Distributed acoustic sensing as a tool for subsurface mapping and seismic event monitoring: a proof of concept

Abstract

Abstract. We use PoroTomo experimental data to compare the performance of distributed acoustic sensing (DAS) and geophone observations in retrieving data to execute standard subsurface mapping and seismic monitoring activities. The PoroTomo experiment consists of two “seismic systems”: (a) a 8.6 km long optical fibre cable deployed across the Brady geothermal field and covering an area of 1.5 × 0.5 km with 100 m long segments and (b) a co-located array of 238 geophones with an average spacing of 60 m. The PoroTomo experiment recorded continuous seismic data between 10 and 25 March 2016. During this period, a Ml 4.3 regional event occurred in the southeast, about 150 km away from the geothermal field, together with several microseismic local events related to the geothermal activity. The seismic waves generated from such seismic events have been used as input data in this study to tackle similarities and differences between DAS and geophone recordings of such wavefronts. To assess the quality of data for subsurface mapping tasks, we measure the propagation of the P wave generated by the regional event across the geothermal field in both seismic systems in term of relative time delays, for a number of configurations and segments. Additionally, we analyse and compare the amplitude and the signal-to-noise ratio (SNR) of the P wave in the two systems at high resolution. For testing the potential of DAS data in seismic event locations, we first perform an analysis of the geophone data to retrieve a reference location of a microseismic event, based on expert opinion. Then, we a adopt different workflow for the automatic location of the same microseismic event using DAS data. To assess the quality of the data for tasks related to monitoring distant events, we retrieve both the propagation direction and apparent velocity of the wave field generated by the Ml 4.3 regional event, using a standard plane-wave-fitting approach applied to DAS data. Our results indicate that (1) at a local scale, the seismic P-wave propagation (i.e. time delays) and their characteristics (i.e. SNR and amplitude) along a single cable segment are robustly consistent with recordings from co-located geophones (delay times δt∼0.3 over 400 m for both seismic systems); (2) the DAS and nodal arrays are in mutual agreement when it comes to site amplifications, but it is not immediately clear which geological features are responsible for these amplifications. DAS could therefore hold potential for detailed mapping of shallow subsurface heterogeneities, but with the currently available information of the Brady Hot Springs subsurface geology, this potential cannot be quantitatively verified; (3) the interpretation of seismic wave propagation across multiple separated segments is less clear due to the heavy contamination of scattering sources and local velocity heterogeneities; nonetheless, results from the plane-wave-fitting approach still indicate the possibility for a consistent detection and location of the distant event; (4) automatic monitoring of microseismicity can be performed with DAS recordings with results comparable to manual analysis of geophone recordings in the case of events within or close to the DAS system (i.e. maximum horizontal error on event location around 70 m for both geophone and DAS data); and (5) DAS data preconditioning (e.g. temporal subsampling and channel stacking) and dedicated processing techniques are strictly necessary for making seismic monitoring procedures feasible and trustable.

Microseismicity Monitoring and Site Characterization With Distributed Acoustic Sensing (DAS): The Case of the Irpinia Fault System (Southern Italy)

“…Similar findings have been retrieved for off‐shore fibers installed in shallow submarine sedimentary layers, where records are dominated by Sholte waves (Sladen et al., 2019). For other surveys, where the ray does not impinge vertically below the surface, the P wave can be clearly recognized and in some cases, the SNR for the P wave on the DAS overcomes the value measured on colocated geophones (Piana Agostinetti et al., 2022; Wang et al., 2018).…”

Sensing Optical Fibers for Earthquake Source Characterization Using Raw DAS Records

“…Also, the availability of existing telecom dark fibers allows to investigate environments usually difficult to monitor, such as oceanic seafloors, volcanic flanks, and geothermal areas, over distances between a few and hundreds of kilometers (e.g., Currenti et al., 2021; Sladen et al., 2019; Tsuji et al., 2021). In the recent years, DAS technology has been successfully applied to seismology for earthquake location (Nishimura et al., 2021; Piana Agostinetti et al., 2022; Sladen et al., 2019), focal mechanism determination (Li et al., 2023), seismic velocity estimation (Lellouch et al., 2019) and site effect characterization (Ajo‐Franklin et al., 2019; Spica et al., 2020).…”

Sensing optical fibers for earthquake source characterization using raw DAS records

“…Also, the availability of existing telecom dark fibers allows to investigate environments usually difficult to monitor, such as oceanic seafloors, volcanic flanks, and geothermal areas, over distances between a few and hundreds of kilometers (e.g., Currenti et al, 2021;Sladen et al, 2019;Tsuji et al, 2021). In the recent years, DAS technology has been successfully applied to seismology for earthquake location (Nishimura et al, 2021;Piana Agostinetti et al, 2022;Sladen et al, 2019), focal mechanism determination (Li et al, 2023), seismic velocity estimation (Lellouch et al, 2019) and site effect characterization (Ajo-Franklin et al, 2019;Spica et al, 2020).…”