Using Dark Fiber and Distributed Acoustic Sensing to Characterize a Geothermal System in the Imperial Valley, Southern California

Abstract

The Imperial Valley, CA, is a tectonically active transtensional basin located south of the Salton Sea; the area hosts numerous geothermal fields, including significant hidden hydrothermal resources without surface manifestations. Development of inexpensive, rugged, and highly sensitive exploration techniques for undiscovered geothermal systems is critical for accelerating geothermal power deployment as well as unlocking a low‐carbon energy future. We present a case study utilizing distributed acoustic sensing (DAS) and ambient noise interferometry for geothermal reservoir imaging, utilizing unlit fiber‐optic telecommunication infrastructure (dark fiber). The study exploits two days of passive DAS data acquired in early November 2020 over a ∼28‐km section of fiber from Calipatria, CA to Imperial, CA. We apply ambient noise interferometry to retrieve coherent signals from DAS records and develop a bin stacking technique to attenuate the effects from persistent localized noise sources and to enhance retrieval of coherent surface waves. As a result, we are able to obtain high‐resolution two‐dimensional (2D) S wave velocity (Vs) structure to 3 km depth, based on joint inversion of both the fundamental and higher overtones. We observe a previously unmapped high Vs and low Vp/Vs ratio feature beneath the Brawley geothermal system, which we interpret to be a zone of hydrothermal mineralization and lower porosity. This interpretation is consistent with a host of other measurements including surface heat flow, gravity anomalies, and available borehole wireline data. These results demonstrate the potential utility of DAS deployed on dark fiber for geothermal system exploration and characterization in the appropriate geological settings.

High‐Resolution Near‐Surface Imaging at the Basin Scale Using Dark Fiber and Distributed Acoustic Sensing: Toward Site Effect Estimation in Urban Environments

“…For more details regarding the DAS ambient noise data processing, we refer the reader to Cheng et al. (2023a).…”

“…See Figure S1 in Supporting Information S1 for the source and receiver configuration of all $${C}_{N}^{2}$$ inter‐station interferometric pairs, where $${C}_{N}^{2}=1+2+\text{\ldots }n-1$$ and n denotes the channel number of each subarray. This technique has recently been used to improve EGF coherence at lower frequencies (<3 Hz) for this data set (Cheng et al., 2023a). The cross‐coherence EGFs after temporal stacking (PWS) and spatial stacking (bin‐offset stacking) can be used for subsequently dispersion imaging.…”

“…Across the 28-km telecommunication cable, this process generated a total of 273 short subarrays where the enhanced VSG was analyzed for surface wave dispersion measurement. Cheng et al (2023a) utilized the same DAS data set to image the deeper geothermal reservoir by resampling the distributed strain-rate array into a series of longer subarrays (5 km) to extract the lower frequency surface waves. The versatility of this data set demonstrates the potential of using DAS for multi-scale and multi-purpose seismic imaging.…”

“…However, one demanding challenge for near‐surface seismic imaging is to reasonably extend the high‐resolution imaging techniques from small scale to large scale with limited budget and resources. Distributed acoustic sensing (DAS) repurposes fiber‐optic cables as dense arrays of seismic sensors, which is dramatically changing seismic acquisition, particularly in cases where dense array spacing is required (Cheng et al., 2023a; Daley et al., 2013; Jousset et al., 2022; Walter et al., 2020; Zhan, 2020). The distributed sensing property of DAS yields the unique advantage of satisfying demands of both high spatial‐resolution and large spatial‐coverage for near‐surface seismic imaging.…”

“…The distributed sensing property of DAS yields the unique advantage of satisfying demands of both high spatial‐resolution and large spatial‐coverage for near‐surface seismic imaging. Recently, DAS ambient noise interferometry has been implemented for seismic imaging in various environments and at various scales (Ajo‐Franklin et al., 2019; Cheng et al., 2023a; Dou et al., 2017; Fang et al., 2020; Spica et al., 2020b; Zhu et al., 2021).…”