Reservoir Engineer, Modeling

About Fervo Energy
Fervo Energy (NASDAQ: FRVO) is a modern power company developing next-generation geothermal resources to meet the growing demand for affordable, reliable, 24/7 carbon-free energy. Our mission is to transform geothermal into America’s most dependable and affordable source of clean, around-the-clock power. By combining innovations in horizontal drilling, fiber-optic sensing, and advanced reservoir engineering, Fervo has developed a repeatable approach to building utility-scale enhanced geothermal systems. Our flagship Cape Station development in Utah is planned to deliver 500 MW of firm, carbon-free power, and we are advancing a development pipeline of more than 50 GW. Join us and work alongside world-class engineers, geoscientists, operators, project builders, and business leaders working to make geothermal a cornerstone of a more reliable, affordable, and sustainable energy future.
Position Description
Joining Fervo as a Reservoir Engineer focused on reservoir modeling and history matching means owning the calibration of our subsurface models against real field performance — both the stimulation fracture growth created during completions and the production and pressure response of the reservoir over time. This role also defines and drives the testing and data acquisition programs needed to close calibration gaps and continuously improve history-matching accuracy. The position is ideal for an engineer who enjoys rigorous model-to-data reconciliation, diagnosing the sources of mismatch, and designing the next test that resolves it.
The Reservoir Engineer will build, calibrate, and maintain reservoir and fracture models, with a strong focus on history matching both stimulation-induced fracture growth and reservoir production/pressure behavior. This role emphasizes quantitative rigor, root-cause diagnosis of model mismatch, and the design of targeted diagnostic testing to improve match quality over time.
The position collaborates closely with Completions, D&C, Reservoir, and Data Science teams to align stimulation design, field data acquisition, and simulation workflows so that models stay predictive as the asset base grows.
Responsibilities
Stimulation & Fracture Growth History Matching
Build and calibrate hydraulic fracture growth models (e.g., ResFrac or comparable geomechanical/fracture simulators) against observed stimulation data.
History-match fracture height, length, and complexity using treatment pressure, microseismic, DAS/DTS, and tracer data.
Characterize in-situ stress state and natural fracture (NF) interactions using fracture mechanics principles to guide fracture growth and stress-shadow modeling.
Account for fracturing-fluid rheology in fracture models, including its influence on fracture width, height growth, and proppant transport.
Incorporate completion design parameters (stage spacing, cluster design, pump schedule, fluid/proppant systems) into fracture growth models and iterate as new stimulation data arrives.
Translate calibrated fracture models into simulation-ready fracture network representations for downstream reservoir modeling.
Quantify uncertainty in fracture geometry and connectivity and communicate its impact on well and pad performance predictions.
Reservoir Production & Pressure History Matching
Build and maintain reservoir simulation models (full-field and sector-scale) representing fractured EGS reservoirs.
History-match production and injection rates, bottom-hole pressures, and thermal/temperature response against field data.
Iterate reservoir model parameters (permeability, fracture conductivity, compartmentalization, injector-producer connectivity) to improve match quality across wells and pads.
Diagnose root causes of history-match mismatch and distinguish model, data, and operational sources of error.
Use history-matched models to inform production forecasts, well spacing, and injection/production strategy.
Testing & Data Program Development
Design diagnostic and surveillance testing programs — pressure transient tests, interference tests, tracer tests, DFITs, PLT/DTS/DAS — specifically to improve history-matching accuracy.
Identify the data gaps most limiting model calibration and prioritize acquisition programs to close them.
Define minimum viable data requirements per well and pad to support robust history matching within cost and schedule constraints.
Continuously evaluate testing protocols against realized model performance and refine the testing program based on lessons learned.
Extend calibrated models beyond history matching to new prospects, forecasting anticipated crossflow behavior and helping design corresponding crossflow test programs; scope and cadence for this forward-looking work will be defined in coordination with Resource and Exploration teams.
Build repeatable workflows (including automation/scripting) to speed up history-matching iteration and testing feedback loops.
Cross-Functional Collaboration
Partner with Completions and D&C to align stimulation design changes with fracture model predictions and obser