• Corrosion Science and Technology
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• v.7 no.6
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• pp.350-361
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• 2008

Canada's oil sands contain one of the largest reserves of oil in the world. According to recent estimates, there are nearly 180 billion barrels of oil in the Canadian oil sands trapped in a complex mixture of sand, water and clay. More than 40 companies have been currently operating or developing oil sands facilities since the first production in 1967. The process of oil sands upgrading is similar with down stream refinery, but the corrosion environment in upgrading refinery is often more severe than in the refinery because of high chlorides, mineral contents, carbonic acid, heavy viscosity and fouling, higher naphthenic acid [$NA-R(CH_{2})nCOOH$], and greater sulfur contents. Naphthenic acid corrosion (NAC) which is one of the most critical corrosion issues in up & downstream refinery plants was observed for the first time in 1920's in refinery distillation processes of Rumania, Azerbaizan (Baku), Venezuela, and California. As a first API report, the 11th annual meeting stated sources and mechanism of NAC in early 1930's. API has been developing the risk base standards, such as API RP580, 571, and Publication 581 which are based on the worst NAC damage in the world since 2000. Nevertheless not only the NAC phenomena and control in Canadian sands oil process are not much widely known but also there are still no engineering guidances for the Canadian sands oil in API standards. This paper will give NAC phenomina and materials selection guidance against NA environment in Canadian oil sands upgrading processes.

• Economic and Environmental Geology
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• v.49 no.3
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• pp.213-224
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• 2016

Non-conventional resource and alternative energy were researched for predicting oil peak. In this study, one of many non-conventional resources, specifically oil-sands, was investigated due to the increasing interest of oil-sands plant modularization in permaforst areas for reducing the construction periods through modular transportation while limiting local construction workers. Hence, tehcnological trends were analyzed for oil-sand plant modularization. Data used were between 1994 and 2015 for patent analysis while targets included Korea, US, Japan, Europe and Canada. Technology classification system consisted of mining, steam assisted gravity drainage(SAGD), separation/upgrading/tailors ponds, module design/packaging, module transportation and material/maintenance. Result of patent analysis, patent application accounts 89% in US and Canada. The main competitive companies were Shell, Suncor and Exxon-mobil. Unlike other oil developments, oil-sands have a long-term stable production characteristic, hence, it is important to ensure the competitiveness of oil-sands for obtaining a patent in the long run.

• Economic and Environmental Geology
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• v.46 no.4
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• pp.313-327
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• 2013

In the study, three-dimensional geostatistical simulations on McMurray Formation which is the largest oil sand reservoir in Athabasca area, Canada were performed, and the optimal site for steam assisted gravity drainage (SAGD) was selected based on the predictions. In the selection, the factors related to the vertical extendibility of steam chamber were considered as the criteria for an optimal site. For the predictions, 110 borehole data acquired from the study area were analyzed in the Markovian transition probability (TP) framework and three-dimensional distributions of the composing media were predicted stochastically through an existing TP based geostatistical model. The potential of a specific medium at a position within the prediction domain was estimated from the ensemble probability based on the multiple realizations. From the ensemble map, the cumulative thickness of the permeable media (i.e. Breccia and Sand) was analyzed and the locations with the highest potential for SAGD applications were delineated. As a supportive criterion for an optimal SAGD site, mean vertical extension of a unit permeable media was also delineated through transition rate based computations. The mean vertical extension of a permeable media show rough agreement with the cumulative thickness in their general distribution. However, the distributions show distinctive disagreement at a few locations where the cumulative thickness was higher due to highly alternating juxtaposition of the permeable and the less permeable media. This observation implies that the cumulative thickness alone may not be a sufficient criterion for an optimal SAGD site and the mean vertical extension of the permeable media needs to be jointly considered for the sound selections.

• Geophysics and Geophysical Exploration
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• v.13 no.1
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• pp.80-87
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• 2010

This study was conducted to develop a reservoir modelling workflow to reproduce the heterogeneous distribution of effective permeability that impacts on the performance of SAGD (Steam Assisted Gravity Drainage), the in-situ bitumen recovery technique in the Athabasca Oil Sands. Lithologic facies distribution is the main cause of the heterogeneity in bitumen reservoirs in the study area. The target formation consists of sand with mudstone facies in a fluvial-to-estuary channel system, where the mudstone interrupts fluid flow and reduces effective permeability. In this study, the lithologic facies is classified into three classes having different characteristics of effective permeability, depending on the shapes of mudstones. The reservoir modelling workflow of this study consists of two main modules; facies modelling and permeability modelling. The facies modelling provides an identification of the three lithologic facies, using a stochastic approach, which mainly control the effective permeability. The permeability modelling populates mudstone volume fraction first, then transforms it into effective permeability. A series of flow simulations applied to mini-models of the lithologic facies obtains the transformation functions of the mudstone volume fraction into the effective permeability. Seismic data contribute to the facies modelling via providing prior probability of facies, which is incorporated in the facies models by geostatistical techniques. In particular, this study employs a probabilistic neural network utilising multiple seismic attributes in facies prediction that improves the prior probability of facies. The result of using the improved prior probability in facies modelling is compared to the conventional method using a single seismic attribute to demonstrate the improvement in the facies discrimination. Using P-wave velocity in combination with density in the multiple seismic attributes is the essence of the improved facies discrimination. This paper also discusses sand matrix porosity that makes P-wave velocity differ between the different facies in the study area, where the sand matrix porosity is uniquely evaluated using log-derived porosity, P-wave velocity and photographically-predicted mudstone volume.