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Yan E.-R.,East China Normal University | Yan E.-R.,University of Alberta | Hu Y.-L.,University of Alberta | Hu Y.-L.,CAS Shenyang Institute of Applied Ecology | And 5 more authors.
Plant and Soil | Year: 2012

Background and aims: Quantitative relationships between soil N availability indices and tree growth are lacking in the oil sands region of Alberta and this can hinder the development of guidelines for the reclamation of the disturbed landscape after oil sands extraction. The aim of this paper was to establish quantitative relationships between soil N availability indices and tree growth in the oil sands region of Alberta. Methods: In situ N mineralization rates, in situ N availability measured in the field using Plant Root Simulators (PRS™ probes), laboratory aerobic and anaerobic soil N mineralization rates, and soil C/N and N content were determined for both the forest floor and the 0-20 cm mineral soil in eight jack pine (Pinus banksiana Lamb.) stands in the oil sands region in northern Alberta. Tree growth rates were determined based on changes in tree ring width in the last 6 years and as mean annual aboveground biomass increment. Results: Soil N availability indices across those forest stands varied and for each stand it was several times higher in the forest floor than in the mineral soil. The in situ and laboratory aerobic and anaerobic soil N mineralization rates, soil mineralized N, in situ N availability measured using PRS probes, soil C/N ratio and N content in both the forest floor and mineral soil, as well as stand age were linearly correlated with tree ring width of jack pine trees across the selected forest stands, consistent with patterns seen in other published studies and suggesting that N availability could be a limiting factor in the range of jack pine stands studied. Conclusions: In situ and laboratory aerobic and anaerobic N mineralization rates and soil C/N ratio and N content can be used for predicting tree growth in jack pine forests in the oil sand region. Laboratory based measurements such as aerobic and anaerobic N mineralization rates and soil C/N ratio and N content would be preferable as they are more cost effective and equally effective for predicting jack pine growth. © 2012 Springer Science+Business Media B.V.

Hu Y.-L.,CAS Shenyang Institute of Applied Ecology | Hu Y.-L.,University of Alberta | Yan E.-R.,East China Normal University | Choi W.-J.,Chonnam National University | And 5 more authors.
Plant and Soil | Year: 2013

Background and aims: Understanding changes in soil N cycling with stand development is critical for forest management as tree growth is affected by soil N availability. The aim of this study was to evaluate the changes in soil N availability and loss with stand development in trembling aspen (Populus tremuloides Michx.) and jack pine (Pinus banksiana Lamb.) in northeastern Alberta, Canada. Methods: Soil inorganic N availability (measured as N supply rate) and foliar N chemistry (N concentration and δ15N) in trembling aspen stands ranged from 52 to 70 years old (n = 7) and jack pine stands 43 to 78 years old (n = 8) were investigated in 2008 and 2009. The relationships among the ratios of NO3 --N to total inorganic N (NO3 --N/TIN), foliar N concentration, and foliar δ15N with stand age were also explored by regression analyses. Results: Total inorganic N supply rates did not systematically change with stand age across stand types, soil layers and measurement periods; whereas NO3 --N/TIN showed a decreasing tendency with stand age, suggesting that nitrification and associated N loss potential became smaller in older stands with greater limitation in soil N availability. Foliar δ15N decreased with stand age from -1.7 to -4.7‰ for aspen and from -4.1 to -7.1‰ for jack pine, and there were positive correlations between foliar δ15N and soil NO3 --N/TIN, suggesting that decreased soil N loss led to less 15N-depletion in the inorganic N available for tree uptake in older stands. However, foliar N concentration did not significantly change with stand age, suggesting that there were other N sources such as organic N in the forest floor, in addition to the inorganic N, available for plant uptake. Conclusions: Our results suggest that soil inorganic N availability became more limited as stand age increased. In addition, the ratio of NO3 --N/TIN and its relationship with foliar δ15N indicated decreased soil N loss potential and shifted N sources with stand age in boreal forests that are typically N-limited. Our study demonstrated that declining nitrification with increasing stand age might be one of the mechanisms mediating N-limitation in the studied boreal forests. © 2013 Springer Science+Business Media Dordrecht.

Sarkar A.,University of Waterloo | Sarkar A.,Total EandP Canada Ltd. | Seth D.,University of Waterloo | Jiang M.,University of Waterloo | And 2 more authors.
Topics in Catalysis | Year: 2014

Structural characterization, the mechanism of catalytic activity generation and the nature of active sites of a NiSO4/γ-Al 2O3 catalyst for isobutene oligomerization were studied by temperature programmed reduction (TPR), X-ray diffraction (XRD), diffuse reflectance infrared fourier transformed (DRIFTS) and X-ray photoelectron spectroscopy (XPS) techniques. The TPR measurements together with the XRD data indicated that calcination of the catalyst at 500 °C did not form either nickel oxide or nickel aluminate. The presence of only one type of surface nickel species formed by the incorporation of nickel ions into the surface vacant sites of γ-alumina lattice was indicated by XPS with Ar+ ions sputtering and TPR measurements. XPS analysis of the calcined catalyst suggested that the oxidation state of nickel ions in the calcined catalyst was (+2) and after calcination the nickel ions were coordinated to relatively more basic ligands. The surface acid centers of the catalyst were found to be only Lewis type. SO4 2- ions were found to be present as a chelating bidentate ligand and enhanced the acidity of metal Lewis acid centers. The results suggested that the combined effects of the presence of the bidentate SO4 2- ligand and dehydroxylation generate coordinatively unsaturated Ni 2 + that interact with isobutene during the oligomerization reaction. The formation of lower-valent nickel ions was demonstrated by in situ DRIFTS using CO as a probe molecule and by XPS measurements. Formation of a binuclear bridging carbonyl complex, 2 suggested that some lower-valent nickel species were formed via in situ reduction by isobutene. Analysis of Ni 2p photolines indicated the appearance of a new lower-valent nickel species during the course of isobutene oligomerization. Hence it is plausible that lower-valent nickel species might act as the active center for the oligomerization reaction, while the SO4 2- ions enhance the acidity of the Lewis acid sites on the surface and assist in the adsorption of reactant molecules on the surface. © 2014 Springer Science+Business Media New York.

Sarkar A.,University of Waterloo | Sarkar A.,Total EandP Canada Ltd. | Seth D.,University of Waterloo | Ng F.T.T.,University of Waterloo | Rempel G.L.,University of Waterloo
Industrial and Engineering Chemistry Research | Year: 2014

The kinetics of oligomerization of isobutene was studied on a NiSO4/γ-alumina catalyst in a stirred batch autoclave at temperatures of 50-90 °C and a pressure of 2170 kPa with different concentrations of isobutene. Experimental results revealed that the catalyst has high dimer selectivity and did not show any significant deactivation during the reaction. A generalized kinetic model based on a Langmuir-Hinshelwood (LH)-type reaction sequence was developed. The intraparticle diffusion effects inside the catalyst particle were correlated to the reaction rates and mass-transfer rate between the catalyst particle and liquid phase. The developed intrinsic kinetic model with estimated model parameters was found to describe the experimental data accurately. The magnitude of the activation energies was found to be in the range of 13-27 kJ mol-1, which suggests that the oligomerization reaction proceeds via surface rearrangement, as considered in the present LH-type kinetic model. © 2014 American Chemical Society.

Duro D.C.,University of Saskatchewan | Franklin S.E.,Trent University | Dube M.G.,Total EandP Canada Ltd | Dube M.G.,Canadian Rivers Institute
International Journal of Remote Sensing | Year: 2012

The random forest (RF) classifier is a relatively new machine learning algorithm that can handle data sets with large numbers and types of variables. Multi-scale object-based image analysis (MOBIA) can generate dozens, and sometimes hundreds, of variables used to classify earth observation (EO) imagery. In this study, a MOBIA approach is used to classify the land cover in an area undergoing intensive agricultural development. The information derived from the elevation data and imagery from two EO satellites are classified using the RF algorithm. Using a wrapper feature selection algorithm based on the RF, a large initial data set consisting of 418 variables was reduced by ~60%, with relatively little loss in the overall classification accuracy. With this feature-reduced data set, the RF classifier produced a useable depiction of the land cover in the selected study area and achieved an overall classification accuracy of greater than 90%. Variable importance measures produced by the RF algorithm provided an insight into which object features were relatively more important for classifying the individual land-cover types. The MOBIA approach outlined in this study achieved the following: (i) consistently high overall classification accuracies (>85%) using the RF algorithm in all models examined, both before and after feature reduction; (ii) feature selection of a large data set with little expense to the overall classification accuracy; and (iii) increased interpretability of classification models due to the feature selection process and the use of variable importance scores generated by the RF algorithm. © 2012 Copyright Taylor and Francis Group, LLC.

Duro D.C.,University of Saskatchewan | Franklin S.E.,University of Saskatchewan | Franklin S.E.,Trent University | Dube M.G.,Total E and P Canada Ltd
Remote Sensing of Environment | Year: 2012

Pixel-based and object-based image analysis approaches for classifying broad land cover classes over agricultural landscapes are compared using three supervised machine learning algorithms: decision tree (DT), random forest (RF), and the support vector machine (SVM). Overall classification accuracies between pixel-based and object-based classifications were not statistically significant (p > 0.05) when the same machine learning algorithms were applied. Using object-based image analysis, there was a statistically significant difference in classification accuracy between maps produced using the DT algorithm compared to maps produced using either RF (p =0.0116) or SVM algorithms (p =0.0067). Using pixel-based image analysis, there was no statistically significant difference (p > 0.05) between results produced using different classification algorithms. Classifications based on RF and SVM algorithms provided a more visually adequate depiction of wetland, riparian, and crop land cover types when compared to DT based classifications, using either object-based or pixel-based image analysis. In this study, pixel-based classifications utilized fewer variables (15 vs. 300), achieved similar classification accuracies, and required less time to produce than object-based classifications. Object-based classifications produced a visually appealing generalized appearance of land cover classes. Based exclusively on overall accuracy reports, there was no advantage to preferring one image analysis approach over another for the purposes of mapping broad land cover types in agricultural environments using medium spatial resolution earth observation imagery. © 2011 Elsevier Inc.

Li X.,University of Alberta | Li X.,CAS Nanjing Institute of Soil Science | Chang S.X.,University of Alberta | Salifu K.F.,Total e and P Canada Ltd.
Environmental Reviews | Year: 2014

Soil texture and its vertical spatial heterogeneity may greatly influence soil hydraulic properties and the distribution of water and solutes in the soil profile; therefore, they are of great importance for agricultural, environmental, and geo-engineering applications such as land reclamation and landfill construction. This paper reviews the following aspects on water and salt dynamics in the presence of a water table: (i) the effect of soil texture on the extent of upward movement of groundwater in homogenous soils and (ii) the impact of soil textural layering on water and salt dynamics. For a homogenous soil, the maximum height of capillary rise (hmax) or the evaporation characteristic length (ECL) is closely related to the soil texture. When the water table is deeper than hmax, water will evaporate at some depth below surface and salts will be retained below the evaporation front, causing the separation of water and salt. For layered soils, flow barriers (capillary and hydraulic barriers) can make the soil hold more water than a nonlayered one. A capillary barrier may work when a fine-textured layer overlies a coarse-textured layer during infiltration or a coarse-textured layer overlies a fine-textured layer during evaporation, and a hydraulic barrier may occur when a poorly permeable layer exists in the soil profile. The extra water held by flow barriers may improve water availability to plants and may at the same time increase salinization and other environmental risks. Under special conditions, such as in seasonally frozen soils with a shallow water table, there is an additional soil salinization incentive caused by freeze-thaw cycles. Above all, further research is needed to understand the complex effects of soil texture and layering on water and salt dynamics, especially in artificial soils such as reclaimed soils with contrasting properties. © 2013 Published by NRC Research Press.

Babak O.,Total E and P Canada Ltd. | Manchuk J.G.,University of Alberta | Deutsch C.V.,University of Alberta
Computers and Geosciences | Year: 2013

Facies models are used to better capture heterogeneity in mineral deposits and petroleum reservoirs. Facies are often considered as mutually exclusive and exhaustive at the scale of the geological model. These two assumptions are needed for sequential indicator simulation and most other facies modeling techniques; however, the assumption that an entire grid block consists of one facies type becomes unreasonable as the scale increases. Most geological models are built at a scale that is larger than the scale of variation of facies. Mixing of multiple facies types within a grid cell is common, especially in zones of transition between different facies. This paper develops a new technique to address the issue of non-exclusivity of facies within grid cells. The approach quantifies the uncertainty resulting from majority-vote upscaling of facies from core or well log scale to the grid cell scale and utilizes this uncertainty to build better models of continuous reservoir properties such as bitumen grade. Uncertainty is quantified using a measure of entropy that is capable of handling situations where there may be similarity between different facies types. A methodology to implement entropy in geo-modeling is introduced and demonstrated with several small examples. An example involving real data from the McMurray formation of Total's Joslyn lease is used to demonstrate the improvement in accuracy compared with traditional modeling workflows. © 2012 Elsevier Ltd.

Babak O.,Total E andP Canada Ltd. | Bergey P.,Total E andP Canada Ltd. | Deutsch C.V.,University of Alberta
Journal of Petroleum Science and Engineering | Year: 2014

Large scale trends are important geological features that should be accounted for in geostatistical characterization of uncertainty. The workflow for uncertainty characterization accounting for a trend involves two major steps: (1) trend modeling and (2) integrating the trend into geostatistical estimation and/or simulation. While there are several options to consider for integrating trend models into geostatistical workflow, building a reasonable and fair trend model based on data coming from different sources and/or defined on different support still presents a challenge. In this paper we describe a locally varying methodology for building a facies proportion trend for Surmont area of Athabasca Oil Sands. The trend is built based on vertical well data and seismic attribute - acoustic impedance; several probability combination schemes are considered for merging facies probability cubes calculated from the two data sources. All steps required building trend models and selecting one representative based on the criteria of fairness and certainty are documented and detailed. © 2014 Elsevier B.V.

Babak O.,Total EandP Canada Ltd.
Stochastic Environmental Research and Risk Assessment | Year: 2014

Inverse distance weighted interpolation is a robust and widely used estimation technique. In practical applications, inverse distance interpolation is oftentimes favored over kriging-based techniques when there is a problem of making meaningful estimates of the field spatial structure. Nowadays application of inverse distance interpolation is limited to continuous random variable modeling. There is a need to extend the approach to categorical/discrete random variables. In this paper we propose such an extension using indicator formalism. The applicability of inverse distance interpolation for categorical modeling is then illustrated using Total's Joslyn Lease facies data. © 2013 Springer-Verlag Berlin Heidelberg.

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