3D Imaging of Geothermal Faults from a Vertical DAS Fiber at Brady Hot Spring, NV USA

Whitney Trainor-Guitton, Antoine Guitton, Samir Jreij, Hayden Powers and Bane Sullivan
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Whitney Trainor-Guitton: Department of Geophysics, Colorado School of Mines, Golden, CO 80401, USA
Antoine Guitton: DownUnder Geosolutions, Golden, CO 80401, USA
Samir Jreij: Cimarex, Tulsa, OK 74104, USA
Hayden Powers: Department of Geophysics, Colorado School of Mines, Golden, CO 80401, USA
Bane Sullivan: Department of Geophysics, Colorado School of Mines, Golden, CO 80401, USA

Energies, 2019, vol. 12, issue 7, 1-15

Abstract: In March 2016, arguably the most ambitious 4D (3D space + over time) active-source seismic survey for geothermal exploration in the U.S. was acquired at Brady Natural Laboratory, outside Fernley, Nevada. The four-week experiment included 191 vibroseis source locations, and approximately 130 m of distributed acoustic sensing (DAS) in a vertical well, located at the southern end of the survey area. The imaging of the geothermal faults is done with reverse time migration of the DAS data for both P-P and P-S events in order to generate 3D models of reflectivity, which can identify subsurface fault locations. Three scenarios of receiver data are explored to investigate the reliability of the reflectivity models obtained: (1) Migration of synthetic P-P and P-S DAS data, (2) migration of the observed field DAS data and (3) migration of pure random noise to better assess the validity of our results. The comparisons of the 3D reflectivity models from these three scenarios confirm that sections of three known faults at Brady produce reflected energy observed by the DAS. Two faults that are imaged are ~1 km away from the DAS well; one of these faults (middle west-dipping) is well-constructed for over 400 m along the fault’s strike, and 300 m in depth. These results confirm that the DAS data, together with an imaging engine such as reverse time migration, can be used to position important geothermal features such as faults.

Keywords: distributed acoustic sensing; depth migration; faults (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
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