Development of a Stimulation Treatment Integrated Model

Abstract

Abstract Past publications have indicated that matrix treatment failures are in the order of 30%. To improve the success rate for matrix treatments, current work has been on real time field monitoring. These systems calculate the evolution of skin during matrix stimulations. However, these systems can only inform you how your treatment is performing. A need for a system that optimizes fluids prior to pumping is needed so that an engineer can take true advantage of monitoring acid treatments. This paper describes the development of an integrated matrix stimulation model for sandstone and carbonate formations that assists in determining formation damage, selection and optimization of fluid volumes, provides a pressure skin response of the acid treatment and forecasts the benefit of the treatment. The model includes three expert advisors for the novice engineer, a kinetic based multilayer reservoir model and a geochemical model to determine rock fluid compatability problems. Additional modules that provide support for the user are a scale predictor, critical drawdown, ball sealer forecaster and a fluid database for the selection of fluids and additives. A production forecast module is included to forecast the benefit of the stimulation. Introduction Formation damage can occur from natural or induced mechanisms that reduce the capability of flow between the formation and the near wellbore region, thus giving a rise to a positive skin. To mitigate this damage, matrix technology using reactive and non reactive fluids are pumped into the formation. StimCADE (Stimulation Treatment Integrated Model Computer Aided Design and Evaluation) was developed as an integrated software application used to identity, prevent and mitigate formation damage. The goal of StimCADE is to optimize stimulation treatments, recognize failures and maximize job success. Within ARCO, matrix stimulation treatments fail to improve productivity in one out of three treatments. A summary of these failures is shown in Table 1. The current practices for selecting wells for matrix stimulation are evaluating well production/injection histories, offset well performance and pressure transient analysis. Design techniques to improve the wells performance are based on 'rules of thumb' To improve ARCO's matrix treatments a real time monitoring system1 was developed based on Paccaloni and Provost work. This technique calculates a transient or "apparent" skin vs. time as shown in Fig. 1. The adaptation of this technique has improved the area of incorrect field procedures. Since then several authors have expanded on these ideas by calculating a derivative skin vs. time and using an inverse injectivity plot as diagnostic tools. To prevent the use of the wrong fluid, Expert systems were developed by ARCO and others. However, these tools were based on rules of thumb, providing no analytical solutions. Past experience indicates that knowledge systems are often discarded by the engineer after a few uses and have only found utility as teaching tools. To overcome this limitation, and to circumvent the loss of expertise within the industry, the expert systems provided within the new software are integrated to an analytical model. This paper examines how to optimize matrix treatments using an integrated design strategy. This software utilizes expert systems linked to analytical acidizing simulators along with several peripheral tools to achieve the optimized treatment. Approach StimCADE is an integrated program designed to allow the user to enter data, calculate and obtain results. P. 75