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 |
Description
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*
Course Outline
DAY 1 : Principles of Uncertainty and Risk Analysis
Overview − 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 − Using historical data, grouping the data, histograms cumulative distribution functions and probability density functions, measures of central tendency and dispersion, confidence intervals.
Distribution Types − Discrete vs. continuous variables; common distributions: normal, lognormal, triangular, binomial; confidence intervals; comparing distributions; Monte Carlo sampling.
Modeling – Define distribution, add outputs, list inputs and outputs, simulation settings, run simulation, moving between the spreadsheet and the results.
Building a Simple Model – Profit model.
Interpreting Output and Fitting Distributions to Output
DAY 2 : Monte Carlo Simulation Design and Execution
Designing a Monte Carlo Simulation Model − Formulating the model, identifying inputs, choosing input distributions, types of outputs, validating the model, use of field data.
Additional Hands-on Modeling − More complex volumetric reserves models.
Fitting Data with Distributions − Sources of data, narrowing the choice for the right distribution, goodness-of-fit tests, field examples, expert opinions and interviewing techniques.
Probability of Success – Geologic, mechanical, commercial – how to incorporate them in our models.
Correlation and Dependency − Recognizing dependency, cross plots, regression, correlation, incorporating dependency, examples, rank order correlation, dependency effects.
Beyond Volumetric Reserves – Practical upstream applications .
DAY 3 : Applications of Uncertainty and Risk Analysis
Effects of Distribution Type and Correlation − 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 − A checklist; techniques for reviewing the model.
Risk Management – Planning and decision-making utilizing uncertainty enlightenment.
Working a Resource Valuation Model