Perpustakaan Digital ITB

Predicting production performance and well life are essential to the oil business as they directly relate to oil companies' financial aspects. Decline curve analysis (DCA) is one of the most widely used methods for predicting production performance as well as reserve estimation. However, the result of DCA is very subjective to the observing engineers. Arps’ decline model is one of the empirical solutions that is often used to analyze the decline in production due to its simplicity. To increase the production rate, the installation of artificial lifts can be one of the solutions, but it will lead to changed operating conditions that contradict the conditions for using Arps’ decline model. In practice, even after a change in operating condition, the new decline rate will be considered the same as decline rate before the condition changes. This study has a purpose to see how the installation of artificial lift will affect well production decline and estimated ultimate recovery (EUR). To imitate the condition of the installation artificial lift, bottom hole pressure will decrease in the middle of the production period. The proposed method is also expected to be able to estimate the life of the well. The method starts with screening data followed by curve fitting that justified using the least-square concept. Curve-fitting is carried out on known production data to extract decline curve parameters which will later be used as limits and objectives at the prediction stage. The proposed method is tested on two types of data, real field data, and data generated from simulations. Predicted production rate calculated using this method successfully fits actual data with errors below 10% for both data types.