Advanced Reservoir Engineering and Performance Prediction Training Course

Advanced Reservoir Engineering and Performance Prediction Training Course

Introduction

Advanced Reservoir Engineering and Performance Prediction Training Course is designed to equip petroleum engineers, reservoir specialists, production engineers, and oil and gas professionals with advanced technical skills for optimizing reservoir performance and maximizing hydrocarbon recovery. The course explores the latest methodologies in reservoir characterization, reservoir simulation, dynamic reservoir modelling, production forecasting, pressure transient analysis, fluid flow modelling, reservoir management, and enhanced oil recovery (EOR). Participants will develop a deeper understanding of complex reservoir behaviour, including multiphase flow, pressure depletion, water and gas drive mechanisms, fluid-rock interactions, and changing reservoir conditions throughout the field lifecycle. By integrating established reservoir engineering principles with modern analytical tools, data-driven workflows, and industry best practices, the programme strengthens the ability to make reliable engineering decisions, improve recovery efficiency, and support economically viable oil and gas field development.

The training also focuses on reservoir performance prediction, production optimization, uncertainty quantification, history matching, predictive analytics, and integrated asset modelling to improve the accuracy of reservoir forecasts and long-term development strategies. Participants will learn how to evaluate production decline, forecast recovery factors, assess reservoir pressure behaviour, estimate ultimate recovery, and identify opportunities for improving field productivity. Through practical exercises, simulation-based learning, real-world case studies, and integrated field development scenarios, learners will gain hands-on experience in evaluating reservoir performance under different operating conditions and development alternatives. The course emphasizes the application of digital oilfield technologies, reservoir surveillance data, machine learning applications in reservoir engineering, and risk-based decision-making to address complex subsurface challenges. By the end of the programme, participants will be better equipped to develop robust reservoir management plans, optimize well and field performance, reduce technical uncertainty, and maximize asset value across the exploration, development, production, and late-life stages of petroleum operations.

Course Duration

10 days

Course Objectives

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

1. Apply advanced reservoir engineering principles to complex hydrocarbon reservoirs and integrated field development projects.
2. Conduct detailed reservoir characterization using geological, petrophysical, geophysical, and production data.
3. Evaluate reservoir fluid properties using advanced PVT analysis and fluid phase behaviour modelling.
4. Interpret pressure transient tests and production data to assess reservoir connectivity, permeability, and pressure behaviour.
5. Develop and validate dynamic reservoir simulation models for reliable performance forecasting.
6. Perform reservoir history matching to improve model accuracy and reduce subsurface uncertainty.
7. Apply advanced production forecasting techniques to predict oil, gas, and water production profiles.
8. Evaluate reservoir drive mechanisms and their effects on recovery efficiency and long-term productivity.
9. Estimate original oil and gas in place (OOIP/OGIP), recovery factors, and ultimate hydrocarbon recovery.
10. Use decline curve analysis and rate-transient analysis to evaluate well performance and forecast production.
11. Assess enhanced oil recovery (EOR) opportunities and compare alternative reservoir recovery strategies.
12. Apply uncertainty quantification, sensitivity analysis, and probabilistic modelling to reservoir development decisions.
13. Develop integrated reservoir management strategies that maximize recovery, improve production efficiency, and enhance asset economics.

Target Audience

1. Reservoir engineers 
2. Petroleum engineers 
3. Production engineers
4. Geoscientists and petrophysicists
5. Reservoir simulation engineers
6. Field development planners and asset managers
7. Oil and gas consultants
8. Technical managers, senior engineers, and professionals

Course Modules

Module 1: Advanced Reservoir Engineering Fundamentals

• Principles of advanced reservoir engineering and fluid flow in porous media.
• Reservoir pressure, temperature, porosity, permeability, and saturation relationships.
• Darcy's law and multiphase flow fundamentals.
• Reservoir heterogeneity, anisotropy, and compartmentalization.
• Case study: Evaluating production differences between homogeneous and heterogeneous reservoirs.

Module 2: Reservoir Characterization and Static Modelling

• Integration of geological, geophysical, and petrophysical data.
• Reservoir facies distribution and depositional environment interpretation.
• Porosity-permeability relationships and rock typing.
• Structural modelling, fault interpretation, and reservoir compartmentalization.
• Case study: Developing a static reservoir model for a faulted sandstone oil field.

Module 3: Reservoir Fluid Properties and PVT Analysis

• Fundamentals of hydrocarbon phase behaviour and fluid characterization.
• Oil, gas, and condensate PVT properties.
• Bubble-point pressure, dew-point pressure, and formation volume factors.
• Fluid viscosity, compressibility, and solution gas-oil ratio analysis.
• Case study: Assessing the effect of changing reservoir pressure on a volatile oil reservoir.

Module 4: Reservoir Drive Mechanisms and Pressure Behaviour

• Solution gas drive, water drive, gas-cap drive, and gravity drainage.
• Reservoir pressure depletion and pressure maintenance.
• Material balance analysis for reservoir performance evaluation.
• Aquifer influx and reservoir energy assessment.
• Case study: Comparing recovery performance under strong water drive and solution gas drive.

Module 5: Advanced Reservoir Simulation and Dynamic Modelling

• Reservoir simulation principles and mathematical model construction.
• Grid design, upscaling, and numerical discretization.
• Relative permeability, capillary pressure, and fluid-flow functions.
• Black-oil, compositional, and thermal simulation approaches.
• Case study: Simulating a mature oil reservoir to evaluate alternative production strategies.

Module 6: Reservoir History Matching and Model Calibration

• Preparation and quality control of historical production data.
• Matching reservoir pressure, oil production, gas production, and water cut.
• Adjustment of permeability, aquifer strength, and relative permeability.
• Parameter estimation and model calibration workflows.
• Case study: History matching a waterflooded reservoir with unexplained water breakthrough.

Module 7: Production Forecasting and Performance Prediction

• Fundamentals of reservoir-based production forecasting.
• Forecasting oil, gas, and water production under changing operating conditions.
• Forecasting well and field performance using simulation models.
• Development of base-case, upside, and downside production scenarios.
• Case study: Predicting production from a developing field under alternative well delivery schedules.

Module 8: Decline Curve Analysis and Rate-Transient Analysis

• Exponential, hyperbolic, and harmonic decline models.
• Estimation of decline parameters and effective production trends.
• Application of rate-transient analysis to well performance evaluation.
• Estimation of estimated ultimate recovery (EUR) and remaining reserves.
• Case study: Comparing conventional decline curve forecasts with observed production from a mature oil field.

Module 9: Reservoir Pressure Transient Analysis

• Pressure buildup, drawdown, and interference testing principles.
• Identification of permeability, skin factor, and reservoir boundaries.
• Well-test interpretation under radial, linear, and boundary-dominated flow.
• Diagnostic plots and pressure derivative analysis.
• Case study: Diagnosing declining productivity in a well affected by formation damage.

Module 10: Well Performance and Integrated Production Systems

• Inflow performance relationships and productivity index evaluation.
• Integration of reservoir inflow with tubing and surface facility performance.
• Nodal analysis for production system optimization.
• Effects of water production, gas handling, and pressure constraints on well performance.
• Case study: Optimizing a constrained oil well by evaluating reservoir pressure and tubing performance.

Module 11: Waterflooding and Enhanced Oil Recovery

• Waterflood design, injection strategies, and sweep efficiency.
• Mobility ratio, displacement efficiency, and breakthrough behaviour.
• Polymer flooding, gas injection, and other EOR techniques.
• Evaluation of recovery improvement and incremental production.
• Case study: Assessing infill drilling and waterflood pattern changes in a mature field.

Module 12: Reservoir Surveillance and Performance Diagnostics

• Integration of pressure, production, injection, and well-test data.
• Water-cut trends, gas-oil ratio, and production allocation analysis.
• Identification of reservoir underperformance and early warning indicators.
• Use of dashboards and digital oilfield monitoring systems.
• Case study: Identifying an injection imbalance responsible for uneven reservoir sweep.

Module 13: Uncertainty Quantification and Sensitivity Analysis

• Identification of geological, petrophysical, and dynamic uncertainties.
• Sensitivity analysis of permeability, porosity, aquifer strength, and relative permeability.
• Probabilistic forecasting and Monte Carlo simulation.
• Low, mid, and high production forecast development.
• Case study: Quantifying forecast uncertainty in a field with limited pressure and production data.

Module 14: Machine Learning and Digital Technologies in Reservoir Engineering

• Applications of machine learning to reservoir performance prediction.
• Data preparation, feature selection, and predictive model development.
• Integration of physics-based simulation with data-driven forecasting.
• Digital twins, automated workflows, and real-time production analytics.
• Case study: Comparing a data-driven production forecast with a conventional reservoir simulation forecast.

Module 15: Integrated Field Development and Reservoir Management Strategy

• Integration of geological, reservoir, drilling, and production engineering.
• Evaluation of infill wells, workovers, injection optimization, and redevelopment options.
• Economic assessment of recovery strategies and production scenarios.
• Development of long-term reservoir management and depletion plans.
• Case study: Preparing an integrated redevelopment plan for a declining offshore oil field.

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.