Improving Oil-Rate Estimate in Capacitance/Resistance Modeling Using the Y-Function Method for Reservoirs Under Waterflood

Abstract

Summary Capacitance/resistance modeling (CRM) is an empirical waterflood modeling technique based on the signal correlations between injection rates and gross production rates. CRM can satisfactorily estimate the gross (liquid) production rate. The oil-production-rate forecast is based on fitting the empirical oil fractional-flow model, the Leverett (1941) oil fractional-flow model, or the Koval (1963) model to the historical production data. We observed that the oil-production-rate forecast in this approach is less satisfactory. We propose a robust approach that combines CRM gross production prediction with a Buckley-Leverett displacement-theory-based waterflood analytical method—the Y-function method—to calculate the oil fraction flow and to improve the oil prediction capability. The analytical method is based on the results of the historical production performance of either an individual producer or a group of producers in a given area. By using this method, a better understanding can be developed about the production performance, such as the breakthrough time of injected water and possible operational issues, such as water channeling. The analytical model compares oil fractional flow and the cumulative gross production on the producers, yet the value of saturation is not required. As a result, the forecast of the oil-production rate becomes more convenient and straightforward. Sayarpour et al. (2009a) outlined field examples to compare the estimated oil production obtained using the current empirical oil fractional flow-model approach and the analytical Y-function method. The new method provided another effective way to calculate the oil rate in CRM. The results indicated that the new approach improved the accuracy of the oil-rate calculation and proved convenient in field applications. The objective of this study was not to regenerate the gross-rate forecast of CRM, but rather to improve the oil fractional-flow description and oil-production-rate forecast from the gross rate using the Y-function method.