| Abstract |
Understanding and optimizing geothermal well performance is essential for sustainable and efficient reservoir utilization. Building on previous work done on stock reservoir modeling (SRM), this study presents an expanded methodology that aims to incorporate interconnected geothermal wells to further enhance production planning for geothermal systems. SRM offers a fast, data-driven approach that requires only historical production data to estimate individual well behavior, without requiring physical reservoir characterization. It has proved effective for wells with reduced interactions; however, for most geothermal fields, well-to-well interactions are frequent, which makes understanding these interactions important when optimizing the production of geothermal fields. This research proposes an expanded SRM methodology that further studies subsurface interactions between wells based on production trends and pressure responses by including data from pressure monitoring of a field. The main objective is to identify the dependencies between wells and provide insight into whether or not considering their interconnectivity would improve the model and the optimization process. By improving SRM’s interaction analysis, the approach aims to improve short- and mid-term forecasting accuracy for geothermal fields. This contributes to making geothermal production models more flexible and robust, especially in fields where operational data is available but detailed subsurface models are not as accessible. |