Monte Carlo Simulation for the Oil and Gas Industry
During this 2-day course, participants work directly with spreadsheet-based risk simulation software (either Crystal Ball or @Risk) to examine and modify prepared models and to create simple models of their own. Participants will also analyze historical data using histograms, cross plots, correlation in Excel, and software to fit probability distributions to data. Several worksheet models are included. The course covers software basics such as menus, settings, distributions, outputs, graphics, statistics, sensitivity analysis, interpreting results, and creating reports. Topics include:
• Monte Carlo simulation and the language of statistics
• Simulation design
• Crystal Ball (or @RISK) features, including inputs, outputs, settings, simulation and reports
• Models to estimate reserves
• Changing distribution types and parameters
• Production and economic forecasts
• Operating and capital expenses
• Cross plots and correlation in Excel
• Handling rare events
• Comprehensive models and linking model components
• Class Problems
Why You Should Attend
This course helps with making better business decisions by addressing the uncertainty and risks that occur during projects or planning. Better allocation of money for budgeting is needed, particularly in a competitive environment with significant swings in prices and expectations. Because of that, it becomes even more important to plan ahead for variations and for what might be beyond single numbers.
You’ll learn to use the language of probability and statistics to build practical models for business decisions. This intensive learning opportunity will give you a deeper understanding of the decision-making process and open new doors in your career.
Who Should Attend
This course is intended for engineers, geologists and geophysicists, managers, planners, economists and technical support staff.
Attendees must bring a laptop to class. No previous knowledge of the subject is assumed, although you should be familiar with Excel. Participants are also expected to have experience using models to solve problems, such
as production or economic forecasting, estimating reserves or scheduling.
1.6 CEUs (Continuing Education Units) awarded for this 2-day course.
To receive a full refund, all cancellations must be received in writing no later than 14 days prior to the course start date. Cancellations made after the 14-day window will not be refunded. Send cancellation requests by email to firstname.lastname@example.org; by fax to +1.866.460.3032 (US) or +1.972.852.9292 (outside US); or mail to SPE Registration, PO Box 833836, Richardson, TX 75083.
For more details, please contact us at email@example.com.
Jim Murtha, a registered petroleum engineer, presents seminars and training courses and advises clients in building probabilistic models in risk analysis and decision making. He is an expert on risk and decision analysis. Murtha published Decisions Involving Uncertainty: An @RISK Tutorial for the Petroleum Industry, and is the principal author of the chapter on “Risk Analysis and Decision Making” for the new SPE Petroleum Engineering Handbook.
In 25 years of academic experience, Murtha has chaired a math department, taught petroleum engineering, served as academic dean of a college, and coauthored two texts in mathematics and statistics. He has a PhD in mathematics from the University of Wisconsin, an MS in petroleum and natural gas engineering from Pennsylvania State University, and a BS in mathematics from Marietta College.
Susan Peterson has more than 20 years of experience as a consultant, project manager/senior drilling engineer, and as an instructor. Peterson specializes in risk analysis and decision-making methods for full field development, and AFE time and cost models. As a consultant, Peterson performs project-specific risk analysis and provides training on decision and risk analysis. She has led a risk analysis and decision methods initiative, and has been responsible for the risk analysis on projects ranging from fast-track remote gas field development to large capital expenditure oil development. She holds PhD and MS degrees from Texas A&M University and a BS from Marietta College, all in petroleum engineering.