Description:
Fervo Energy is bringing next-generation geothermal power to commercial scale — 24/7 carbon-free energy that firms the grid rather than relying on it. By applying horizontal drilling, multi-stage stimulation, and fiber-optic subsurface sensing to Enhanced Geothermal Systems (EGS), Fervo has moved geothermal from a resource-constrained niche to a scalable, dispatchable source of clean power.
Fervo is seeking a Seismologist to lead the design, deployment, and processing of surface and borehole seismic monitoring networks across our EGS development portfolio. You will own our arrays of three-component geophones and broadband seismometers — sited at the surface, in shallow vaults and boreholes, and downhole in monitoring wells — from network geometry and instrumentation through calibration, data quality, and continuous processing.
The central deliverable of this role is a high-precision, defensible earthquake catalog. Proficiency with HypoDD and GrowClust is required, and you will build, relocate, quality-control, and defend the catalogs that feed fracture-network characterization, reservoir models, induced-seismicity mitigation protocols, and regulatory and community engagement.
Fervo also operates fiber-optic Distributed Acoustic Sensing (DAS) in a number of wells, and you will incorporate DAS alongside the conventional sensor network as a complementary observing system. Familiarity with DAS is valuable, but it is not the focus of the role and is not required at hire — the conventional network and the relocated catalog come first.
Requirements:
Responsibilities
Surface and Borehole Geophone & Seismometer Networks
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Design, deploy, and maintain surface and borehole geophone and seismometer networks.
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Set network geometry and instrumentation to meet detection, location-accuracy, and completeness targets.
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Own instrument response, sensor orientation and calibration, timing, and continuous data QC.
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Run automated detection, phase picking, and event association across the network.
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Build and maintain 1D and 3D velocity models and station corrections.
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Manage field campaigns, vendor scopes, and data-delivery standards.
Earthquake Location, Relocation, and Catalog Development
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Run HypoDD for double-difference relocation.
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Run GrowClust for relative relocation and hierarchical clustering.
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Generate waveform cross-correlation differential travel times and maintain automated relocation pipelines.
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Determine source parameters — magnitude, focal mechanism, moment tensor, and stress drop.
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Interpret relocated seismicity as fracture geometry, stimulated volume, and fault reactivation.
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Maintain a versioned production catalog with documented magnitudes, completeness, and uncertainty.
Distributed Acoustic Sensing (DAS) — complementary observing system
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Incorporate DAS data from instrumented wells alongside the conventional network.
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Perform joint DAS and sensor processing where it improves the catalog.
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Interpret DAS response in a borehole setting, including its resolution limits.
Induced Seismicity, Hazard, and Risk
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Track b-value and magnitude of completeness, and forecast seismicity rates and maximum magnitude.
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Develop real-time hazard algorithms using physics-based, statistical, and machine-learning methods.
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Maintain traffic light protocols and mitigation strategies with operations.
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Link observed seismicity to Thermo-Hydro-Mechanical-Chemical reservoir models.
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Represent Fervo with regulators, partners, and communities on induced-seismicity questions.
Qualifications
Required
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Ph.D. in Geophysics, Seismology, Applied Mathematics, or a closely related field. No minimum years of industry or post-doctoral experience are required — recent and upcoming graduates are encouraged to apply.
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Working proficiency with HypoDD and GrowClust, including generation of waveform cross-correlation differential travel times, parameter selection, and assessment of relocation uncertainty. This may have been developed through thesis work, post-doctoral research, or industry practice.
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Solid grounding in surface and borehole seismic monitoring — network geometry and detectability, instrument response, sensor orientation and calibration, and earthquake detection, picking, and location.
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Knowledge of earthquake source analysis, including moment tensor inversion, focal mechanism determination, magnitude estimation, and stress drop estimation.
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Understanding of induced seismicity and seismic hazard concepts — magnitude of completeness, b-value, Gutenberg-Richter statistics, and ground-motion estimation.
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Python proficiency for seismic data processing (ObsPy, NumPy/SciPy, pandas, or equivalent tooling) and comfort working in Linux environments with shell scripting and version control.
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Ability to build velocity models and to produce, quality-control, and defend earthquake catalogs that others rely on.
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Willingness to travel to field sites for network deployment, commissioning, and troubleshooting up to 20%.
Preferred
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High Performance Computing and large-scale distributed processing of continuous seismic data.
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Machine learning applied to seismological problems, including deep-learning phase pickers.