Future of the Canadian Oil Sector: Insights from a Hybrid Model Approach Based on Times-Canada

FUTURE OF THE CANADIAN OIL SECTOR: INSIGHTS FROM A HYBRID MODEL APPROACH BASED ON TIMES-CANADA Project funded by the National Science and Engineering Research Council of Canada (NSERC) with strong support from Natural Resources Canada.

Yuri Alcocer, Research Group in Decision Analysis (GERAD), HEC Montreal Montreal, Canada, yuri-ernesto.alcocer- [email protected] Olivier Bahn, GERAD, HEC Montreal, Montreal, Canada [email protected] Camille Fertel, GERAD, University of Quebec in Montreal (UQAM), Montreal, Canada, [email protected] Kathleen Vaillancourt, GERAD, UQAM, Montreal, Canada, [email protected] Jean-Philippe Waaub, GERAD, UQAM, Canada, [email protected] Overview Canada is an important energy producer. It is the largest supplier of natural uranium, a leader in hydroelectricity production and an important producer/exporter of oil, gas and coal. The United States is the main consumer of Canadian energy products counting for about 98% of the total energy exports. Oil and gas production in Canada has experienced a change toward the extraction from more non-conventional sources such as oil sands and shale gas. At the provincial level, Alberta is by far the most significant producer, but the offshore production in Eastern Canada has been increasing significantly. On the medium term, Western oil sands are expected to represent the most important supply resources in Canada. The availability of Canadian oil is uncertain and its accounting as “proved reserves” can vary from one year to another. This accounting difference also occur between diverse reporting official sources. One reason for this variation is related to new technological and economical developments that are increasing the availability of cost-effective unconventional oil.The challenges related to oil sands developments include important increase in energy consumption, greenhouse gas emissions and technology costs. For these reasons, there is an intrinsic marginal cost that is higher for oil sands than for conventional sources. There is also an imminent challenge related to the increasing availability of Western Canadian oil and its distribution to domestic and international markets. Indeed, uncertainty in oil reserves and production implies uncertainty on future trade movements, and consequently, on oil corridors. In the case of Alberta for example, it is economically crucial to benefit from an effective oil corridors network (pipelines, rail, road and marine routes) to distribute its oil production (conventional and non-conventional) to the international markets. In other words, Alberta’s exports, especially those destinated to the United States, depend on the reliability of the oil corridor network. All these challenges have economic implications that translate in a price differential. As a reference, one may consider the recent price differential between Brent and Western Canadian Selected. To address these issues related to the evolution of the Canadian oil sector, the uncertainty on the availability of oil reserves and the risk associated to oil corridors, we propose the use of TIMES-Canada, a bottom-up energy model describing the whole Canadian energy sector including interprovincial and international oil corridors. Furthermore, we extend the functionality of TIMES-Canada by creating “soft-links” with a well count forecasting model providing useful inputs on reserves and future energy demands and with a energy security model providing risk indexes (political, technological and environmental) associated to each oil corridors.

Methods Our approach is based first on the multi-provincial energy model TIMES-Canada for long term energy and environmental policy analysis. In addition, this approach benefits from forecasting models suited for short term analysis, and consequently, for planning and strategic decisions at corporate level, as the evolution relates to the current knowledge of the business. Finally, the approach involve a soft-link with an energy security model based on a multicriteria decision tool, PROMETHEE, in order to assess the safer strategy related to oil trades. TIMES is a linear programming model used for economic analysis of energy and climate policies (Fishbone and Abilock,1981), (Loulou et al., 2005). It represents the entire energy system of a country or a region. Such a system includes the extraction, transformation, distribution, end-uses, and trade of various energy forms and some materials. Each economic sector is described by means of technologies, each of which is characterized by its economic and technological parameters. End-use demands (i.e. energy services) in the base case are based on socio-economic assumptions and are specified exogenously by the user in physical units (industrial production, vehicle-kilometers, etc.) over a future horizon. TIMES computes a dynamic inter-temporal partial equilibrium on integrated energy markets. The objective function to maximize is the total surplus. This is equivalent to minimizing the total discounted system cost while respecting environmental and many technical constraints. The main model outputs are future investments and activities of technologies at each period. An additional output of the model is the implicit price of each energy form, material and emission, which is equal to its opportunity cost (shadow price). The model tracks emissions of CO2, CH4, and N2O from fuel combustion and processes. TIMES-Canada is calibrated on a 2007 base year using recent energy balances (Statistics Canada, 2007). It covers the whole energy system of the 13 Canadian provinces and territories which are linked together through energy, material as well as emission flows. TIMES-Canada spans 44 years (2007 to 2050) with different time periods lengths and 12 annual time slices (four seasons and three periods a day including peak hours). The reference energy system of each province is represented in many details and the oil&gas sector in particular. In the conventional oil sector, there are different primary 2 Intelligent Well Technology: Status and Opportunities for Developing Marginal Reserves SPE production technologies for light oil, heavy oil, condensates, pentanes and offshore light oil. In addition, a distinction is made for light and heavy oil production from located reserves or new discovery reserves and enhanced recovery reserves, as more energy is needed in the latter case. These technologies are characterized by different costs and energy consumption figures to reflect the differences in the different extraction processes. Regarding the oil sands sector, there are distinct technologies for bitumen extracted from mined and in situ methods. In addition, for both methods different technologies represent the production of bitumen and the production of synthetic oil. This requires an deep data collection process to produce a detailed description of the production profile, by province and by oil type. As a resource-constrained model, reserves represents an important input. This input is provided by the well count forecasting model. Then, the TIMES-Canada model gives the optimal pathway to extract these reserves at a detail level by showing the evolution of the type of oil and quantity extracted. To address the security issues, we combine TIMES-Canada with an energy risk (supply or export) model composed of three components, a political one (P) attached to the land unit crossed by the corridor, a technological one (T) attached to the technology characteristics of the segment of corridor, and an environmental one (E) related to the territorial context and energy carrier. The multicriteria risk index is implemented in TIMES-Canada as a technology output. It can be implemented in two different ways: as global index where R = αP + βT + σE. In this case all the risk components have to be normalized and optimized in the same way (maximized or minimized) and the parameters (α, β, σ) are determined according to different risk scenarios; as individual indexes. Then, we build a cost-risk trade-off curve using an iterative approach (European Commission, 2010). The BAU scenario account for the total risk, which is, then constrained step wise.

Results From different business as usual scenarios on the 2100 horizon, following different Canadian socio-economic growths associated to different energy price evolution profiles, we calculate and compare costs and GHG emissions of different conventional and unconventional oil production types under different technology assumptions: The short term evolution (2010-2030) of the different crude oil types. We look particularly price, production and emissions from upstream, midstream and downstream operations. We show how Canadian oil export increase considerably to the US by 2030. In the case of refined products we show how provincial imports change, like in the case of Quebec, where we show an important reduction for gasoline and diesel. We also show the changes in fuel consumption for Alberta. The long term evolution (2030-2100) of the different crude oil types. In this case we look to reserves, energy and emissions related to extraction, transportation and transformation. We provide a security of supply and export analysis of the domestic and international trade movements according the risk components of the oil corridors. Each Canadian provinces and territories as supply and export countries are ranked from the less politically risky to the more according a multicriteria political risk index. The technological disruption risk is computed for each segment of corridor modelled according to their physical characteristics, and expressed as a loss of energy in the transportation network. For example, the technological risk for oil pipeline represents approximately an annually average 57 PJ of loss, which is like an additional cost. Finally, the environmental component, takes into account the socio-environmental acceptability of each energy carrier (e.g: oil sands versus conventional). As result, Times-Canada provides the less risky way to import and export oil, among the existing corridors, or decide to build a new one, if necessary.

Conclusion We successfully model the Canadian oil sector, looking to the details of the different types of conventional and unconventional oil sources. We also model the detail at provincial level, considering the extraction, energy security concerns related to trade movements and refining of the different types of oil in the different provinces. A detail study of quantity, price and emissions is given on this level of detail.

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