Using Distributed Acoustic Sensing and Dark Fiber for Basin Scale Geothermal System Characterization: The Imperial Valley Dark Fiber Project

Distributed Acoustic Sensing (DAS) is a recently developed method which utilizes short pulses of laser light to measure strain at thousands of locations along an optical fiber, effectively transforming fiber optic cables into massively distributed arrays of seismometers. We are exploring the use of DAS recorded on unused sections of the telecommunication network, referred to as dark fiber, as a tool for basin scale geothermal characterization and monitoring. Such large array-based seismic measurements can be used for detection of natural seismicity associated with tectonically active faults as well as an imaging tool through recording of the ambient seismic noise wavefield. Inversion of DAS ambient noise measurements, because of their dense spatial sampling and extent (20 km+), can be used to generate detailed profiles of shear wave velocity as well as scattering information which may assist in early exploration phases. The same dark fibers can be used for measurement of near-surface temperature using a related sensing technique (DTS) if surface thermal profiles are valuable. We are currently conducting a proof-of-concept evaluation of DAS & DTS in this capacity in the Imperial Valley, CA. Our target is imaging seismicity and velocity structures related to the Brawley Seismic Zone (BSZ) and the Imperial Valley Fault, two features associated with existing produced (Brawley) and potential geothermal resources. We will present early results from this project including (a) evaluation of DAS for ambient noise-based fault imaging and seismic event detection using data from analog profiles, (b) the design and layout of the experiment including the fiber profile, sensing hardware, and geological framework, and (c) preliminary evaluation of our array, which runs from Calipatria, CA to near Imperial, CA. The DAS study will also be augmented by planned nodal and broadband deployments; in this context, we are exploring ambient noise imaging combining DAS with point sensors.