Probabilistic Assessment of Well Production Capacity in the Dieng Geothermal Field Using Monte Carlo Simulation and Jiwa Flow Modeling
DOI:
https://doi.org/10.30588/jo.v9i1.2144Abstract
The Dieng Geothermal Field, located in Central Java, Indonesia, is a high-temperature geothermal
system with two primary reservoirs: Sileri and Sikidang. This study aims to estimate the electricity
production capacity of the reservoir using a probabilistic approach and Monte Carlo simulation with Jiwa
Flow software. The methodology involves modeling well trajectory, casing data, and feed zone
characteristics, incorporating uncertainty in reservoir parameters to generate probability distribution
curves. The simulation results indicate that at 50% probability (P50), the estimated electricity capacity is
8.47 MWe, increasing to 11.66 MWe at 90% probability (P90), which is classified as proven reserves. At
99% probability (P99), the estimated capacity reaches 14.06 MWe, representing possible maximum
reserves. These findings suggest that the Dieng reservoir has significant geothermal energy potential,
predominantly characterized as a steam-dominated system, which is optimal for power generation. The
study highlights that electricity production can be enhanced through reservoir management optimization
and additional well drilling. The results provide a scientific basis for planning geothermal development,
particularly in the expansion of Dieng Unit-2. Future research should focus on improving the accuracy of
capacity estimations through real-time reservoir monitoring and extended field studies.
Keywords: Dieng Geothermal Field, Monte Carlo Simulation, Jiwa Flow, Probabilistic Analysis
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