APPLICATION OF TIMES SERIES ANALYSIS IN FORECASTING FUTURE PERFORMANCE OF A RESERVOIR UNDER WATER INJECTION

• Main Author: Rachman, Alfian
• Format: Final Year Project
• Language: English
• Published: IRC 2015
• Subjects: T Technology (General)
• Online Access: http://utpedia.utp.edu.my/16843/1/Dissertation%20%5BR%5D.pdf; http://utpedia.utp.edu.my/16843/

Decline Curve Analysis (DCA) and History Matching (HM) are classical methods used in predicting reservoir performance. While both methods are widely used, they have certain limitations and strengths. DCA is only applicable for reservoir with primary drive and assumes that all mechanical conditions of a well remain constant. HM, on the other hand, is very complex, takes longer time, and require experience. Hence, a new simpler and faster technique is required. In this work, a technique called Time Series Analysis (TSA) is proposed for predicting the reservoir performance. Time series analysis is widely used in predicting future patterns in economics and weather forecasting, where factors influencing output are too many to consider. Other examples of the application of time series analysis are prediction of equipment prognostic and process of quality control. Two types of TSA were tested: Output-Error (OE) and Box-Jenkins (BJ). Eight models are developed by varying the order of each models. Two of the best models were chosen based on the resulting normalized root mean square error (NRMSE) and are compared with the conventional reservoir forecasting methods. The NRMSE from the selected models, OE (1-2-1) and BJ (1-2- 1-2-1), showed a comparable result with DCA and HM. The result of this study shows that, TSA has a very good potential for use in reservoir performance prediction under water injection and hence it can be utilized as alternative reservoir forecasting tool