Crystal Ball Recorded Demos
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Crystal Ball
Duration: 2min 42sec
A brief demo illustrating how Crystal Ball can be used to transform existing Excel
spreadsheets to perform risk analysis. The demo shows how probability distributions are
used to define uncertain inputs, define forecasts, run a simulation and interpret
results. Using Crystal Ball, an existing spreadsheet can be used for predictive
modelling in matter of minutes. -
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Evaluating Mining Projects Using Monte Carlo Simulation
Duration: 54min 24sec
In this recording Nathan Stubina of Barrick Gold discusses mining projects that are particularly well-suited to using a Monte Carlo approach. Nathan shows how input parameters such as capital, operating costs, mining rates, recoveries, and metal prices can easily be varied in order to determine which of them will have the greatest impact on the project’s economic success. In this way, project engineers can understand where to direct their focus.
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Portfolio Optimisation in the Oil and Gas Industry
Duration: 49min 47sec
How do you figure out which upstream oil and gas projects will be strong contributors to the company and which will be a waste of corporate time and effort?
During this one-hour recorded seminar, Dave Hammal from Oracle analyses an optimised portfolio of capital projects and examines the sources of systematic and unsystematic risk. You will see how this helps in making decisions about funding and the different impacts this has on a portfolio and its risk/return characteristics. He also discusses- when a project qualifies for an efficient use of corporate capital;
- what is the Efficient Frontier and how to calculate it;
- what is an appropriate measure of risk in capital project evaluation and
- what is the role of strategic flexibility (real options) in project evaluation and the capital allocation decision.
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How BP uses Monte Carlo Analysis as a Risk Management Tool
Duration: 49min 52sec
In this 1-hour recording Hugh Williamson, BP's global specialist on well cost estimation and risk management, discusses how BP has made Monte Carlo analysis part of the way they work. At the end of this seminar, you will have learned:
- Why and how probabilistic estimation has become a core skill for over a thousand well engineering staff at the world's largest privately-owned oil and gas operator;
- The key benefits of the methodology, and some lessons learned from developing models for a large user-group;
- How to apply Crystal Ball software to a Microsoft Excel spreadsheet model and perform your own stochastic analysis.