Projects & Case Studies
Nechelik Field Reservoir Simulator (MATLAB)
A fully implicit 2D finite-difference reservoir simulator modeling multi-well drainage and pressure depletion in heterogeneous oil reservoirs using real-field Nechelik formation data. Validated against the Theis/Ei-function analytical solution.
Multiphase Waterflood Simulator (Python)
A fully implicit 3D black-oil reservoir simulator built from first principles in Python to evaluate waterflood performance. Implements coupled oil-water flow with Newton-Raphson iterations, Jacobian assembly, and scenario-based injection optimization.
Gravity- & Capillary-Driven IMPES Waterflood Simulator (Python)
A 2D two-phase oil-water simulator for dipping reservoirs using IMPES formulation with Brooks-Corey rel perm, capillary pressure, and gravity segregation. Validated against Buckley-Leverett. OOIP: 15.89 MMbbl | Recovery: 46.27% | Field life: 16.9 years.
Indigenous 2D PTA & Well Performance Simulator (Python)
A fully implicit 3×3 non-uniform grid simulator for pressure transient analysis and well performance forecasting in anisotropic heterogeneous reservoirs. Peaceman well model with mixed boundary conditions.
Advanced 7×7 Simulator with Fault Barrier (Python)
A 7×7 Cartesian grid simulator with a fault-induced zero-transmissibility barrier, custom Gaussian elimination solver, and pressure-constrained well operations. Models compartmentalized flow and injector-producer communication.
Industry Case Studies: From Diagnosis to Economic Decision
Real field studies executed for operators in Tunisia, Cameroon, and the Mediterranean. Each project includes custom software development, multiphase hydraulic modeling, and full economic validation.
Case Study: Integrated Unconventional Reservoir Characterization — Tunisia Tight Gas
A multi-method validation framework for a hydraulically fractured tight-gas well, integrating Pressure Transient Analysis (PTA), Rate Transient Analysis (RTA), and Modern Decline Curve Analysis (DCA). Cross-validation across methods confirmed ultralow permeability (0.01–0.05 mD), fracture half-length of ~80–101 ft, and a 20-year EUR of 2.758 Bcf with bounded uncertainty. Developed a Python automation platform for integrated unconventional workflows.
Case Study: Mature Field Revival & Artificial Lift Optimization — EL AIN & KL04
Comprehensive artificial lift campaign restoring production from dead wells (0 STB/d) to profitable rates. Evaluated standalone ESP (8,000 bbl/d), standalone Gas Lift (2,002 STB/d), advanced Variable Position Control valves (+50% gain over conventional GL), and a novel Hybrid GL-ESP architecture. Custom Python and Excel VBA tools validated against commercial PROSPER/PIPESIM with <3% discrepancy. 10-year economics confirm +$211M net profit for ESP and +$33M for optimized gas lift. PROSPER/PIPESIMPythonExcel VBAESP DesignGas Lift
Case Study: Stochastic Field Development Planning & Economic Risk Quantification
Probabilistic reserves estimation and economic evaluation frameworks replacing deterministic single-number guesses with full confidence-interval analysis. Monte Carlo simulation integrated with volumetric methods and material balance quantifies reserves uncertainty (P90/P50/P10) and project profitability under PSC fiscal regimes. Field KK: P50 OOIP = 2.095 Billion barrels. Anonymous offshore field: P50 STOOIP = 346.72 MMstb, NPV10 = $231.54M, ROI = 13.39%, payback = 5.78 years. Excel VBAPythonMonte CarloMaterial BalancePSC EconomicsMachine Learning
Case Study: AI-Driven Formation Evaluation — Rio Del Rey Basin
Automated well log facies interpretation using supervised machine learning. Trained on 8,264 data points from the WERTH NO.1 well (offshore Cameroon), the ENY apps system classifies Sandstone, Sandy-Shale, and Shale intervals in under one second — eliminating days of manual interpretation and removing human subjectivity. Achieves 99.95% testing accuracy with 100% precision across all three lithology classes.