Advanced Dynamic Reservoir Simulation Training Course

Advanced Dynamic Reservoir Simulation Training Course

Introduction

Advanced Dynamic Reservoir Simulation Training Course is designed to equip oil and gas professionals with advanced technical expertise in reservoir modeling, dynamic reservoir simulation, reservoir performance forecasting, production optimization, and integrated reservoir management. This course provides an in-depth understanding of reservoir simulation principles, numerical modeling techniques, fluid flow dynamics, pressure-transient behavior, multiphase flow, and advanced reservoir characterization. Participants will explore the application of black-oil simulation, compositional reservoir modeling, thermal simulation, uncertainty quantification, history matching, and predictive reservoir analytics to improve reservoir development strategies. Through practical exercises and industry-relevant case studies, learners will develop the technical capabilities required to build, calibrate, validate, and interpret sophisticated reservoir simulation models for conventional and unconventional oil and gas reservoirs.

The course emphasizes the integration of geological models, petrophysical data, seismic interpretation, well logs, pressure measurements, production history, and reservoir engineering data into reliable dynamic simulation workflows. Participants will learn how to evaluate reservoir connectivity, characterize heterogeneity, analyze fluid movement, model aquifer support, simulate enhanced oil recovery (EOR), and forecast long-term production performance under different development scenarios. Advanced topics include ensemble-based history matching, assisted reservoir history matching, machine learning applications in reservoir simulation, digital twin technology, coupled geomechanical simulation, carbon capture and storage (CCS), and uncertainty-based field development planning. The training also examines numerical stability, grid design, simulation convergence, model calibration, and computational efficiency to support robust engineering decisions. By combining theoretical foundations with hands-on modeling exercises, real-world case studies, and collaborative problem-solving, the program enables participants to improve recovery factors, reduce subsurface uncertainty, optimize well placement, strengthen field development plans, and maximize the economic value of petroleum assets throughout their lifecycle.

Course Duration

10 days

Course Objectives

By the end of this course, participants will be able to:

1. Apply advanced dynamic reservoir simulation principles to evaluate reservoir behavior and optimize hydrocarbon recovery.
2. Develop integrated geological and dynamic reservoir models using industry-standard simulation workflows.
3. Configure and optimize reservoir simulation grids, numerical discretization, and computational parameters.
4. Analyze multiphase fluid flow using black-oil, compositional, and advanced fluid-property models.
5. Perform advanced history matching using pressure, production, water-cut, and gas-oil-ratio data.
6. Apply ensemble-based methods and assisted history matching to improve model calibration efficiency.
7. Evaluate reservoir heterogeneity, anisotropy, connectivity, and uncertainty in dynamic performance.
8. Forecast production profiles, pressure depletion, recovery factors, and ultimate hydrocarbon recovery.
9. Optimize well placement, infill drilling, production rates, and injection strategies through simulation.
10. Design and assess enhanced oil recovery (EOR) strategies, including waterflooding and gas injection.
11. Integrate uncertainty quantification and sensitivity analysis into reservoir development planning.
12. Utilize machine learning, reservoir digital twins, and data analytics to improve simulation workflows.
13. Evaluate reservoir development economics and generate technically defensible, risk-informed field optimization recommendations.

Target Audience

1. Reservoir Engineers 
2. Reservoir Simulation Engineers
3. Petroleum Engineers 
4. Geoscientists and Reservoir Geologists 
5. Production Engineers 
6. Enhanced Oil Recovery Specialists designing and evaluating advanced recovery processes.
7. Subsurface Team Leaders and Asset Managers making strategic reservoir development decisions.
8. Research Scientists, Consultants, and Technical Specialists

Course Modules

Module 1: Advanced Reservoir Simulation Fundamentals

• Principles of dynamic reservoir simulation and numerical reservoir engineering.
• Reservoir flow equations and conservation of mass.
• Darcy's law and multiphase fluid-flow fundamentals.
• Black-oil, compositional, and thermal simulation approaches.
• Case Study: Evaluating alternative simulation approaches for a mature offshore oil reservoir.

Module 2: Reservoir Characterization and Static-to-Dynamic Model Integration

• Integration of geological, petrophysical, and geophysical datasets.
• Construction of three-dimensional reservoir property models.
• Porosity, permeability, saturation, and net-to-gross distribution.
• Upscaling geological models for dynamic simulation.
• Case Study: Converting a high-resolution geological model into a simulation-ready reservoir model.

Module 3: Advanced Grid Design and Reservoir Discretization

• Structured, corner-point, and unstructured grid concepts.
• Grid refinement around wells, faults, and complex reservoir features.
• Local grid refinement and adaptive gridding principles.
• Grid sensitivity, numerical dispersion, and computational performance.
• Case Study: Improving well productivity prediction through targeted grid refinement.

Module 4: Reservoir Fluid Properties and PVT Modeling

• Pressure-volume-temperature (PVT) data interpretation.
• Black-oil fluid-property correlations and model calibration.
• Equation-of-state modeling for compositional simulation.
• Fluid phase behavior, gas liberation, and condensate banking.
• Case Study: Assessing the impact of PVT uncertainty on gas-condensate reservoir forecasts.

Module 5: Numerical Methods and Simulation Convergence

• Finite-difference methods and discretization of reservoir flow equations.
• Fully implicit and alternative numerical solution strategies.
• Nonlinear solvers, timestep control, and convergence diagnostics.
• Numerical stability, mass balance, and error analysis.
• Case Study: Diagnosing convergence failures in a highly heterogeneous reservoir model.

Module 6: Advanced History Matching and Model Calibration

• Production and pressure data quality assessment.
• Static and dynamic model calibration workflows.
• Matching oil production, water cut, gas-oil ratio, and pressure.
• Parameter sensitivity and uncertainty-driven history matching.
• Case Study: Calibrating a mature waterflood model against ten years of production data.

Module 7: Assisted History Matching and Ensemble-Based Modeling

• Principles of assisted history matching and automated calibration.
• Ensemble-based reservoir parameter updating.
• Objective functions, parameterization, and model ranking.
• Geological consistency and uncertainty preservation during calibration.
• Case Study: Using multiple model realizations to improve history matching in a faulted reservoir.

Module 8: Reservoir Heterogeneity, Connectivity, and Compartmentalization

• Impact of permeability variation and anisotropy on fluid movement.
• Fault transmissibility and sealing behavior.
• Identification of connected and isolated reservoir compartments.
• Flow diagnostics, tracer analysis, and interwell communication.
• Case Study: Investigating unexpected water breakthrough in a compartmentalized oil field.

Module 9: Production Forecasting and Reservoir Performance Analysis

• Forecasting oil, gas, and water production profiles.
• Reservoir pressure depletion and energy-drive mechanisms.
• Recovery factor estimation and remaining-reserves assessment.
• Production constraints, facility limitations, and forecast uncertainty.
• Case Study: Comparing production forecasts for natural depletion and pressure-maintenance strategies.

Module 10: Well Placement, Infill Drilling, and Development Optimization

• Simulation-based well placement and trajectory evaluation.
• Infill drilling opportunities and unswept hydrocarbon identification.
• Horizontal well modeling and well productivity analysis.
• Production allocation, completion design, and development sequencing.
• Case Study: Ranking infill drilling locations in a mature onshore oil field.

Module 11: Waterflooding and Pressure Maintenance Simulation

• Water injection design and reservoir pressure support.
• Waterflood pattern optimization and sweep-efficiency analysis.
• Water breakthrough prediction and injection conformance.
• Injection allocation, voidage replacement, and injectivity constraints.
• Case Study: Optimizing injector-producer patterns to improve recovery and delay water breakthrough.

Module 12: Enhanced Oil Recovery and Compositional Simulation

• Fundamentals of gas injection, miscible displacement, and chemical EOR.
• Compositional modeling of fluid mixing and phase behavior.
• Thermal recovery and steam-injection simulation concepts.
• Screening EOR scenarios using recovery, risk, and economic indicators.
• Case Study: Comparing immiscible gas injection with miscible gas flooding for a high-pressure reservoir.

Module 13: Uncertainty Quantification and Robust Field Development Planning

• Identification of key geological and dynamic uncertainties.
• Sensitivity analysis and probabilistic production forecasting.
• Low, mid, and high-case reservoir development scenarios.
• Monte Carlo simulation and ensemble-based risk assessment.
• Case Study: Evaluating field development options under uncertainty in aquifer strength and permeability distribution.

Module 14: Digital Reservoir Simulation, AI, and Integrated Workflows

• Applications of machine learning in reservoir engineering.
• Surrogate modeling and accelerated production forecasting.
• Real-time production data integration and model updating.
• Digital reservoir twins and decision-support workflows.
• Case Study: Developing a simplified proxy model to rapidly screen hundreds of development scenarios.

Module 15: Integrated Reservoir Management and Advanced Applications

• Coupled reservoir and geomechanical simulation principles.
• Reservoir simulation for carbon capture, utilization, and storage (CCUS).
• Integration of reservoir, well, and surface-facility constraints.
• Economic evaluation, production optimization, and asset life-cycle planning.
• Case Study: Developing an integrated reservoir management plan balancing hydrocarbon recovery, injection performance, and long-term storage integrity.

Training Methodology

• Interactive lectures and presentations.
• Group discussions and brainstorming sessions.
• Hands-on exercises using real-world datasets.
• Role-playing and scenario-based simulations.
• Analysis of case studies to bridge theory and practice.
• Peer-to-peer learning and networking.
• Expert-led Q&A sessions.
• Continuous feedback and personalized guidance.

Register as a group from 3 participants for a Discount

Send us an email: info@datastatresearch.org or call +254724527104 

Certification

Upon successful completion of this training, participants will be issued with a globally- recognized certificate.

Tailor-Made Course

 We also offer tailor-made courses based on your needs.

Key Notes

a. The participant must be conversant with English.

b. Upon completion of training the participant will be issued with an Authorized Training Certificate

c. Course duration is flexible and the contents can be modified to fit any number of days.

d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.

e. One-year post-training support Consultation and Coaching provided after the course.

f. Payment should be done at least a week before commence of the training, to DATASTAT CONSULTANCY LTD account, as indicated in the invoice so as to enable us prepare better for you.