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RC NUMBER

1163991

TRAINING COURSE

PETROLEUM RISK AND DECISION ANALYSIS - PRD

PETROLEUM RISK AND DECISION ANALYSIS - PRD





Good technical and business decisions are based on competent analysis of project costs, benefits and risks. Participants learn the decision analysis process and foundation concepts so they can actively participate in multi-discipline evaluation teams. The focus is on designing and solving decision models. About half the problems relate to exploration. The methods apply to R&D, risk management, and all capital investment decisions.

 

Designed For

Geologists, engineers, geophysicists, managers, team leaders, economists, and planners.

 

You will learn

  • Describe the elements of the decision analysis process and the respective roles of management and the analysis team
  • Express and interpret judgments about risks and uncertainties as probability distributions and popular statistics
  • Represent discrete risk events in Venn diagrams, probability trees, and joint probability tables
  • Solve for expected values with decision trees, payoff tables, and Monte Carlo simulation (hand calculations)
  • Craft and solve decision models
  • Evaluate investment and design alternatives with decision tree analysis
  • Develop and solve decision trees for value of information (VOI) problems

 

Course Content

  • Decision Tree Analysis: decision models, value of information (a key problem type emphasized in the course), flexibility and control, project threats and opportunities
  • Monte Carlo Simulation: Latin hypercube sampling, portfolio problems, optimization, advantages and limitations
  • Decision Criteria and Policy: value measures, multiple objectives, HSE, capital constraint, risk aversion
  • Modeling the Decision: influence diagrams, sensitivity analysis, modeling correlations
  • Basic Probability and Statistics: four fundamental rules including Bayes' rule (the easy way), calibration and eliciting judgments, choosing distribution types, common misconceptions about probability
  • Expected Value Concept: foundation for decision policy, features, pitfalls to avoid
  • Implementing Decision Analysis: problem framing, guidelines for good analysis practice, team analyses, computer tools (discussion and demonstrations), mitigating risks
  • Evaluating a multi-pay prospect (team exercise)

 

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