A novel approach in gas well performance monitoring and forecasting using modified decline curve analysis

Decline curve analysis is a widely used technique in evaluating well production performance and forecasting. One of the most commonly used decline curve modelling approaches is called Arp's model. This modelling approach has four fundamental assumptions. One of these assumptions is that the well is produced at constant bottomhole pressure (BHP). This assumption is usually approximated under real-production situation. Therefore, the objective of this study is to construct a novel mathematical workflow using modified decline curve models without violating constant pressure assumption, and use the production forecast to identify potential issues in the wellbore. In this data analytic process, using a large field data sets, the linear regression technique was implemented to convert variable pressure values into an equivalent constant pressure value. Consequently, this equivalent constant pressure was used to derive new gas rates using the back pressure equation. The new gas rates were used as input parameters in the new production performance as well as forecasting algorithm. Using MATLAB's toolbox, a large set of field gas production data were analysed, and the results showed very good agreement with insignificant margin of deviation. In addition, the new model prediction when compared with the actual production data enabled the user to detect events such as liquid loading (hydrocarbon) or water dropout phenomena. Consequently, the new algorithm was used to forecast the future production behaviour. A novel decline curve modelling algorithm without constant bottomhole pressure approximation is presented in this paper. In addition, the new algorithm also presents a tool for the reservoir engineers to identify events in the wellbore such as well loading with dropped out condensate or accumulation of conning water to create blockage of gas production.