Oil Well Performance Forecasting Using Decline Curve Analysis: Tharjiath Oil Field, South Sudan

Abstract

This study applied Decline Curve Analysis (DCA) to forecast the performance and reserves of oil wells in the Tharjiath Oil Field, located in South Sudan's Muglad Basin. Historical production data from five wells were analyzed to compare exponential, hyperbolic, and harmonic decline models. The exponential model was found to be the most accurate, as it closely matched observed production trends by assuming a constant percentage decrease, aligning well with the initial production behaviour in the Tharjiath Oil Field.  To further validate the findings, Oil Field Manager (OFM) software was used to simulate future production trends based on the exponential model. This robust platform enabled comprehensive analysis and visualization of reservoir performance, confirming the effectiveness of DCA in predicting well performance and reserves and reinforcing the exponential model as the best representation of the reservoir's natural depletion. The findings underscored the necessity of refining forecasts through sensitivity analysis, which involved varying key input parameters such as initial production rates, decline rates, and reservoir pressure. This systematic alteration of variables allowed the study to identify a range of potential outcomes and assess the associated uncertainties in production predictions. Additionally, the study emphasized the benefits of integrating DCA with real-time production monitoring and reservoir simulation models to enhance forecast accuracy. The study also recommended further exploration of Enhanced Oil Recovery (EOR) techniques, including water flooding and gas injection, to optimize recovery and extend the economic life of the field. Some recommendations were made to expand DCA applications to all wells in the field, incorporate real-time data into the forecasting process, and address the economic and policy implications for sustainable reservoir management