Reservoir Engineer, Modeling

Description

Fervo is working to build the most cost-effective, repeatable geothermal power plants in the world. Delivering on this mission requires operational excellence across every function — including the reservoir models and calibration workflows that translate field data into a predictive understanding of how our fractured geothermal reservoirs behave.

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.

• Build and calibrate hydraulic fracture growth models (e.g., Res Frac 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.

• 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.

• 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…