Open AccessAn experimental and theoretical study to relate uncommon rock/fluid properties to oil recovery. Final report
Author(s) -
R.W. Watson
Publication year - 1995
Language(s) - English
Resource type - Reports
DOI - 10.2172/90388
Subject(s) - petroleum engineering , oil in place , residual oil , water saturation , permeability (electromagnetism) , geology , saturation (graph theory) , petroleum reservoir , porosity , relative permeability , enhanced oil recovery , core sample , wetting , residual , core (optical fiber) , mineralogy , geotechnical engineering , materials science , petroleum , mathematics , chemistry , paleontology , biochemistry , composite material , combinatorics , membrane , algorithm
Waterflooding is the most commonly used secondary oil recovery technique. One of the requirements for understanding waterflood performance is a good knowledge of the basic properties of the reservoir rocks. This study is aimed at correlating rock-pore characteristics to oil recovery from various reservoir rock types and incorporating these properties into empirical models for Predicting oil recovery. For that reason, this report deals with the analyses and interpretation of experimental data collected from core floods and correlated against measurements of absolute permeability, porosity. wettability index, mercury porosimetry properties and irreducible water saturation. The results of the radial-core the radial-core and linear-core flow investigations and the other associated experimental analyses are presented and incorporated into empirical models to improve the predictions of oil recovery resulting from waterflooding, for sandstone and limestone reservoirs. For the radial-core case, the standardized regression model selected, based on a subset of the variables, predicted oil recovery by waterflooding with a standard deviation of 7%. For the linear-core case, separate models are developed using common, uncommon and combination of both types of rock properties. It was observed that residual oil saturation and oil recovery are better predicted with the inclusion of both common and uncommon rock/fluid properties into the predictive models