Regional aquifer parameters evaluated during mine depressurization in the Athabasca Oil Sands, Alberta

1980 ◽  
Vol 17 (1) ◽  
pp. 131-136 ◽  
Author(s):  
Douglas A. Hackbarth
Keyword(s):  
Heavy Oil ◽  
Oil Sands ◽  
Athabasca Oil Sands ◽  
Type Curve ◽  
Pumping Tests ◽  
Oil Saturation ◽  
Aquifer Parameters ◽  
Long Duration ◽  
Observation Wells ◽  
Regional Aquifer

Withdrawal of groundwater for depressurization of the "water sands aquifer" under a test pit in the Athabasca Oil Sands of Alberta caused declines in hydraulic heads in two observation wells located 3700 and 6600 m away. Analysis of these declines over a 6 month period by the time–drawdown method indicated transmissivity values of 68 m2/day for both wells. Pumping tests of 24 h duration had previously indicated that transmissivities at the two observation wells were 1.2 and 118 m2/day.Geological assessment of the water sands aquifer revealed that it is discontinuous between the test pit and the observation wells. Variations in lithology and heavy oil saturation as well as relief on the underlying limestone indicate that the water sands aquifer does not meet the "homogeneous and isotropic" criteria necessary for application of the Theis method of analysis. Nevertheless, the excellent fit of the time–drawdown data to the type curve and the identical values obtained for transmissivity indicate that the method can be used for pumping tests of long duration, which reflect conditions over extensive areas of the water sands aquifer.

Groundwater temperatures in the Athabasca Oil Sands area, Alberta

1978 ◽  
Vol 15 (11) ◽  
pp. 1689-1700 ◽  
Author(s):  
D. A. Hackbarth
Keyword(s):  
Groundwater Flow ◽  
Land Surface ◽  
Oil Sands ◽  
Shallow Groundwater ◽  
Athabasca Oil Sands ◽  
Average Temperature ◽  
Geophysical Logs ◽  
Devonian Age ◽  
Observation Wells ◽  
Made In

Bottom-hole temperatures were measured in groundwater observation wells in the Athabasca Oil Sands area of Alberta. Depth of observation varies from 6–581 m in rocks of Holocene, Cretaceous, and Devonian age. Observations of temperature at various depths at a particular location were made in individual wells.At depths of 300 and 400 m, a correlation of both hydraulic head-loss and temperature with the elevation of the land surface at the observation well indicates that groundwater flow is the dominant parameter controlling subsurface temperatures. The control of groundwater flow on temperature and the location of observation wells in different positions in the groundwater flow system means that temperatures are not well correlated with depth.Bottom-hole temperatures from geophysical logs made in the area are significantly higher than values observed nearby at similar depths during this study. Published thermal gradient maps based upon information from geophysical logs give values which are about twice as high as those calculated with the present data.At depths less than about 60 m temperatures varied widely and at many well sites declined with depth. The average temperature of shallow groundwater was 5.9 °C at an average depth of 12.7 m. This fact indicated that the mean annual air temperature of −0.6 °C should not be used to approximate the temperature of shallow groundwater.

Electromagnetic Induction Heating for Bitumen Recovery: A Case Study in Athabasca Oil Sands

2021 ◽  
Author(s):  
Ahmed Sherwali ◽  
Mehdi Noroozi ◽  
William G. Dunford
Keyword(s):  
Induction Heating ◽  
Oil Recovery ◽  
Heavy Oil ◽  
Oil Sands ◽  
Electromagnetic Induction ◽  
Water Saturation ◽  
Oil Reservoirs ◽  
Athabasca Oil Sands ◽  
Heavy Oil Reservoirs ◽  
Electromagnetic Induction Heating

Abstract This paper demonstrates how electromagnetic induction heating is used for bitumen recovery from the Athabasca oil sands in Alberta with minimal external water requirements. The paper addresses the setup requirements and the necessary parameters for this method to achieve an economic energy to oil ratio. An iterative process is followed to couple the heat rate generated by electromagnetic induction heating to the reservoir model over a defined period. The reservoir model represents a 33 meter payzone with properties for the lower McMurray formation in an area north of Fort McMurray within the Athabasca oil sands deposit. Several scenarios are extensively explored to reach the most practical and feasible setup for oil recovery. The process enables operators to monitor and control reservoir pressure and temperature, liquid production, and energy to oil ratio to maximize recovery from oil sands and heavy oil reservoirs. The results show an expected ultimate oil recovery factor of +70% with an average energy to oil ratio that is lower than the average ratio associated with steam assisted gravity drainage. It is observed that the amount of energy required by the process correlates with water saturation in the near wellbore region, higher water saturation levels are preferred for enhanced oil recovery. It is also noticed that majority of the electromagnetically induced heat rate is generated in the near wellbore region vaporizing any existing water in that region, which eventually slows down the heating process. However, water injection improves the heat convection further into the reservoir, and therefore is essential for establishing a steam chamber using this method. Nevertheless, the volume of injected water required to establish a steam chamber is comparable to the overall volume of water produced from the reservoir, and thus minimal external water is necessary in this process. Moreover, the method is emissions free because heat is generated in the reservoir using an electrically powered downhole inductor (patent pending) that transfers electromagnetic energy to heat. In conclusion, this novel method shows high potential for responsible oil recovery from oil sands and heavy oil reservoirs while meeting economic and environmental expectations. This paper presents the use of a novel clean energy technology to recover bitumen from the Athabasca oil sands in Alberta. Furthermore, the technology is of high value to oil production from heavy oil reservoirs around the world and therefore provides large benefits to the energy industry.

Oil Saturation Log Prediction Using Neural Network in New Steamflood Area

2020 ◽  
Author(s):  
A. Syahputra
Keyword(s):  
Neural Network ◽  
Water Saturation ◽  
Prediction Method ◽  
Neural Model ◽  
Training Model ◽  
Acquisition Time ◽  
Oil Saturation ◽  
Full Field ◽  
Remaining Oil ◽  
Observation Wells

Surveillance is very important in managing a steamflood project. On the current surveillance plan, Temperature and steam ID logs are acquired on observation wells at least every year while CO log (oil saturation log or SO log) every 3 years. Based on those surveillance logs, a dynamic full field reservoir model is updated quarterly. Typically, a high depletion rate happens in a new steamflood area as a function of drainage activities and steamflood injection. Due to different acquisition time, there is a possibility of misalignment or information gaps between remaining oil maps (ie: net pay, average oil saturation or hydrocarbon pore thickness map) with steam chest map, for example a case of high remaining oil on high steam saturation interval. The methodology that is used to predict oil saturation log is neural network. In this neural network method, open hole observation wells logs (static reservoir log) such as vshale, porosity, water saturation effective, and pay non pay interval), dynamic reservoir logs as temperature, steam saturation, oil saturation, and acquisition time are used as input. A study case of a new steamflood area with 16 patterns of single reservoir target used 6 active observation wells and 15 complete logs sets (temperature, steam ID, and CO log), 19 incomplete logs sets (only temperature and steam ID) since 2014 to 2019. Those data were divided as follows ~80% of completed log set data for neural network training model and ~20% of completed log set data for testing the model. As the result of neural model testing, R2 is score 0.86 with RMS 5% oil saturation. In this testing step, oil saturation log prediction is compared to actual data. Only minor data that shows different oil saturation value and overall shape of oil saturation logs are match. This neural network model is then used for oil saturation log prediction in 19 incomplete log set. The oil saturation log prediction method can fill the gap of data to better describe the depletion process in a new steamflood area. This method also helps to align steam map and remaining oil to support reservoir management in a steamflood project.

scholarly journals The Effects of Plume Episodes on PAC Profiles in the Athabasca Oil Sands Region

2021 ◽  
pp. 117014
Author(s):  
Narumol Jariyasopit ◽  
Tom Harner ◽  
Cecilia Shin ◽  
Richard Park
Keyword(s):  
Oil Sands ◽  
Athabasca Oil Sands ◽  
Athabasca Oil Sands Region

scholarly journals Identifying Reservoir Features via iSOR Response Behaviour

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 427
Author(s):  
Jingyi Wang ◽  
Ian Gates
Keyword(s):  
Oil Sands ◽  
Gravity Drainage ◽  
Athabasca Oil Sands ◽  
Steam Chamber ◽  
Heterogeneous Reservoirs ◽  
Steam Assisted Gravity Drainage ◽  
Response Behaviour

To extract viscous bitumen from oil sands reservoirs, steam is injected into the formation to lower the bitumen’s viscosity enabling sufficient mobility for its production to the surface. Steam-assisted gravity drainage (SAGD) is the preferred process for Athabasca oil sands reservoirs but its performance suffers in heterogeneous reservoirs leading to an elevated steam-to-oil ratio (SOR) above that which would be observed in a clean oil sands reservoir. This implies that the SOR could be used as a signature to understand the nature of heterogeneities or other features in reservoirs. In the research reported here, the use of the SOR as a signal to provide information on the heterogeneity of the reservoir is explored. The analysis conducted on prototypical reservoirs reveals that the instantaneous SOR (iSOR) can be used to identify reservoir features. The results show that the iSOR profile exhibits specific signatures that can be used to identify when the steam chamber reaches the top of the formation, a lean zone, a top gas zone, and shale layers.

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