Probabilistic Petroleum Asset Evaluation Training Course

Probabilistic Petroleum Asset Evaluation Training Course

Introduction

Probabilistic Petroleum Asset Evaluation Training Course is designed to equip oil and gas professionals with advanced knowledge and practical skills for evaluating petroleum assets under conditions of geological, technical, commercial, and economic uncertainty. This comprehensive training course explores the principles and applications of probabilistic petroleum asset evaluation, including resource and reserve estimation, production forecasting, field development planning, capital expenditure assessment, operating cost analysis, and hydrocarbon recovery optimization. Participants will learn how to incorporate uncertainty in reservoir properties, hydrocarbon volumes, recovery factors, commodity prices, drilling costs, and production performance into robust economic evaluation models. Through practical exercises and industry-relevant case studies, the course demonstrates how probabilistic methods improve the reliability of petroleum asset valuations and support informed investment decisions across exploration, development, and production portfolios.

The course also focuses on risk-adjusted petroleum economics, probabilistic cash flow modeling, decision-tree analysis, sensitivity analysis, real options valuation, and risk-based portfolio optimization. Participants will develop the ability to interpret P10, P50, and P90 estimates, evaluate probability distributions, quantify the likelihood of achieving project targets, and communicate uncertainty to management, investors, joint venture partners, and regulatory stakeholders. Emphasis is placed on integrating subsurface uncertainty with engineering performance, commercial assumptions, fiscal regimes, and financial indicators such as net present value (NPV), internal rate of return (IRR), and expected monetary value (EMV). The training further examines how probabilistic asset evaluation supports exploration prospect ranking, development concept selection, reserves maturation, investment screening, acquisition and divestment decisions, and long-term production strategy. By the end of the course, participants will be better prepared to build transparent, auditable, and decision-focused petroleum evaluation models that strengthen capital allocation, improve risk management, and maximize the economic value of oil and gas assets.

Course Duration

5 days

Course Objectives

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

1. Explain the principles of probabilistic petroleum asset evaluation and its role in modern oil and gas investment decisions.
2. Apply uncertainty quantification techniques to geological, reservoir, production, and economic parameters.
3. Interpret P10, P50, and P90 estimates for petroleum resources, reserves, production forecasts, and project economics.
4. Develop probabilistic resource and reserve assessment models using appropriate statistical distributions.
5. Apply Monte Carlo simulation to evaluate uncertainty in petroleum asset performance and valuation.
6. Construct integrated petroleum economic models incorporating probabilistic capital expenditure (CAPEX), operating expenditure (OPEX), revenue, and fiscal assumptions.
7. Calculate and interpret risk-adjusted NPV, IRR, EMV, and other investment performance indicators.
8. Conduct sensitivity analysis and scenario modeling to identify critical drivers of petroleum asset value.
9. Evaluate geological, technical, commercial, regulatory, and geopolitical risks affecting asset economics.
10. Apply decision-tree analysis and probability-weighted outcomes to petroleum investment decisions.
11. Integrate reservoir simulation outputs and production forecasting uncertainty into asset valuation.
12. Use probabilistic evaluation to support portfolio optimization, asset acquisition, divestment, and capital allocation.
13. Communicate probabilistic results through risk profiles, uncertainty ranges, probability distributions, and management decision reports.

Target Audience

1. Petroleum engineers and production engineers.
2. Reservoir engineers and reservoir simulation specialists.
3. Geoscientists, exploration geologists, and petroleum resource evaluators.
4. Petroleum economists and oil and gas financial analysts.
5. Asset managers and field development planning professionals.
6. Investment analysts, corporate finance specialists, and valuation consultants.
7. Risk management professionals and petroleum project managers.
8. Oil and gas executives, commercial managers, and business development specialists.

Course Modules

Module 1: Fundamentals of Probabilistic Petroleum Asset Evaluation

• Principles of probabilistic versus deterministic asset evaluation.
• Sources of uncertainty across the petroleum asset lifecycle.
• Overview of geological, engineering, commercial, and economic risk.
• Probability distributions, statistical measures, and confidence levels.
• Establishing evaluation objectives, assumptions, and decision criteria.
• Case study: Compare deterministic and probabilistic valuations for an offshore oil discovery to demonstrate how uncertainty changes investment confidence and development decisions.

Module 2: Probabilistic Resource and Reserve Assessment

• Petroleum resource classification and reserve estimation principles.
• Uncertainty in reservoir area, net pay, porosity, and hydrocarbon saturation.
• Probabilistic estimation of oil initially in place and gas initially in place.
• Recovery factor uncertainty and its impact on recoverable volumes.
• Interpretation of P10, P50, and P90 resource and reserve estimates.
• Case study: Evaluate an undeveloped onshore reservoir using probabilistic volumetric calculations to estimate recoverable reserves under low-, mid-, and high-case assumptions.

Module 3: Statistical Distributions and Uncertainty Quantification

• Selection of normal, lognormal, triangular, uniform, and beta distributions.
• Estimating input ranges from historical data and expert judgment.
• Correlation and dependency between reservoir and production variables.
• Data quality assessment, sampling bias, and uncertainty propagation.
• Model validation, distribution selection, and assumption documentation.
• Case study: Assess uncertainty in porosity, permeability, net-to-gross ratio, and recovery factor to determine how subsurface variables influence recoverable reserves.

Module 4: Monte Carlo Simulation and Probabilistic Modeling

• Fundamentals of Monte Carlo simulation in petroleum economics.
• Defining stochastic input variables and probability distributions.
• Building integrated probabilistic asset evaluation models.
• Running simulation trials and interpreting output distributions.
• Model verification, convergence testing, and simulation result validation.
• Case study: Develop a Monte Carlo model for an offshore development project to estimate the probability of achieving a positive NPV and identify the range of potential project values.

Module 5: Probabilistic Production Forecasting and Reservoir Performance

• Production forecasting under reservoir and operational uncertainty.
• Probabilistic decline curve analysis and production profile modeling.
• Uncertainty in well productivity, water cut, uptime, and decline rates.
• Integration of reservoir simulation results into economic models.
• Evaluating production plateau, recovery performance, and field life.
• Case study: Compare probabilistic production forecasts for a mature oil field under different decline rates, workover success rates, and water-handling constraints.

Module 6: Petroleum Economic Modeling and Risk-Adjusted Valuation

• Developing probabilistic CAPEX, OPEX, and revenue models.
• Modeling oil and gas prices, exchange rates, inflation, and cost escalation.
• Calculating NPV, IRR, payback period, and EMV under uncertainty.
• Incorporating royalties, taxes, production-sharing contracts, and fiscal terms.
• Evaluating breakeven prices, economic limits, and downside exposure.
• Case study: Evaluate a gas development project under uncertain gas prices, pipeline costs, fiscal terms, and production volumes to establish its probability of economic viability.

Module 7: Risk Analysis, Decision Trees, and Portfolio Optimization

• Identifying and quantifying technical and commercial petroleum risks.
• Sensitivity analysis, scenario analysis, and probabilistic tornado charts.
• Decision-tree modeling and probability-weighted investment outcomes.
• Risk-adjusted project ranking and capital allocation strategies.
• Real options analysis for staged investment and development flexibility.
• Case study: Compare three exploration prospects using geological success probabilities, discovery sizes, development costs, and commercial outcomes to determine the preferred investment sequence.

Module 8: Integrated Asset Evaluation, Reporting, and Case Studies

• Integrating subsurface, production, financial, and commercial models.
• Assessing acquisition, divestment, and farm-in or farm-out opportunities.
• Evaluating asset value under alternative development strategies.
• Preparing probabilistic valuation reports and executive dashboards.
• Presenting uncertainty ranges, key risks, and investment recommendations.
• Case study: Conduct an integrated evaluation of a hypothetical producing petroleum asset for acquisition, incorporating reserves uncertainty, forecast production, abandonment liabilities, commodity price scenarios, and risk-adjusted valuation.

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.