Reservoir Engineer - Dynamic Simulation & Ensemble Modeling

1. Job Overview / Summary

As a Reservoir Engineer specializing in Dynamic Simulation and Ensemble Modeling, you will lead the construction, calibration, and execution of advanced numerical reservoir models to optimize asset value, predict field performance, and quantify subsurface uncertainty. You will utilize state-of-the-art ensemble-based workflows (such as assisted history matching and uncertainty quantification) to guide robust field development planning, well placement, and reservoir management decisions.

• Key Responsibilities:

  • Dynamic Reservoir Simulation: Build, calibrate, and maintain high-fidelity compositional and black-oil dynamic reservoir simulation models to forecast primary, secondary, and tertiary (EOR/IOR) recovery scenarios.
  • Ensemble Modeling & Uncertainty Quantification: Design and execute ensemble-based modeling workflows to systematically handle structural, stratigraphic, and fluid uncertainties, moving away from single deterministic models.
  • Assisted History Matching (AHM): Utilize advanced algorithms and statistical tools (e.g., modern AHM software, machine learning/AI techniques) to integrate production logs, pressure data, and 4D seismic into ensemble models.
  • Field Development Planning (FDP): Evaluate and optimize drainage strategies, including well count, spacing, completion designs, artificial lift requirements, and injection patterns to maximize Net Present Value (NPV).
  • Production Forecasting & Reserves: Generate robust probabilistic production forecasts (P10, P50, P90) and support corporate reserves estimation and reporting in alignment with PRMS/SEC guidelines.
  • Cross-Functional Collaboration: Partner closely with Geologists, Geophysicists, Production Engineers, and Drilling teams to ensure seamless integration of static frameworks, fluid properties (PVT), SCAL data, and operational constraints.

• Technical & Domain Skills:

  • Advanced numerical reservoir modeling
  • Ensemble-based workflows (e.g., assisted history matching, uncertainty quantification)
  • Modern algorithms and statistical tools, including machine learning/AI techniques
  • PRMS/SEC guidelines for reserves reporting

• Soft Skills:

  • Cross-functional collaboration
  • Problem-solving
  • Multidisciplinary team integration