PROCEEDINGS, The 8th Indonesia International Geothermal Convention & Exhibition (IIGCE)

Kerinci geothermal field is in Kerinci district, Jambi Province, Indonesia. It is a liquid-dominated reservoir, geothermal field, with temperature about 210°C to 60°C and characterized by fumarole as surface manifestation in the Kunyit Mountain area. This field is planned to develop 55 MWe to meet electrical needs in the southern part of Sumatra Island by Pertamina Geothermal Energy (PGE).This study area is part of the Great Sumatra Fault, which means it is a fault-controlled geothermal system. There are two main faults dominating the area, the Sikai and Dua Belas Fault. The lithological condition of the Kerinci region mostly consists of volcanic rocks. Based on JICA (1989), the deep reservoir fluid is neutral chloride water, and there is an overlying vapor-dominated zone. One of challenges with developing this field is the target area, which is located inside the Kerinci Seblat National Park, acknowledged by UNESCO as a World Heritage Site and protected by the government. As a result, the limited availability of field data needs to be optimized by using the latest technology to better understand the subsurface condition.

The objective of this study is to utilize available data in the Kerinci geothermal field, especially gravity data, to create 2.5D and 3D models of density by using integrated subsurface modeling software. These models can be used to update the reservoir condition and by combining them with other information, providing a better understanding of the geothermal system in the study area. Data used for this study are published gravity and elevation data from several station points in the Kerinci area as the main data. Additional information comes from available well data, geological map, lineament structure of remote sensing image, and other geophysics surveys and geochemical data. The workflow started by preparing and processing gravity data to get a complete Bouguer anomaly (CBA), loading data into an E&P software platform, performing quality control (QC) on the data, building 2.5D and 3D forward gravity models, and then validating the result by using available well data. Furthermore, an interpretation will be given based on the final models to be used for other subsurface modeling processes. Having a more accurate model, as the result of this study will better picture the subsurface condition and reservoir system in Kerinci Geothermal field. Which aid better decision making on field development to optimize production and minimize potential risk.