Open AccessResponse Surface Method Using Box-Behnken Design for Probabilistic Resource Assessment: A Case Study in Atadei Geothermal Field, Indonesia
Author(s) -
Marchel Christian Supijo,
Heru Berian Pratama,
Sutopo Sutopo
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/417/1/012022
Subject(s) - response surface methodology , probabilistic logic , geothermal gradient , box–behnken design , monte carlo method , environmental science , computer science , process engineering , mathematics , engineering , statistics , geology , machine learning , artificial intelligence , geophysics
Resource assessment in geothermal green-fields will most likely encounter some difficulties due to the limited initial data and directly impact the accuracy of the estimated resources. Proper electricity potential based on resource assessment affects the development scenario in order to determine optimum capacity to be installed. Therefore, this paper applied the response surface method approach using three-level Box-Behnken Design (BBD) to the TOUGH2 numerical model of Atadei geothermal green-field to generate probabilistic resource assessment results. This study aimed to perform the Response Surface Method (RSM) using Box-Behnken design for probabilistic resource assessment in Atadei geothermal green-field. A Box-Behnken design was used to build 27 experiments and investigated four parameters (permeability, porosity, liquid saturation, and feed zone location) at three levels (minimum, most likely, and maximum). The results from multiple model runs were used to create a polynomial function (proxy equation) and then applied to Monte Carlo simulation to generate a probabilistic distribution of the potential power output. This method had been successfully estimated a more robust electricity potential covering the entire range of possible values of important reservoir parameters. The probabilistic electricity potential using Monte Carlo based on Response Surface Method for 30 years production for P10, P50, and P90 are 11.7 MW, 18.2 MW, and 25.6 MW respectively.