Seismologist

Full-time 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. Responsibilities Surface and Borehole Geophone & Seismometer Networks Design, deploy, and maintain surface and borehole geophone and seismometer networks. Set network geometry and instrumentation to meet detection, location-accuracy, and completeness targets. Own instrument response, sensor orientation and calibration, timing, and continuous data QC. Run automated detection, phase picking, and event association across the network. Build and maintain 1D and 3D velocity models and station corrections. Manage field campaigns, vendor scopes, and data-delivery standards. Earthquake Location, Relocation, and Catalog Development Run HypoDD for double-difference relocation. Run GrowClust for relative relocation and hierarchical clustering. Generate waveform cross-correlation differential travel times and maintain automated relocation pipelines. Determine source parameters — magnitude, focal mechanism, moment tensor, and stress drop. Interpret relocated seismicity as fracture geometry, stimulated volume, and fault reactivation. Maintain a versioned production catalog with documented magnitudes, completeness, and uncertainty. Distributed Acoustic Sensing (DAS) — complementary observing system Incorporate DAS data from instrumented wells alongside the conventional network. Perform joint DAS and sensor processing where it improves the catalog. Interpret DAS response in a borehole setting, including its resolution limits. Induced Seismicity, Hazard, and Risk Track b-value and magnitude of completeness, and forecast seismicity rates and maximum magnitude. Develop real-time hazard algorithms using physics-based, statistical, and machine-learning methods. Maintain traffic light protocols and mitigation strategies with operations. Link observed seismicity to Thermo-Hydro-Mechanical-Chemical reservoir models. Represent Fervo with regulators, partners, and communities on induced-seismicity questions. Qualifications Required 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. 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. Solid grounding in surface and borehole seismic monitoring — network geometry and detectability, instrument response, sensor orientation and calibration, and earthquake detection, picking, and location. Knowledge of earthquake source analysis, including moment tensor inversion, focal mechanism determination, magnitude estimation, and stress drop estimation. Understanding of induced seismicity and seismic hazard concepts — magnitude of completeness, b-value, Gutenberg-Richter statistics, and ground-motion estimation. 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. Ability to build velocity models and to produce, quality-control, and defend earthquake catalogs that others rely on. Willingness to travel to field sites for network deployment, commissioning, and troubleshooting up to 20%. Preferred High Performance Computing and large-scale distributed processing of continuous seismic data. Machine learning applied to seismological problems, including deep-learning phase pickers. #J-18808-Ljbffr Stanford Climate Ventures