other rock properties such as permeability (k), Flow Zone Index (FZI), Hydraulic Units (HUs), or reservoir quality index (RQI). In addition, PTSDS influences the shape of Pc curves. This research investigated correlations of Swir with k, FZI, HUs, and RQI and determined a) that these correlations are improved after classification and b) that, by inference, the strongest correlations exist when Swir is correlated to RQI and next to k. However, inferior correlations exist when Swir is correlated to FZI and HUs. Pe is also best related to RQI. Pc curves and reservoir saturations are markedly improved when the proposed classification is completed, end points are correlated to RQI, and the proposed model is used. Finally, very accurate Pc curves can be derived from log saturations when routine core data are available in a key well. The Pc model based on routine core data and log replicates log saturations in all wells perfectly. This method can eliminate the need for Pc curve measurement in the lab or reduce the number of required measurements. Rock classification before Pc generation is necessary and crucial but is often ignored. The use of novel functions for end points of Pc curves and the proposed model for Pc curves results in a marked improvement in the accuracy of Pc curves. A novel technique that generates very accurate Pc curves from log saturations is introduced. This method can eliminate the need for and the cost of Pc measurement in the lab or reduce the costs. The result is greatly more accurate saturation modeling of the reservoir at lower cost.