Principles and Applications of Uncertainty and Risk Analysis For Upstream Oil and Gas: Using Monte C
|Event Date/Time: Nov 17, 2010||End Date/Time: Nov 19, 2010|
This hands-on course provides course participants with a thorough understanding of the fundamentals, applications, and methodologies of risk analysis, uncertainty analysis, and decision analysis. Attendees will utilize Excel and one of the popular add-in Monte Carlo software packages (@RISK or Crystal Ball) as they advance through typical upstream oil & gas models and analyses covering the life cycle of a well or field. Examples and exercises will include resource, reserves, well construction cost and time, production, price, and cash-flow models. A comprehensive final case study will have the participants value a field development and recommend the path forward.
A complete set of course materials and lunch is included in this course.
*Participants will need to bring a PC laptop with Microsoft Excel to each day of this course. At the course a trial version of @Risk or Crystal Ball will be installed*
DAY 1 : Principles of Uncertainty and Risk Analysis
Overview âˆ’ What is Uncertainty, Risk and Decision Analysis? Why do it?
Problem Types: Objectives and recurring themes; uncertainty analysis, risk assessment, Monte Carlo simulation, sensitivities, risk management.
Descriptive Statistics âˆ’ Using historical data, grouping the data, histograms cumulative distribution functions and probability density functions, measures of central tendency and dispersion, confidence intervals.
Distribution Types âˆ’ Discrete vs. continuous variables; common distributions: normal, lognormal, triangular, binomial; confidence intervals; comparing distributions; Monte Carlo sampling.
Modeling â€“ Define distribution, add outputs, list inputs and outputs, simulation settings, run simulation, moving between the spreadsheet and the results.
Building a Simple Model â€“ Profit model.
Interpreting Output and Fitting Distributions to Output
DAY 2 : Monte Carlo Simulation Design and Execution
Designing a Monte Carlo Simulation Model âˆ’ Formulating the model, identifying inputs, choosing input distributions, types of outputs, validating the model, use of field data.
Additional Hands-on Modeling âˆ’ More complex volumetric reserves models.
Fitting Data with Distributions âˆ’ Sources of data, narrowing the choice for the right distribution, goodness-of-fit tests, field examples, expert opinions and interviewing techniques.
Probability of Success â€“ Geologic, mechanical, commercial â€“ how to incorporate them in our models.
Correlation and Dependency âˆ’ Recognizing dependency, cross plots, regression, correlation, incorporating dependency, examples, rank order correlation, dependency effects.
Beyond Volumetric Reserves â€“ Practical upstream applications .
DAY 3 : Applications of Uncertainty and Risk Analysis
Effects of Distribution Type and Correlation âˆ’ Class problem using data to establish distributions and correlation coefficients for a volumetric reserves application.
Production/Economic Forecast Application - Model assumptions, from deterministic to stochastic, imposing uncertainty on prices and costs, model shortcomings and refinements.
Drilling AFE Generation, Cost Models, General Aggregation Models - Finding component parts, sums of distributions, effects of distribution types and correlation.
Comprehensive Models - Reserves to NPV for wells and for prospects.
Simple Exploration or Development Portfolio - Combining reserves, capital, success rates.
Auditing and Reviewing Simulation Models âˆ’ A checklist; techniques for reviewing the model.
Risk Management â€“ Planning and decision-making utilizing uncertainty enlightenment.
Working a Resource Valuation Model