Andrew Pancoe
Oil Sands Research Proposal
Oil sands have become increasingly more efficient and demanded in extraction. As the price of
oil is driven up the high extraction cost of oil sands and oil shale becomes less of a deterrent for
producers. The producers of oil have depended heavily on the oil fields of Saudi Arabia and
other Middle East countries for too long. In general oil companies have started to look into
multiple new sources of petroleum other than the conventional oil. The oil sands have become
more economical in recent history. The normal method of surface mining is extremely harmful
to the environment and basically destroys the landscape. My project will be to map out
currently economical oil sand deposits in Canada, the second largest holder of oil, and then
buffer the area affected by the extraction.
The market for oil is constantly changing as the demand by consumers is inelastic compared to
other non luxury goods. Because any market is determined by the consumer’s willingness to
buy, oil prices can be extremely seasonal and fluctuate a large amount. Currently the oil sands
output energy is 5 times that of the input energy. This makes it economical in some sense to
extract, but many companies still rely on conventional methods. The social cost is what I find
the most interesting about oil sands. As they become more economical companies will begin to
buy up land so they can literally tear it apart. These costs are not borne by the companies but
by those people that live near the extraction sites. This is the buffer and spatial analyst that the
project will specifically show. Prior studies have shown that oil sands are becoming more
efficient; however they still affect the environment in a large way.
If there is a large increase in prices of oil sands then oil sands will become more economical and
extracted in greater quantities. To lessen the high marginal social cost oil already has on the
environment buffers will have to be instituted to protect land and people.
The primary data I will need, which has for the large part been mapped out already, is the large
oil fields of Canada. The oil sand in Canada occupies some of the most beautiful landscape
North America has to offer. Alberta is largely unoccupied in the oil field areas and so the most
drastic costs to society will be on the environment. This mapping of the oil sands and the areas
the oil companies need to protect is the main goal of the project. Also general pricing of oil will
be done to anticipate future economical oil sand extraction sites and their necessary buffers.
This data will need to be structured with a rastar format to produce limitations on how far the
companies will be able to extract and the distances that they need from certain amenities.
These places will include wilderness, wildlife, people and towns, and historical sites.
I plan on using rastar calculators to develop buffers for multiple issues that the oil companies
could come into contact with by simply even being close to them. The rastar calculator will be
in an exponential scale so for the larger the scale of a site the larger the buffer will have to be.
The strength of this method is developing a wide berth to hopefully decrease social costs. The
weakness is that it is very hard to calculate the needed amount of a buffer between things like
wilderness where willingness to save it is low.
I expect to find large areas that companies should be distancing sites for environmental
reasons. I do not expect however for these buffers to be acknowledged by the oil producers
though. The public policy for these sites can be extremely improved, because of the high social
cost. These buffers would help to cut down on these costs and not allow companies to tear up
the land.
Budget: 3 Laptops at 750 a piece= $2250. 3 ArcGIS=$ 4500. 2 workers at $30 an hour for 40
hours a week and 5 weeks= $6,000. Total costs= $12,750.
Timeframe:
Week 1: Gathering of Data for Oil Sand deposits.
Week 2: Gathering of pricing data.
Week 3: buffer Calculations.
Week 4: Application of data with buffer areas.
Week 5: Conclusions and new developments