Monitoring the gravel packing process during completion of a geothermal well using distributed fiber optic sensing

An efficient, safe, and sustainable geothermal energy supply depends on reliable well completion and monitoring technologies. Gravel packing is a process in well construction where the space between the filter screen and the formation is filled with gravel. This process can be crucial for producing sand-free fluid with minimal head loss. However, conventional wireline monitoring methods, such as manual bathometers or density logs, provide only discrete or post-placement information, leaving real-time downhole processes unobserved. This lack of continuous feedback creates operational uncertainties and leads to suboptimal decisions that can threaten well construction and reduce the well's efficiency.Here, the gravel packing of a 450-meter-deep exploration well designed for High-Temperature Aquifer Thermal Energy Storage (HT-ATES) in Berlin, Germany, was investigated using a fiber-optic sensing cable attached to the production casing. The study first evaluates the feasibility of simultaneous Distributed Temperature Sensing (DTS) and Distributed Dynamic Strain Sensing (DDSS, also known as Distributed Acoustic Sensing, DAS) for real-time gravel pack monitoring. Building on this, a combined interpretation of temperature cooling fronts, pump-induced wavefield reflections, vibrational energy anomalies, and low-frequency strain transients is used to identify the thermal and acoustic signatures of operational downhole processes such as fluid circulation and gravel pack placement, as well as of operational hazards such as caving, gravel bridging and collapse, screen clogging, and artesian fluid inflow. In situ observation of these theoretical concepts demonstrates the value of continuous fiber-optic measurements for improved understanding of downhole processes during well completion. The lightweight processing required to retrieve these data products makes the workflow suitable for edge deployment, enabling timely feedback to support proactive interventions that minimize operational risks and enhance well efficiency.