Research & Innovation

Research philosophy

We believe that accurate reservoir understanding requires integrating physics-based modeling with data-driven analytics. Our research spans theoretical poromechanics, numerical simulation, and machine learning — always with an eye toward practical application in African basins.

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Applied Industry Research

GSERC's research is validated against real field data from African and Mediterranean basins. Our industry projects bridge theoretical frameworks with operational execution — producing not just publications, but deployable software, economic decisions, and field development plans. Rio Del Rey Basin · Scikit-Learn

Pillar A — Unconventional Reservoir Intelligence

Multi-method validation framework integrating PTA, RTA, and Modern DCA for tight-gas reservoirs. Cross-validated ultralow permeability (0.01–0.05 mD), fracture half-length (~80–101 ft), and 20-year EUR of 2.758 Bcf. Tunisia · Python Platform

Pillar B — Mature Field Revival & Artificial Lift

Comprehensive artificial lift campaign restoring production from dead wells to 8,000 bbl/d (ESP) and 2,002 STB/d (Gas Lift). Custom tools validated against PROSPER/PIPESIM within ~3%. 10-year economics: +$211M net profit. Tunisia · Cameroon · Python/VBA

Pillar C — Probabilistic Reserves & Economics

Monte Carlo stochastic frameworks replacing deterministic guesses with P90/P50/P10 confidence intervals. Field KK: P50 OOIP = 2.095 Billion barrels. Anonymous offshore: P50 STOOIP = 346.72 MMstb, NPV10 = $231.54M, 5.78-year payback. Mediterranean · West Africa

Pillar D — AI-Driven Subsurface Characterization

Automated well log facies classification using ensemble tree models. Trained on 8,264 points from offshore Cameroon. 99.95% testing accuracy, 0.8-second execution, 100% precision across all lithology classes. Rio Del Rey Basin · Scikit-Learn

10 Active Research Areas

Reservoir Simulation & Numerical Modeling

FDM/FVM discretization, implicit & IMPES formulations, sparse solvers, Newton-Raphson Jacobian assembly, Peaceman well models, analytical validation (Ei-function, Buckley-Leverett, material balance).

Research area 1: Reservoir simulation & numerical modeling
Finite-difference and finite-volume discretization of multiphase flow equations · Implicit and IMPES formulations · Sparse matrix solvers and custom Gaussian elimination · Newton-Raphson Jacobian assembly · Transmissibility calculations with harmonic averaging · Well modeling (Peaceman, dynamic PI, mixed constraints) · Analytical validation (Ei-function, Buckley-Leverett, material balance) · Grid construction: structured Cartesian, non-uniform, heterogeneous

Reservoir Geomodeling & Subsurface Characterization

Static model building, geostatistical modeling, facies characterization uncertainty quantification, heterogeneous/anisotropic permeability, fault compartmentalization.

Research area 2: Reservoir geomodeling & subsurface characterization
Reservoir geomodeling and static model building · Subsurface modeling with spatially varying properties · Formation evaluation and petrophysical analysis · Integration of well log, core, and seismic data · Geostatistical modeling and facies characterization · Uncertainty quantification in subsurface models · Heterogeneous and anisotropic permeability distributions · Fault-induced compartmentalization and barrier modeling

Unconventional Reservoir Engineering

Hydraulic fracturing design, PTA for fractured systems, RTA type-curves (Fetkovich-Arps, Blasingame, Agarwal-Gardner), flow regime identification, shale & tight-gas production forecasting.

Research area 3: Unconventional reservoir engineering
Hydraulic fracturing design and flow regime analysis · Pressure Transient Analysis (PTA) for hydraulically fractured systems · Rate Transient Analysis (RTA) using type-curve methods (Fetkovich-Arps, Blasingame, Agarwal-Gardner) · Flow regime identification and reservoir/fracture parameter evaluation · Production forecasting for shale and tight-gas reservoirs · Fracture network modeling and well interference

Unconventional Reservoir Engineering

Artificial lift design, production system analysis, DCA (Duong, LGM, SEPD, T-model), probabilistic reserves (p10/p50/p90), waterflood optimization, integrated production systems.

Research area 4: Production engineering & optimization
Production engineering workflows and system analysis · Artificial lift system selection, design, and optimization · Production optimization for mature and green fields · Decline Curve Analysis (DCA): Duong, Logistic Growth Model (LGM), SEPD, T-model · Probabilistic reserves estimation (p10/p50/p90) · Reservoir performance enhancement strategies · Waterflood design, implementation, and optimization · Integrated production system modeling

Well Engineering, Integrity & Completion

Hydraulic fracturing modeling, well treatment optimization (acidizing, stimulation, conformance), integrity assessment, wellbore stability, drilling & completion, cementing & zonal isolation.

Research area 5: Well engineering, integrity & completion
Hydraulic fracturing modeling and evaluation · Well treatment optimization (acidizing, stimulation, conformance) · Well integrity assessment and monitoring protocols · Wellbore stability analysis under varying stress states · Drilling and completion recommendations · Well performance modeling with skin and anisotropy corrections · Cementing and zonal isolation studies

Computational Poromechanics & Geomechanics

Pressure-dependent poroelasticity, critical pressure states (PCRIT), porosity-induced stiffening, multi-axial loading, micro-to-reservoir upscaling, anisotropic stress modeling (σH, σh, σv).

Research area 6: Computational poromechanics & geomechanics
Pressure-dependent poroelastic behavior in porous media · Critical pressure states and porosity-induced stiffening phenomena · Multi-axial loading effects on reservoir rock mechanical properties · Upscaling from micro-scale pore networks to reservoir-scale behavior · Coupled flow-geomechanics for compaction and subsidence · Anisotropic stress modeling (σH, σh, σv) · Micro-poromechanical models for pore-volume compressibility

CCUS & Energy Transition

CO₂ injection modeling, reservoir stiffening during storage, site characterization, coupled flow-geomechanics, plume migration & trapping, African asset transition pathways.

Research area 7: CCUS & energy transition
CO₂ injection modeling and reservoir stiffening analysis · Carbon capture, utilization, and storage site characterization · Coupled flow-geomechanics for secure storage · Transition pathways for African petroleum assets · CO₂ plume migration and trapping mechanisms · Reservoir monitoring and verification for storage projects

Data Analytics, Machine Learning & Automation

Python/MATLAB automation, surrogate modeling, physics-informed neural networks (PINNs), Bayesian optimization for history matching, feature engineering, predictive analytics.

Research area 8: Data analytics, machine learning & automation
Automated workflow development in Python and MATLAB · Feature engineering for subsurface datasets · Surrogate modeling for reservoir simulation acceleration · Predictive analytics for production optimization · Physics-informed neural networks (PINNs) · Bayesian optimization for history matching · Data-driven reservoir characterization and production forecasting

Formation Evaluation & Petrophysics

Well log interpretation, core analysis, porosity/permeability/saturation estimation, capillary pressure & relative permeability modeling (Brooks-Corey, Corey-type), rock typing, shale volume.

Research area 9: Formation evaluation & petrophysics
Well log interpretation and integration · Core analysis and laboratory data correlation · Petrophysical property estimation (porosity, permeability, saturation) · Capillary pressure and relative permeability modeling · Brooks-Corey and Corey-type formulations · Rock typing and hydraulic flow unit classification · Shale volume and clay content analysis

Enhanced Recovery & Field Development

Waterflood performance evaluation, EOR screening & design, chemical flooding, gas injection (CO₂, N₂, hydrocarbon), reservoir management, mature field redevelopment, infill drilling optimization.

Research area 10: Enhanced recovery & field development
Waterflood performance evaluation and optimization · Enhanced Oil Recovery (EOR) screening and design · Chemical flooding and surfactant-polymer modeling · Gas injection (CO₂, N₂, hydrocarbon) for miscible/immiscible displacement · Reservoir management and field development planning · Mature field redevelopment and infill drilling optimization
Research outputs
Peer-reviewed journal publications · Conference presentations and proceedings · Technical white papers and case studies · Open-source software tools and libraries · Industry reports and consulting deliverables · Training curricula and educational materials
Multi-Well Pressure Interference & Drainage Simulation — Nechelik Field
A fully self-contained, 2D implicit reservoir simulator in MATLAB modeling transient pressure evolution and multi-well interference in a heterogeneous clastic reservoir. Integrates real-field geostatistical data (porosity and permeability) to evaluate drainage efficiency under mixed boundary conditions.
 
Project overview
Developed a 54 × 22 finite-difference grid (1,188 active blocks) over a reservoir footprint of 7,060 ft × 5,753 ft × 100 ft, directly importing spatially varying porosity and permeability from Nechelik field datasets. Inactive cells (NaN / zero permeability) were rigorously masked to honor geological realism. The simulator runs 1-day timesteps over a 201-day forecast horizon with unconditional stability via implicit matrix inversion.
Heterogeneous grid implementation
Built a 54×22 finite-difference grid with spatially varying porosity and permeability from Nechelik field datasets. Inactive cells rigorously masked to honor geological realism.
Implicit pressure solver
Assembled sparse transmissibility (T), accumulation (B), source (Q), and well productivity (J) matrices. Solved the diffusivity equation implicitly via matrix inversion.
Multi-well physics
Peaceman well model for BHP-controlled producers and constant-rate injector. Captured well-to-well interference, skin effects, and dynamic productivity index evolution.
Analytical validation
Cross-validated numerical pressure profiles against the line-source analytical solution (exponential integral / Ei-function) for radial flow, ensuring code verification.
Production forecasting & visualization.
Computed time-dependent well rates, injector bottom-hole pressure, and cumulative oil production (Np) to support reserves estimation and development planning. Generated publication-quality 3D pressure surface plots, 2D contour maps, and rate-decline curves to communicate reservoir dynamics to stakeholders, universities, and industry partners.
Impact
This simulator serves as a pedagogical and decision-support tool for African independent operators and university trainees, demonstrating how computational geoscience can optimize well spacing, predict waterflood response, and manage reservoir energy in heterogeneous fields — without reliance on expensive commercial software licenses.
Multiphase Waterflood Simulator & Production Forecasting Platform
A fully implicit three-dimensional black-oil reservoir simulator built from first principles in Python to evaluate waterflood performance in heterogeneous petroleum reservoirs. Implements coupled oil-water flow with Newton-Raphson iterations, Jacobian assembly, and scenario-based injection optimization.
PythonNumPy / SciPy3D Finite-DifferenceNewton-RaphsonWaterflood Optimization
Project overview
Led the development and validation of an integrated computational reservoir simulation framework designed to model multiphase fluid flow in petroleum reservoirs and evaluate waterflood performance under various operational scenarios. The project provides a cost-effective, locally developed alternative to commercial reservoir simulators for field performance forecasting and decision support in African oil and gas operations.
3D finite-difference gridding
Cell-centered 3D finite-difference reservoir model using structured Cartesian grids in x, y, and z directions (ngx, ngy, ngz) with cell-based calculations for multiphase flow simulation.
Coupled oil-water flow
Implemented coupled oil-water flow equations with pressure-dependent fluid properties, formation volume factors, viscosities, fluid densities, and rock compressibility effects.
Multiphase characterization
Incorporated relative permeability and capillary pressure functions to model saturation-dependent phase mobility and displacement efficiency in black-oil systems.
Newton-Raphson solver
Developed a fully implicit Newton-Raphson solver with analytical Jacobian matrix construction for robust convergence under strong pressure and saturation nonlinearities.
Well modeling & production analysis
Integrated injection and production well models to calculate dynamic bottom-hole pressure, oil production rate, water production rate, water cut, and water-oil ratio throughout the simulation period. Simulated water injection and oil production performance over long-term production periods exceeding 400 days.
Scenario-based optimization
Evaluated five waterflood development scenarios (Cases 1-5) to quantify the impact of injection rates on reservoir pressure support and recovery performance. Predicted field-scale production indicators including cumulative oil recovery, cumulative water production, water cut evolution, WOR trends, injector pressure, and producer pressure response.
Validation & numerical performance
Performed numerical validation through material-balance error tracking and production history consistency checks. Demonstrated robust numerical performance through low material-balance errors and stable nonlinear convergence throughout long-term reservoir forecasting simulations.
Field development challenges addressed
• Early water breakthrough and increasing water cut during long-term injection scenarios
• Pressure maintenance through optimized water injection strategies
• Balancing oil recovery improvement against increasing water production and operational costs
• Numerical stability and nonlinear convergence of strongly coupled multiphase flow systems
Impact
This platform serves as a production forecasting and waterflood optimization tool for African operators, enabling scenario-based decision-making without the cost barrier of commercial simulators. Trainees gain hands-on experience with the full reservoir simulation workflow — from PVT modeling and relative permeability to Jacobian assembly and production forecasting.
Project 3: Gravity- & Capillary-Driven IMPES Waterflood Simulator
A 2D two-phase oil-water reservoir simulator for dipping reservoirs using the IMPES formulation with Brooks-Corey relative permeability, capillary pressure, gravity segregation, and adaptive well conversion. Validated against the Buckley-Leverett analytical solution. Achieved 46.27% recovery factor over 16.9 years.
 
Project overview
Developed an advanced reservoir simulation framework for modeling oil recovery from structurally complex dipping reservoirs under waterflood operations. The simulator accounts for combined effects of gravity segregation, capillary pressure, relative permeability, reservoir heterogeneity, and well interactions — enabling realistic field-scale production forecasting without commercial software dependency.
IMPES formulation & stability
Implicit pressure solution coupled with explicit saturation update. Upwind mobility weighting ensures numerical stability during water displacement. Timestep sensitivity and numerical dispersion analyzed near displacement fronts.
Multiphase physics
Brooks-Corey relative permeability fitted to lab data. Capillary pressure integrated through empirical curve fitting. Gravity potential calculations capture flow behavior in dipping reservoirs with depths from 12,000 to 13,400 ft.
Adaptive well strategy
One injector at ~2000 STB/day and three producers with BHP constraints. Producing wells automatically convert to injectors when water cut exceeds 95%, improving pressure support and extending field life.
Validation & results
Validated against Buckley-Leverett analytical solution with excellent saturation front agreement. OOIP: 15.89 MMbbl. Recovery: 7.35 MMbbl (46.27%). Field life: 6,169 days (~16.9 years).
Project 4: Indigenous 2D PTA & Well Performance Simulator
A fully implicit 2D non-uniform grid simulator for pressure transient analysis and well performance forecasting in anisotropic heterogeneous reservoirs. Implements Peaceman well modeling with mixed boundary conditions and gravity-aware initialization.
 
Project overview
Developed a fully programmable reservoir simulation platform from first principles for modeling fluid flow in realistic geologic settings characterized by heterogeneity, anisotropy, gravity effects, complex boundary conditions, and multiple well constraints. Serves as a transparent alternative to commercial black-box systems.
Heterogeneous anisotropic grid
3 × 3 non-uniform 2D Cartesian grid covering 1200 × 600 ft with 200 ft thickness. Permeability: 1000–2500 mD. Porosity: 18–26%. Explicit anisotropy with k_y = 2k_x for directional flow investigation.
Mixed well constraints
Constant-rate producer at (600, 300) ft: 10,000 scf/day. Constant BHP well at (1000, 500) ft: 1500 psi. Peaceman productivity index with wellbore radius, skin, effective permeability, and anisotropy corrections.
Numerical innovations
Finite-difference discretization of pressure diffusivity equation · Harmonic averaging for inter-block transmissibility · Fully implicit formulation for unconditional stability · Sparse matrix assembly and efficient linear solution · Gravity-aware pressure initialization and flow calculations · Dynamic well handling through productivity-index-based models
Project 5: Advanced 7×7 Simulator with Fault Barrier
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 in structurally complex reservoirs.
 
Project overview
Developed a physics-based numerical simulator for pressure transient analysis and reservoir performance forecasting in compartmentalized reservoirs with structural barriers. The 7 × 7 Cartesian grid (49 blocks) covers 1400 × 1400 ft with a fault-induced zero-transmissibility barrier creating realistic flow compartmentalization.
Fault & compartment modeling
Fault-induced zero-transmissibility barrier blocks direct pressure communication. Pressure-constrained injection at 6000 psi and production at 3000 psi. Models realistic compartmentalized flow challenges common in African faulted basins.
Custom Gaussian elimination
Developed entirely in Python with custom Gaussian elimination and matrix-solver implementation. Full transparency into numerical solution process. Sparse matrix assembly and coefficient matrix generation from first principles.
Engineering challenges addressed
• Modeling fluid flow around impermeable fault barriers
• Maintaining numerical stability during long-term simulations
• Accurately propagating pressure fronts between injector and producer wells
• Achieving convergence toward steady-state flow conditions
• Handling pressure-constrained boundary conditions within finite-difference framework