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Department of Mathematics & Statistics

MS 476, Math Sciences Building
University of Calgary
2500 University Dr NW
Calgary, AB T2N 1N4 Canada
T. 403.220.5203
F. 403.282.5150

MCFL presents 'Lunch in the Lab' seminar: Two Topics: "Models of Canadian Oil and Gas Prices" and "Modelling Risk and Value in Unconventional Oil Play"

Date & Time:
November 25, 2015 | 2:00 pm
MS 431
GLJ Petroleum Consultans Mike Morgan and Tyler Schlosser

The Mathematical and Computational Finance Laboratory (MCFL) at the Department of Mathematics and Statistics, University of Calgary, invites you to the Fall 2015 'Lunch at the Lab' financial mathematics seminar.



1. Morgan, Mike (GLJ Petroleum Consultans)
2. Schlosser, Tyler (GLJ Petroleum Consultans)


1. Models of Canadian Oil and Gas Prices
2. Modelling Risk and Value in Unconventional Oil Play


1. In most oil and gas economics, the biggest uncertainty is the commodity price. To provide this information, many experts produce very detailed price forecasts. These forecasts tend to follow very smooth trends. Unfortunately, both recent and past events have shown that hydrocarbon prices can change very rapidly.  As well, several competing trends can be found in oil and gas prices. Long-term historical data indicates that hydrocarbon prices tend to revert back to historical averages. However, short-term price fluctuations are unpredictable. To address this need, a price fluctuation model has been developed for the Canadian oil industry.  A random walk model with mean-reversion was developed and tuned to fit Canadian hydrocarbon prices. Starting with the current spot price, the model will generate a random but equiprobable prediction of future prices. The model can be used as input into a Monte-Carlo simulation.   Alternately, the model can be run multiple times in order to generate "high", "low", and "expected" price predictions.

2. In the current lower commodity price environment, characterizing and quantifying risk and understanding value expectations are of great importance to producers, investors and creditors. It is common practice in industry to exclusively use deterministic methods in well and field performance prediction and ultimate recoverable volume estimation,  as well as in commodity price forecasting and cash flow forecasting. This can lead to an incomplete understanding of value expectations, and often, an underestimation of the breadth of possible outcomes. We discuss a general probabilistic workflow for characterizing risk and value in unconventional resource plays, including stochastic decline analysis  and price forecasting methods, geostatistical considerations, and suitable performance metrics to inform decisions. To illustrate some of the benefits this method offers over conventional deterministic methods, we pose several relevant example questions relating to risk and value assessment and proceed to answer them upon completion of this process.