Integrated Energy Optimization Model for Oil Sands Operations

Abstract

This article presents a new energy model that predicts the energy infrastructure required to maintain oil production in the Canadian Oil Sands operation at minimum cost. Previous studies in this area have focused on the energy infrastructure for fixed energy demands (i.e., the production schemes that produce synthetic crude oil (SCO) and commercial diluted bitumen remained fixed in the calculation of the optimal infrastructure). The key novelty of this work is that the model searches simultaneously for the most suitable set of oil production schemes and the corresponding energy infrastructures that satisfy the total production demands under environmental constraints, namely, CO 2 emissions targets. The proposed modeling tool was validated using historical data and previous simulations of the Canadian Oil Sands operation in 2003. Likewise, the proposed model was used to study the 2020 Canadian Oil Sands operations under three different production scenarios. Also, the 2020 case study was used to show the effect of CO 2 capture constraints on the oil production schemes and the energy producers. The results show that the proposed model is a practical tool for determining the production costs of the Canadian Oil Sands operations, evaluating future production schemes and energy demand scenarios, and identifying the key parameters that affect Canadian Oil Sands operations.

Optimized integration of renewable energy technologies into Alberta’s oil sands industry

“…Their results included the quantified energy costs and emissions associated with bitumen and SCO production. Betancourt-Torcat et al (2011) later developed an optimization model that simultaneously determines the optimal energy infrastructure and oil sand production schemes, and referred to it as the integrated oil sands energy optimization model. In comparison to the work done by Ordorica-Garcia et al (2008) the energy demands are not determined a priori, instead they are calculated internally in the optimization model since both energy and oil producers are set as decision variables.…”

Stochastic Modeling of the Oil Sands Operations under Greenhouse Gas Emission Restrictions and Water Management

“…The environmental constraint can be set according to data obtained from environmental regulators or green policy projections. 18−20 The deterministic model proposed by Betancourt et al 8 assumes that the natural gas market price and SOR value are perfectly known a priori. This assumption will be relaxed in the following section, and uncertainty will be accounted for using a single-period stochastic programming modeling approach.…”

“…, , DBE f f (8) where HWD is the total demand of hot water in the oil operations and HW f denotes the hot water requirements by stage f. Furthermore, the remaining total energy demands involved in the oil operations are (1) hydrogen (H U ) that depends on the amount used in the upgrading stage (U ∈ f); (2) SAGD steam (SSE), which is determined by the amount consumed in the SAGD extraction stage (SE ∈ f), for both the production of commercial diluted bitumen and SAGD SCO; (3) process fuel (PF U ) which depends on the fuel requirements for upgrading (U ∈ f); and 4) diesel (D) that represents the consumption of fuel in the mining stage (ME ∈ f). Energy Costs.…”

“…Moreover, the most likely of the scenarios suggest the use of ten (10) units of this type of hydrogen plant (i.e., over 85% of the feasible scenarios). The minimum and maximum amounts of HP 4 plants used in the energy scenarios are expected to be eight (8) and twelve (12) units, respectively. This type of plant is selected because it is cost-effective, since these plants are coal-based and also cogenerate electricity; thus, more than one form of useful energy is produced from the same energy resource.…”

“…Their model only considers a case study of the historical Oil Sands operations in the year 2003. Moreover, Betancourt-Torcat et al 8 developed a mixed-integer nonlinear programming (MINLP) model that simultaneously determines the most suitable infrastructures of oil producer and energy plant to minimize the total annual energy cost of the Oil Sands industry. The model includes a CO 2 emission target as environmental constraint and was used to forecast the industry operations for the year 2020.…”