Forecasting Oil Response in Steam Injection Operations Combining Analytical and Empirical Tools
Authors: Vassilellis George D. , Prestridge Andrew L. 
Published: December 2007

Forecasting oil production in steam thermal operations is difficult using decline curve analysis techniques and often requires the use of analytical and numerical tools. The proposed method is a combination of analytical modeling with decline curve analysis and analogy. The analytical part of the proposed methodology is based on several published derivations that are often used in thermal evaluations. Some modifications are made to accommodate the effect of excessive water production. Analytical derivations are sought to approximate the magnitude and timing of peak oil rate in response to steam injection, making the application practical and adoptive. As the analytical models are often built on some simplifying assumptions considered typical for a given set of conditions, it is difficult for them to be globally applicable. By using the analytical models as extreme boundary conditions, an empirical oil production forecast is constructed that results in a desired combination of typical conditions. The reservoir conditions, petrophysical properties, and the injected steam quality greatly affect the resulting forecast. The accuracy of the method is dependent on matching closely the performance of a relatively mature thermal operation to an analogous early stage of continuous or cyclic steam injection. The presented field examples are in the San Joaquin Valley and Los Angeles Basin in California. The application is suited for evaluating continuous or cyclic steam injection projects, where thermal reservoir simulation is either not possible, or could benefit from an independent verification. The methodology is designed and can be used in a widely available spreadsheet application, making this implementation particularly practical and adaptive.

Introduction

The application of decline curve analysis, or any other empirical forecasting method is not possible in a case of inclining oil production and a subsequent constant oil rate period, typical of thermal operations. On the other hand, the analytical models that have been developed through the history of thermal EOR operations are effective in determining the final outcome of a thermal operation, but do not reliably predict the produced oil rate. In economic evaluations, this is a serious drawback as the Net Present Value (NPV) of a thermal operation cash flow, is strongly related to the initial oil production rates. This drawback is expected from the analytical models, as they are formulated around the thermodynamic properties of a steam process, rather than the rock quality and particularly the reservoir transmissibility that greatly influences the oil production rates. Therefore the forecasting of oil rates from a steam injection operation and the subsequent economic evaluation are usually based on thermal simulation or on analogy, whenever possible.

The proposed method is a combination of analytical modeling and empirical reasoning that is designed to make the most out of analytical models while improving their deficiencies by introducing in the calculations reservoir parameters like well spacing, oil viscosity as a function of temperature and well productivity. The method is empirical, designed to adopt to field data and to apply analogy in a rigorous manner.