EOR preliminary analysis is pivotal to be performed at early stage of assessment in order to elucidate EOR feasibility. This study proposes an in-depth analysis toolkit for EOR preliminary evaluation. The toolkit incorporates EOR screening, predictive, economic, risk analysis and optimisation modules. The screening module introduces algorithms which assimilates statistical and engineering notions into consideration. The United States Department of Energy (U.S. DOE) predictive models were implemented in the predictive module. The economic module is available to assess project attractiveness, while Monte Carlo Simulation is applied to quantify risk and uncertainty of the evaluated project. Optimization scenario of EOR practice can be evaluated using the optimisation module, in which stochastic methods of Genetic Algorithms (GA), Particle Swarm Optimization (PSO) and Evolutionary Strategy (ES) were applied in the algorithms. The modules were combined into an integrated package of EOR preliminary assessment. Finally, we utilised the toolkit to evaluate several Indonesian oil fields for EOR evaluation (past projects) and feasibility (future projects). The attempt was able to update the previous consideration regarding EOR attractiveness and open new opportunity for EOR implementation in Indonesia.
|Original language||English (US)|
|Title of host publication||SPE/IATMI Asia Pacific Oil & Gas Conference and Exhibition|
|Publisher||Society of Petroleum Engineers (SPE)|
|State||Published - Oct 17 2017|
Bibliographical noteKAUST Repository Item: Exported on 2020-10-01
Acknowledgements: The financial supports from Pertamina Upstream Technology Center (UTC) is appreciated. Help from Mr. Dede Alam Setiadi for the code development is highly acknowledged. Authors would also thank all former research assistants in this project. This research was carried out while A.D. Hartono and F. Hakiki were still at Institut Teknologi Bandung, Indonesia. All tested data is from published works and no confidentiality issues.