Introduction to Risk and Uncertainty Management Principles
Sound estimation of key engineering, geotechnical and economic parameters is essential for maximizing profitability of oil and gas field development and operations. Characteristic key drivers for development projects include: production profile (initial rate, plateau and decline), capital and operating costs, commodity price, cycle time, EUR, and completion & mechanical chance.
Traditional deterministic methods call for ongoing study of key parameters to get ever closer to “The Right Answer.” Probabilistic methods, on the other hand, recognize that most parameters have some amount of uncertainty, even through the development phase. Accordingly, a better approach is to deal with this uncertainty through probabilistic estimates of key parameters, using the extra time created to evaluate other projects. This course helps professionals learn to become proficient probabilistic estimators!
The course provides a review of fundamental concepts of statistics, uncertainty theory, Project Assurance, reserve uncertainty, chance assessment and aggregation principles. It is designed for engineers, commercial team members, geoscientists, managers and planners involved with drilling, reservoir evaluation and production management.
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Chapter 1- Probabilities and Statistics
1.01 Sample representativeness
1.02 What distributions to expect based on first principles
1.03 The central limits theorem
1.04 Basis of the log cumulative probability plot
1.05 Impact of correlations
Chapter 2 - Estimating under Uncertainty
2.01 Effectiveness of directly estimating an 0% confidence interval
2.02 Causes of bias in our estimates
2.03 The Dunning Kruger effect - why we are all experts until we are not!
2.04 Multiple working hypotheses and peer review benefits
Chapter 3 – Reserve Uncertainty and Chance
3.01 Your accuracy of outputs cannot exceed that of your input variables
3.02 Drivers of ranges in EUR and production forecasts
3.04 Modeling uncertainty in production type well curves
3.05 How to determine chance of geological success
3.06 Determining chance of economic success via fully stochastic models
Chapter 4 – Aggregation Principles
4.01 The use of Trumpet charts to forecast results forma proven region
4.02 Reverse engineering trumpet plots to determine the range of the unknown mean from a region with a limited data set
4.03 Impact of aggregation of booking reserves and resources
4.04 Building confidence curves
4.05 Real time performance tracking using sequential accumulation plots
Chapter 5 – Project Assurance
5.01 The seven conditions for confidence in delivery
5.02 The Value Assurance Process steps
5.03 Sensitivity analysis via spider charts and tornado diagrams
Chapter 1- Probabilities and Statistics
1.01 Sample representativeness
1.02 What distributions to expect based on first principles
1.03 The central limits theorem
1.04 Basis of the log cumulative probability plot
1.05 Impact of correlations
Chapter 2 - Estimating under Uncertainty
2.01 Effectiveness of directly estimating an 0% confidence interval
2.02 Causes of bias in our estimates
2.03 The Dunning Kruger effect - why we are all experts until we are not!
2.04 Multiple working hypotheses and peer review benefits
Chapter 3 – Reserve Uncertainty and Chance
3.01 Your accuracy of outputs cannot exceed that of your input variables
3.02 Drivers of ranges in EUR and production forecasts
3.04 Modeling uncertainty in production type well curves
3.05 How to determine chance of geological success
3.06 Determining chance of economic success via fully stochastic models
Chapter 4 – Aggregation Principles
4.01 The use of Trumpet charts to forecast results forma proven region
4.02 Reverse engineering trumpet plots to determine the range of the unknown mean from a region with a limited data set
4.03 Impact of aggregation of booking reserves and resources
4.04 Building confidence curves
4.05 Real time performance tracking using sequential accumulation plots
Chapter 5 – Project Assurance
5.01 The seven conditions for confidence in delivery
5.02 The Value Assurance Process steps
5.03 Sensitivity analysis via spider charts and tornado diagrams
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