| Abstract |
The sustainability of geothermal reservoirs is essential for ensuring long-term renewable energy production. However, various operational challenges such as pressure declines, fluid depletion, scaling, and induced seismicity, threaten reservoir efficiency. Root Cause Analysis (RCA) serves as a critical diagnostic tool for identifying, mitigating, and preventing these issues, thereby enhancing the efficiency of geothermal energy systems. This paper explores RCA methodologies and their application in geothermal reservoir monitoring, focusing on their role in identifying key operational inefficiencies. By leveraging techniques such as Fishbone Diagram, 5 Whys, Fault Tree Analysis, Pareto Analysis, and Failure Mode and Effects Analysis (FMEA), RCA helps optimize energy extraction, reinjection strategies, and system sustainability. A case study from the Olkaria geothermal field highlights RCA’s effectiveness in diagnosing and addressing silica scaling issues, a major operational challenge. Well OW-34 experienced a rapid production decline due to massive silica deposition, ultimately leading to its shutdown. RCA was crucial in understanding the cause of silica scaling, preventing future well failures, improving geothermal field management, and optimizing remediation strategies. Furthermore, as geothermal energy expands globally, the integration of RCA with digital technologies, including artificial intelligence, real-time data analytics, and IoT-based monitoring, will enhance predictive maintenance and improve reservoir management. By applying RCA-driven insights, geothermal operators can significantly reduce operational risks, improve economic viability, and ensure long-term energy sustainability. |