EOR Screening, Economics and Project Selection Training Course

EOR Screening, Economics and Project Selection Training Course

Introduction

EOR Screening, Economics and Project Selection Training Course provides a comprehensive framework for identifying, evaluating, ranking, and selecting Enhanced Oil Recovery (EOR) opportunities that offer strong technical feasibility and attractive commercial returns. This practical course equips petroleum professionals with advanced tools for EOR screening criteria, reservoir characterization, recovery-factor estimation, laboratory data interpretation, uncertainty analysis, production forecasting, incremental recovery assessment, and technology benchmarking. Participants will learn how to move systematically from reservoir screening to technically robust EOR candidates and ultimately develop defensible project-selection recommendations.

The course also focuses strongly on EOR economics, investment decision-making, project risk, economic modelling, sensitivity analysis, scenario planning, and portfolio optimization. Participants will learn how to evaluate CAPEX, OPEX, incremental production, oil price assumptions, cash flow, NPV, IRR, payout period, profitability index, fiscal terms, carbon economics, and economic risk when comparing competing EOR opportunities. Through industry-oriented case studies and practical exercises, participants will develop the ability to distinguish technically promising projects from economically viable investments and to construct EOR project ranking matrices and decision frameworks for field development planning. The training emphasizes integrated reservoir-engineering, production, facilities, commercial, and sustainability considerations, enabling organizations to prioritize EOR investments that maximize value, improve recovery efficiency, manage uncertainty, and support energy transition and lower-carbon oilfield strategies.

Course Duration

5 days

Course Objectives

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

1. Apply advanced EOR screening methodologies to identify technically promising reservoirs and recovery opportunities.
2. Evaluate reservoir characteristics, fluid properties, rock-fluid interactions, and production history for EOR candidate selection.
3. Compare thermal, miscible, chemical, gas injection, and emerging EOR technologies using structured screening criteria.
4. Develop robust EOR screening matrices and ranking methodologies for field-level decision-making.
5. Estimate incremental oil recovery, production uplift, recovery factor, and reserves potential associated with EOR projects.
6. Apply EOR economic evaluation techniques including NPV, IRR, payout, profitability index, and discounted cash flow analysis.
7. Assess CAPEX, OPEX, infrastructure requirements, injection costs, and operating constraints affecting EOR economics.
8. Conduct sensitivity, scenario, uncertainty, and risk analysis for EOR investment decisions.
9. Evaluate the influence of oil prices, fiscal regimes, carbon costs, energy prices, and market assumptions on EOR project economics.
10. Integrate reservoir simulation, production forecasting, laboratory results, and economic models into project-selection decisions.
11. Develop EOR business cases and investment-ready project proposals supported by quantitative evidence.
12. Apply multi-criteria decision analysis (MCDA), value-ranking frameworks, and portfolio optimization to competing EOR opportunities.
13. Formulate practical EOR project selection and implementation strategies that maximize recovery, profitability, resilience, and long-term asset value.

Target Audience

1. Petroleum and Reservoir Engineers
2. Enhanced Oil Recovery and Production Engineers
3. Field Development and Asset Management Professionals
4. Petroleum Geoscientists and Reservoir Modelers
5. Petroleum Economists and Commercial Analysts
6. EOR Project Managers and Investment Professionals
7. Oilfield Planning, Strategy, and Business Development Teams
8. Energy Consultants, Regulators, and Technical Decision-Makers

Course Modules

Module 1: Fundamentals of EOR Screening and Project Selection

• Principles and objectives of Enhanced Oil Recovery
• Primary, secondary, and tertiary recovery mechanisms
• EOR opportunity identification across mature oilfields
• Key technical and commercial screening parameters
• Case Study: Initial screening of a mature sandstone reservoir for EOR deployment

Module 2: Reservoir and Fluid Screening for EOR

• Reservoir depth, temperature, pressure, permeability, and heterogeneity
• Oil viscosity, API gravity, composition, and PVT characteristics
• Rock-fluid interactions and wettability considerations
• Water saturation, reservoir connectivity, and remaining oil distribution
• Case Study: Reservoir-fluid compatibility assessment for chemical EOR

Module 3: EOR Technology Screening and Benchmarking

• CO₂, WAG, and miscible gas injection screening
• Polymer, surfactant, and alkaline flooding evaluation
• Thermal EOR and steam-based recovery applications
• Low-salinity and emerging EOR technologies
• Case Study: Comparative screening of five EOR technologies for a heavy-oil asset

Module 4: EOR Performance Forecasting and Incremental Recovery

• Estimating incremental production and recovery factor
• EOR production profiles and decline-curve considerations
• Reservoir simulation and dynamic forecasting
• Injection efficiency and sweep improvement
• Case Study: Forecasting incremental recovery from a CO₂-EOR project

Module 5: EOR Cost Estimation and Economic Modelling

• EOR CAPEX and OPEX development
• Injection facilities, wells, compression, utilities, and infrastructure costs
• Production revenue and incremental cash-flow modelling
• NPV, IRR, payout period, and profitability index
• Case Study: Economic model for polymer flooding versus waterflood optimization

Module 6: Risk, Uncertainty and Sensitivity Analysis

• Identifying technical, operational, economic, and subsurface risks
• Oil-price, production, cost, and recovery-factor sensitivities
• Scenario analysis and probabilistic evaluation
• Uncertainty ranges and decision-quality analysis
• Case Study: Monte Carlo-style risk assessment for an offshore EOR investment

Module 7: EOR Project Ranking and Portfolio Optimization

• Developing EOR project ranking matrices
• Multi-criteria decision analysis and weighted scoring
• Technical versus economic attractiveness
• Portfolio constraints, capital allocation, and project sequencing
• Case Study: Ranking multiple EOR opportunities across a regional asset portfolio

Module 8: Integrated EOR Project Selection and Investment Decisions

• Building an integrated EOR business case
• Investment gates and project maturation processes
• Sustainability, emissions, carbon intensity, and ESG considerations
• Management presentation and investment recommendation development
• Case Study: Final selection of an EOR project based on technical, economic, risk, and sustainability criteria

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.