Fiber-Optic Distributed Acoustic Sensing in Laboratory-Scale Hydraulic Fracture Experiments: Implications for Monitoring

Hydraulic fracturing is commonly used to enhance permeability in subsurface reservoirs, and microseismic monitoring plays a crucial role in assessing the geometry, orientation, and extent of induced fractures. Although extensively applied in field operations, the complexity of stimulation mechanisms remains inadequately understood. Laboratory-scale experiments offer a controlled environment to improve our understanding but often suffer from limited spatial resolution due to the use of sparse piezoelectric acoustic emission (AE) sensors (Warpinski, 2009). Distributed Acoustic Sensing (DAS) provides an alternative solution by transforming fiber-optic cables into dense continuous sensors, significantly improving both spatial and temporal resolution (Stanek et al., 2022). This study explores the use of DAS for high-resolution microseismic monitoring during hydraulic fracturing in a laboratory setup and evaluates its ability to detect and localize events in comparison to traditional AE sensors. A laboratory hydraulic fracturing experiment was conducted on a 40 cm × 40 cm × 40 cm limestone rock blocks characterized by a p-wave velocity of 5,282 m/s and a number of stylolites cutting at various angles across the block. We wrapped fiber optic cables around the block by embedding them into shallow grooves to prevent direct exposure to applied confining stresses. The center of the cube’s top face is penetrated by a 23 cm deep well 2.3 cm in diameter for injection of hydraulic fracturing fluid. As casing we cemented a stainless-steel tube into the well to a depth of 20 cm, leaving an open interval of 3 cm at the bottom for fluid injection and fracture initiation. The fiber-optic cables were carefully wrapped along each groove, ensuring continuous laser pulse propagation through elongated bends. The cables were calibrated over their entire length and separated into 18 distinct wraps that covered all the surfaces of the rock block. Prior to stimulation, a calibration ball drop experiment was conducted to verify sensor alignment and waveform timing. After this hydraulic fracturing fluid was injected through the well. For acoustic emission monitoring, we used both DAS and 8 AE transducers. DAS data were acquired at 125 kHz and AE data at 100 kHz. Signal preprocessing included detrending and bandpass filtering between 5 and 50 kHz. A Kirchhoff migration imaging technique was used to estimate event locations, with a zero-phase 20 kHz Ricker wavelet as the assumed source wavelet. Three hydraulically induced microseismic events were detected and validated by both DAS and AE systems. The dominant frequencies observed aligned with the expected spectral components, which were in the range of 20 to 45 kHz. Using Kirchhoff migration imaging, the hypocenter coordinates of the three events were estimated to be (28, 17, 13), (13, 19, 17), and (19, 28, 15) cm. The results show that DAS is a viable technology for lab-scale microseismic monitoring, with estimated event coordinates indicating possible activation of multiple fractures. Despite lower SNR, DAS effectively captured 3D acoustic information, demonstrating advantages over conventional AE sensors, particularly under confining stresses.