Low Frequencies of Distributed Dynamic Strain Sensing enable unprecedented profiling of deep geothermal fluid production and injection

Geothermal productivity strongly depends on reservoir performance, which is regularly monitored. This work presents the results from Distributed Dynamic Strain Sensing (DDSS or DAS) measurements during the restart of injection and production in deep geothermal wells. This technology's high spatiotemporal resolution enables monitoring relative strain and temperature changes along the entire sensing cable. We monitored 3.7 km of a producer and approximately 4.1 km of an injector. Both cables were installed post-borehole completion and reached up to 1 km into the reservoir. Distributed sensing was achieved using a commercial DDSS acquisition system sampling the boreholes at 1 m spatial interval and 2000 Hz.

Here, we focus on the low-frequency subsurface dynamics captured during the restart phase. We extracted the low-frequency content (<0.1 Hz) by applying a cascading Finite Impulse Response (FIR) filter and a large decimation factor. As fiber optic strain measurements are sensitive to strain and temperature changes along the fiber optic cable, the low-frequency signal is influenced by subtle temperature changes induced by fluid motion.

The results provide unprecedented accuracy in determining deep geothermal inflow zones because we can detect flow velocities magnitudes lower than conventional flow meter measurements. Further, the activation time of the inflow from different depths can be distinguished. Fluid-flow velocity, strain, and their respective temporal derivatives can be used as a proxy for the heat contribution of different depths and the associated inflow zones.

These findings are part of the GFK-Monitor project (https://gfk-monitor.de/en/), demonstrating the ability of DDSS to detect and interpret complex reservoir processes in deep geothermal systems. This research advances downhole monitoring technologies, offers an improved understanding of subsurface processes, and informs strategies to optimize geothermal energy production.