| Title | Application of numerical simulation method with experimental design in the Sibayak geothermal field, Indonesia |
|---|---|
| Authors | E. Firanda, M.P. Canilandi, P. Hastuti |
| Year | 2025 |
| Conference | New Zealand Geothermal Workshop |
| Keywords | Numerical simulation, experimental design, Sibayak field |
| Abstract | This paper presents a comprehensive method for estimating geothermal field resources through numerical simulation, demonstrated through a case study of the Sibayak field. However, due to limited available data and the need to reduce subjectivity, significant uncertainties remain that must be addressed. To manage these uncertainties, an experimental design approach is employed. The primary objective of applying experimental design in geothermal simulation is to systematically assess the impact of uncertain reservoir parameters such as liquid saturation, permeability, porosity, and fracture properties on model outputs that influence pressure, enthalpy, and production sustainability. By generating a structured set of simulation scenarios, this approach helps identify the key parameters that have the greatest effect on field performance and quantifies the probability of achieving long-term production targets. The simulation process begins with data preparation, model construction, and the conversion of the static Sibayak model. This is followed by natural state simulation and calibration using available production history data from wells such as SBY-3, SBY-5, SBY-6, and SBY-8. Once a satisfactory history match is achieved, the model is used to forecast future production. The experimental design method is then applied to evaluate the probability of the Sibayak field sustaining production throughout the contract period. The integration of numerical simulation and experimental design offers a structured and quantitative framework for addressing subsurface uncertainties. This combined approach improves confidence in decision making by providing a more realistic estimate of the field’s long-term production potential. |