6th ITB International Geothermal Workshop | |
Probabilistic approach of resource assessment in Kerinci geothermal field using numerical simulation coupling with monte carlo simulation | |
Hidayat, Iki^1 ; Sutopo^1,2 ; Pratama, Heru Berian^2 | |
Study Program of Petroleum Engineering, Faculty of Mining and Petroleum Engineering, Bandung Institute of Technology, Indonesia^1 | |
Study Program of Geothermal Engineering, Faculty of Mining and Petroleum Engineering, Bandung Institute of Technology, Jl. Ganeca No. 10, West java Bandung | |
40132, Indonesia^2 | |
关键词: Conceptual model; National parks; Pressure and temperature profiles; Probabilistic approaches; Reservoir characterization; Resource assessments; Simulation data; State simulation; | |
Others : https://iopscience.iop.org/article/10.1088/1755-1315/103/1/012007/pdf DOI : 10.1088/1755-1315/103/1/012007 |
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来源: IOP | |
【 摘 要 】
The Kerinci geothermal field is one phase liquid reservoir system in the Kerinci District, western part of Jambi Province. In this field, there are geothermal prospects that identified by the heat source up flow inside a National Park area. Kerinci field was planned to develop 1×55 MWe by Pertamina Geothermal Energy. To define reservoir characterization, the numerical simulation of Kerinci field is developed by using TOUGH2 software with information from conceptual model. The pressure and temperature profile well data of KRC-B1 are validated with simulation data to reach natural state condition. The result of the validation is suitable matching. Based on natural state simulation, the resource assessment of Kerinci geothermal field is estimated by using Monte Carlo simulation with the result P10-P50-P90 are 49.4 MW, 64.3 MW and 82.4 MW respectively. This paper is the first study of resource assessment that has been estimated successfully in Kerinci Geothermal Field using numerical simulation coupling with Monte carlo simulation.
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Probabilistic approach of resource assessment in Kerinci geothermal field using numerical simulation coupling with monte carlo simulation | 729KB | download |