SAGD Impacts: A Perspective on the Surface Freshwater- Groundwater resources in Athabasca Bitumen Deposits, Alberta

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1 CSCE 2013 General Conference - Congrès général 2013 de la SCGC Montréal, Québec May 29 to June 1, 2013 / 29 mai au 1 juin 2013 SAGD Impacts: A Perspective on the Surface Freshwater- Groundwater resources in Athabasca Bitumen Deposits, Alberta Mohamed H. Elsanabary 1, Rick Chalaturnyk 2, Gonzalo Zambrano 3 1 Postdoctoral Fellow, Department of Civil and Environmental Engineering, University of Alberta, Assistant Professor, Civil Engineering Department, Port Said University, Egypt 2 Professor, Department of Civil and Environmental Engineering, University of Alberta 3 Research Associate, Department of Civil and Environmental Engineering, University of Alberta Abstract: Steam Assisted Gravity Drainage (SAGD) could affect the subsurface environment specifically the surface water and the under groundwater regime. The spatial and size distribution of lakes is critical for assessment of the SAGD operation impacts that could have on the water resources of Alberta. The study focuses on the statistical characteristics of the surface water in the Athabasca/Wabasca bitumen deposit regions. This will help in understanding the possible impacts of SAGD process on the surface and groundwater regime in the region. The total surface lake area in the region is about 3435 km 2 i.e. 3.7% of the Athabasca/Wabasca bitumen deposits. The lakes dimensions of this regional area follow a power-law distribution, and the 99% confidence level was (0.01 km 2 ) and for lake equivalent length was (0.08 km). Also, a 3-D groundwater modeling system (GMS) simulation of a local area within the Athabasca/Wabasca region was performed to simulate the groundwater head water variation as a baseline model. Our future work is focusing on imposing the effects from the SAGD simulations on this and similar baseline models using reservoir-geomechanical couple simulations. An comprehensive study is being conducted to assess the impacts of SAGD process on the water resources in the region which will help the policy makers in establishing acts necessary to protect the environment in Alberta. 1 Introduction Currently, the total annual water allocation in Alberta is (9.9 BM 3 /year) one billion m 3 per year (AESRD, 2010). Roughly 88% of the Alberta's population, concentrated in central and southern regions, rely on 13% of the province's surface water supply that found in the North and South Saskatchewan River basins. Another 0.5% of surface water is found in the Beaver River basin. A very small amount (0.1%) of surface water is found in the Milk River basin, which flows to the Gulf of Mexico (AESRD (a), 2013). The surface and groundwater management is controlled by the government of Alberta through licence allocation and transfer systems to satisfy the long-term conservation of Alberta s water resources. Surface and groundwater quality is affected by both natural conditions and human activities. Alberta lakes are often nutrient-rich, making them biologically productive but also sensitive to additional pollutants. Natural sources of sediment, nutrients and other substances can also contribute to background environmental water quality. The groundwater observation well network (GOWN) comprises over 250 monitoring wells spread across the province of Alberta. 200 of these wells are being used to monitor the groundwater levels on a continuous basis. 160 of these wells are used to monitor the groundwater quality for various parameters (AESRD (b), 2013). The three major oil sands deposits in Alberta are explored in three regions, the Athabasca/Wabasca, Cold Lake and Peace River bitumen deposits. The Athabasca River is the main source of water for oil sands projects. 80% of the fresh water used for oil sands mining was from the Athabasca River. Although, the prairie streams have almost no flow, except during rain events in spring, numerous communities and GEN-87-1

2 users meet their water demands from smaller rivers, creeks, local watersheds. The oil sands industry allowed using 7% of Alberta s total water allocation and 2% for conventional oil and gas (AESRD, 2010). Oil sands can be extracted using two different techniques, surface mining and in situ operations. Surface mining operations depend on a water-based process to separate the bitumen from the oil sands. Athabasca River is the main source of water. Other sources of water include rainfall and groundwater that is pumped to dewatering the mines. Both surface mining and in situ operations may potentially affect groundwater quality and quantity. In situ techniques affect water levels in various aquifer intervals primarily through the extraction and use of groundwater for steam generation to assist bitumen recovery. Different from other in situ bitumen extraction techniques the SAGD technology is characterized by lower impacts on the groundwater and water bodies above the injection wells (Ko and Donahue, 2011).As part of the Environmental Impact Assessment process oil sands projects are required to perform extensive hydrological studies and monitoring of the surface and groundwater resources which may be affected by the Bitumen extraction. Several factors affecting the water quality due to in situ oil sands production (AESRD, 12): Physical and chemical effects from substantial heating of subsurface formations; Fractures and creation of pathways to groundwater change at connections between aquifers; The unlikely release of production fluids from casing failures or annular leakage; Pressure effects and continuous migration from waste disposal activities; Operational accidents such as spills, leaks and uncontrolled releases of chemicals and hydrocarbons Groundwater plays a crucial rule in Alberta; supplying water for various purposes from domestic to industrial water needs specifically the Oil sands industry (AESRD (b), 2013). According to Alberta Environment, More than 600,000 rural Albertans get their drinking water from the groundwater. Also, the groundwater help maintain the water level in the surface water bodies e.g. rivers and lakes. Interaction between the water in lakes and rivers and groundwater is evident. Great amount of the water flowing in rivers comes from groundwater seepage into the stream bed. Groundwater contributes to water bodies in physiographic and climatic arrangements. The region's geography, geology, and climate vary the proportion of stream water that comes from groundwater inflow. In order to conduct a quantitative assessment of the water bodies that are within the Bitumen regions of northern Alberta, the Athabasca/Wabasca deposits were selected to conduct the statistical characterization at the regional scale, and within this region a 10 km by 10 km area was selected to conduct a local assessment of surface and groundwater regime. The study area at the regional scale is located in northeast Alberta and is bounded on the west and north by the Athabasca River, to the east by the Alberta/Saskatchewan border and to the south by the Cold Lake Oil sands specifically the Beaver River (Figure 1). This area was selected because it forms the hydrologic divide between the Cold Lake Beaver River drainage basin to the south and the Athabasca river drainage basin to the north. This region encompasses the southeast portion of Athabasca Oil Sands Area that was designated by the Energy Resources Conservation Board (ERCB) of Alberta. Athabasca/Wabasca bitumen deposits located in the north-eastern region of Alberta are the largest known reservoir of crude bitumen in the world and the largest of three major oil sands deposits in Alberta with an approximately surface projected area of 93,700 km 2 (OSDC, 2008; Letcher, 2008). The Wabasca (often called Wabiskaw) oil sands are the fourth largest deposit of oil sands with a surface projected area of 6,700 km 2. The Wabasca deposits are located southwest of the larger Athabasca oil sands deposit. The Wabasca oil sands are at higher stratigraphic level that is under a greater depth of overburden than the mineable portion of the Athabasca oil sands (Speight, 2012). The total added lakes surface areas within the Athabasca/Wabasca bitumen deposits region is approximately 3,435 km 2 that is 3.7% of the projected area of that bitumen deposits. The study, on local scale, within Athabasca/Wabasca region was carried out with the aim of developing the baseline groundwater model for this area that later will be used to assess the effects of the SAGD projects on the groundwater regime. This study used the Groundwater Modeling System (GMS), a finite-difference computer code, to simulate the groundwater flow. This numerical technique has been used effectively in numerous groundwater assessments studies in Alberta (e.g. Stempvoort et al, 1993; Spaling et al, 2000; Schmidt et al, 2010; Vasanthavigar et al., 2010; Jasechko et al, 2012) GEN-87-2

3 130 0'0"W 90 0'0"W 80 0'0"W 70 0'0"W 70 0'0"N 65 0'0"N 65 0'0"N 60 0'0"N Peace River Athabasca/Wabasca 60 0'0"N Regional Scale Athabasca/Wabasca Local Scale Christina Lake Area 50 0'0"N Cold Lake 50 0'0"N 45 0'0"Nµ 45 0'0"N 120 0'0"W 100 0'0"W Kilometers 90 0'0"W Figure 1: Alberta major three Bitumen deposits and the study area is shown by the magenta polygon for the lakes statistics and the red square for the groundwater modeling 2 Objectives and Scope This study is part of a major feasibility investigation on the assessment of the possible effects that SAGD process have on the water bodies and groundwater regime in the bitumen regions of Northern Alberta. This paper discusses only the results from the statistical analysis and GMS simulation as a baseline case. The main objectives of the paper can be summarized as: i) Investigate the surface water bodies at the regional scale in the Athabasca/Wabasca bitumen deposits; ii) Identify the statistical characteristics of the size and geometry of the lakes at the regional scale in the Athabasca/Wabasca bitumen deposits; iii) At the local scale, simulate the groundwater scheme in 10km 10 km area in the Athabasca/Wabasca bitumen deposits as shown in Figure 1. 3 Statistical Analysis Lake dimensions are very important for reservoir-geomechanical couple simulations particularly if the aim is to assess the impacts from SAGD process on the surface water. The outcome of this study will be used to assess multiple scenarios with lake size dimensions that are very probable to find with this region. The geospatial vector data that describe the hydrologic features in the region, such as lakes were obtained from the national hydro network (NHN), GeoBase, most of which are indirect data produced under partnership between federal, provincial and territorial agencies. (GeoBase, 2012). This type of dataset was used to derive statistical relationships of the lake dimensions (both maximum Area, A max, mean Area, A mean, maximum dimension, L max, mean dimension, L mean, etc.). Statistical analysis was carried out for the Athabasca oil sands deposits. Also, the complete lake dataset was screened by excluding the outliers of the lake dimensions to maintain the power law lake size distribution. Figure 2 shows a classification of Athabasca/Wabasca deposits lakes with respect to their surface areas. It is observed from Figure 2 that the majority of the lakes are laying below 1 km 2 (i.e. less than 100 hectare) e.g. Telephone lake which is enclosed by the black circle has a surface area of 0.88 km 2, while few lakes have larger surface area ranging from 1 to 245 km 2. GEN-87-3

4 Telephone Lake 116 0'0"W 115 0'0"W 114 0'0"W 113 0'0"W 112 0'0"W 111 0'0"W 58 0'0"N Area (km^2) areas_a4 < '0"W 90 0'0"W 80 0'0"W '0"W 70 0'0"N '0"N '0"N 57 0'0"N '0"N '0"N 60 0'0"N 50 0'0"N 56 0'0"N 50 0'0"N 56 0'0"N N 45 0'0"N µ 45 0'0"N 120 0'0"W '0"W 90 0'0"W 900 Kilometers N µ 116 0'0"W '0"W Kilometers 114 0'0"W 113 0'0"W 112 0'0"W 111 0'0"W Figure 2: Athabasca Oil Sands with water bodies Table 1 show the descriptive statistical parameters of the lakes in the region with maximum surface 2 area of around 245 km with a very large standard deviation which could lead to misrepresentation of the lakes surface area in the hydrologic simulation. In order to represent the lake dimension in 1-D simulations the lakes have been approximated to squares and the equivalent lake length (L) is calculated by finding the square root of its area as shown in the footnote of Table 1 and 2. It is noted that 82% of the 2 lakes have an area below km. Figure 3 shows the non-power law lake size-distribution. Table 1: Dimension statistics of Athabasca/Wabasca deposits lakes Mean Variance Std Mean squared deviation Minimum value Maximum value Range Lower Quartile, Q1 Median, Q2 Upper Quartile, Q3 Lake Area (km2) Lake perimeter (km) L* (km) * L is the equivalent lake length = GEN-87-4

5 Frequency (log) 100,000 10,000 1, Area Limit # lakes Percent A< % 0.045<A< % 1<A< % 3<A< % 5<A< % 10<A< % 20<A< % 60<A< % > % 10 1 A< <A<1 1<A<3 3<A<5 5<A<10 10<A<20 20<A<60 60<A<70 Area (Km 2 ) Figure 3: Histogram of the Athabasca/Wabasca deposits lakes >70 The confidence interval (P99, P95, P50, P10) are used to calculate the confidence limit for the lake area and lake equivalent length (L) with respect to the number of lakes, standard deviation, mean and confidence level. The total number of lakes in the region is (n=22919 lakes). By applying the Confidence Interval Formula as shown in Eqn. 1 for n 30: Where, ( ) x = Mean lake area or lake equivalent length σ = Standard Deviation ( ) The 99% confidence level was found to be ( km 2 ) for lake equivalent length to be ( km). From visual examination of the lakes in the region and according to Figure 3 the lakes of area km 2, lakes area greater than km 2 were eliminated for further statistical analysis. The total number of lakes in the region is (n= lakes). As a result we expect to get a very low confidence interval ( ) which means we are representing the dominant mean of the lakes area in the region (see Table 2). Figure 4 shows the power law lake size-distribution, uniform histogram and the probability density function of the lakes in the region. Figure 5 shows the cumulative distribution function of the lakes in the region after eliminating the lakes with area greater than km 2. The P99 of the lake equivalent length is 0.08 km. The main purpose behind the descriptive statistics is to find the most appropriate lake equivalent length that is being used to assess the SAGD activities impacts on the underneath water bodies.. GEN-87-5

6 Table 2: Dimension statistics of Athabasca/Wabasca deposits lakes after trimming the lakes with area greater than km 2 Lake Area (km 2 ) Lake perimeter (km) L * (km) Mean Variance Std Mean squared deviation Minimum value Maximum value Range Lower Quartile, Q Median, Q Upper Quartile, Q * L is the equivalent lake length = Figure 4: Histogram of the Athabasca/Wabasca deposits lakes after trimming the lakes with area > km 2 Probability Cumulative Density Function Area (Km 2 ) Figure 5: Cumulative density function of the Athabasca/Wabasca deposits lakes after trimming the lakes with area greater than km 2 4 Groundwater Modeling To better understand the groundwater flow pattern within the Christina Lake area, a groundwater flow model is developed for the study area. This section focuses on an area of 10 km by 10 km GEN-87-6

7 that is centered at the approximate latitude of 55 35ʹ 41ʺ north and longitude of ʹ 52ʺ west. The Canadian Digital Elevation Data (CDED) that consists of an ordered array of ground elevations at regularly spaced intervals has been used to obtain the source digital data for CDED at scales of 1:50,000 and 1:250,000. It is extracted from the hypsographic and hydrographic elements of the National Topographic Data Base (NTDB) or various scaled positional data acquired from the provinces and territories. Figure 6 shows the study area digital elevation model (DEM) with all of the 19 observation wells that were used to identify the soil stratification. The depth of these wells range from 12 meters up to 180 meters, and some of the wells have water table levels that were used to calibrate the model. The steady-state groundwater modeling was developed using the modular three-dimensional finitedifference groundwater flow model GMS. GMS was used to simulate the groundwater in the region of interest. The entire GMS system consists of a graphical user interface that integrates other numerical codes (e.g., MODFLOW). Athabasca/Waba N Figure 6: Christina Lake Study area the yellow dots represent the observation wells A uniform finite difference grid consisting of square grid cells of 200 m by 200 m was overlain on the modeled area. Using the wells data from the Alberta Environment database, a simplified model with different soil layers underneath the Cristina Lake was developed for this study. The numerical groundwater model was constructed using seven layers. Figure 7 presents the simplified conceptual model of the multiple soil layers beneath the Christian lake study area. The surface topography was assigned to the top of layer 1 using a 1:50,000 DEM from the GeoBase database. The bottoms of the layers were defined as follows: i) Layer 1: Brown Till ii) Layer 2: Rocks iii) Layer 3: Gray Till (1) iv) Layer 4: Sand v) Layer 5: Gray Till (2) vi) Layer 6: Consolidated Till vii) Layer 7: Shale The layer class assigned to each of the layers was based on the interpreted data from the GOWN in the area. The Boundary conditions to specify groundwater sources and sinks in the model domain were constant heads, drains and the recharge represented by the precipitation. Constant head value was assigned from groundwater levels recorded in wells within or in close proximity to the modeled area. Groundwater discharge areas can be simulated in MODFLOW using the DRAIN package, by setting the assigned drain level equal to the topography, and the conductance value assigned through estimation GEN-87-7

8 from the drain dimensions. Recharge with a uniform and constant rate of m/day, which is the mean annual precipitation recorded in the study area, was assigned throughout the model domain. The model is assumed to be under steady-state conditions. The layers properties assigned to the model were hydraulic conductivity and porosity. The total porosity was assumed to be 0.3 for all of the layers. The hydraulic conductivity and thickness for each of the seven layers are summarized in Table 3 Table 3: Summary of Hydraulic Parameters Layer Hydraulic Conductivity Thickness, [m] Brown Till to 30 Rocks Gray Till (1) Sand Gray Till (2) Consolidated Till Shale N Layers Brown Till_1 Rocks_10 Gray Till (2)_12 Sand (2)_18 Gray Silty Till_19 Consolidated Silt_20 Shale_23 Figure 7: Simplified Stratigraphy of the 7 sub layers beneath of the Christina Lake Study area The predicted variation groundwater head within the local study area are presented in Figure 8. These results suggest that the groundwater flow initiates at the higher elevation areas to the south eastern zone, recharges into the lower areas to the north, and continues to flow in the Christina Lake. The hydraulic head gradient is greater in areas of larger topographic relief and decreases in the sections of smaller relief. Comparison of the observation wells water levels and the modeled water level was performed. The well represented by G2 in Figure 8 has an observed water level at 6.82 m below the ground level and from the simulation has (ground elevation of minus the simulated head of = 6.4 m). While the differences exist between modeled and existing head in some areas, the authors feel that the model offers a preliminary and general idea regarding the groundwater flow direction in the region and helps to illustrate groundwater flow direction with respect to the SAGD projects implemented in the area as part of the feasibility study to study the impacts of these projects on the groundwater regime. GEN-87-8

9 N Figure 8: Contour map of the Groundwater head 5 Conclusions and Future work In this paper, the statistical assessment of the surface area of water bodies within the Athabasca and Wabasca oil sands region of Alberta was conducted. The total added surface area of the lakes in this region is approximately 3435 km 2 i.e. 3.7% of the Athabasca oil sands. The 99% confidence level was found to be (0.01 km 2 ) for lake equivalent length to be (0.08 km). The results have been used to determine the most dominant lake size in the region and subsequent to study the impacts of SAGD process on the water bodies. The GMS modeling technique is a suitable predicting the groundwater in the Athabasca and Wabasca Oil Sands region. It is important to study the effects of the oil sands projects on the environment. Such activities might affect the surrounding surface and groundwater. Our future work is focusing on imposing the effects from the SAGD simulations using reservoir-geomechanical couple simulations and GMS simulations to predict the surface and groundwater and drainage systems behaviour at a local scale. 6 Acknowledgement The authors thank Canadian Council on Geomatics represented by the GeoBase for providing all the lakes, and DEM data used in the analysis. The financial support was provided through Support from OSUM/Alberta Energy that formed the foundation for this project. Many thanks go to the Alberta Environment for providing the wells data that used for the groundwater modeling. Finally the authors want to thank the two anonymous reviewers for spending time reviewing the paper and for their valuable comments. References Alberta Environment and Sustainable Resource Development (a). Surface Water, [Accessed 25 January 2013]. Alberta Environment and Sustainable Resource Development (b). Groundwater, [Accessed 25 January 2013]. GEN-87-9

10 Alberta Environment and Sustainable Resource Development. Water for life: a renewal [Accessed 26 January 2013]. Alberta Environment and Sustainable Resource Development. Groundwater [Accessed 26 January 2013]. Alberta Environment and Sustainable Resource Development, 2010, Water Use in Canada s Oil Sands, [Accessed 26 January 2013] Alberta Environment and Sustainable Resource Development, 2012, Lower Athabasca Region Groundwater Management Framework, [Accessed 26 January 2013] Speight, J. (2012) Oil Sand Production Processes, Gulf Professional Publishing, 188 pgs., ISBN: Letcher, T. (2008) Future Energy: Improved, Sustainable and Clean Options for our Planet, Elsevier, 400 pgs., ISBN: Geobase, retrieved 15 November 2012) Jasechko, S., Gibson, J. J., Jean Birks, S., Yi, Y. (2012). Quantifying saline groundwater seepage to surface waters in the Athabasca oil sands region, Applied Geochemistry. Ko, J., Donahue, W. F. (2011). Drilling Down: Groundwater Risks Imposed by In Situ Oil Sands Development, Water matters Society of Alberta. Letcher, T. (2008) Future Energy: Improved, Sustainable and Clean Options for our Planet, Elsevier, 400 pgs., ISBN: OSDC, 2008, The Oil Sands Story: The Resource, Edited by the Oil Sands Discovery Centre, Schmidt, A., Gibson, J. J., Santos, I. R., Schubert, M., Tattrie, K., & Weiß, H. (2010) The contribution of groundwater discharge to the overall water budget of two typical Boreal lakes in Alberta/Canada estimated from a radon mass balance. Hydrology and Earth System Sciences, 14(1), 79. Spaling, H., Zwier, J., Ross, W., & Creasey, R. (2000). Managing regional cumulative effects of oil sands development in Alberta, Canada. Journal of Environmental Assessment Policy and Management, 2(04), Van Stempvoort, D., Ewert, L., & Wassenaar, L. (1993) Aquifer vulnerability index: a GIS-compatible method for groundwater vulnerability mapping. Canadian Water Resources Journal, 18(1), Vasanthavigar, M., Srinivasamoorthy, K., Vijayaragavan, K., Rajiv Ganthi, R., Chidambaram, S., Anandhan, P.,... & Vasudevan, S. (2010). Application of water quality index for groundwater quality assessment: Thirumanimuttar sub-basin, Tamilnadu, India. Environmental monitoring and assessment, 171(1), GEN-87-10