Canada has the third largest oil reserves in the world, mostly in oil sands located in the northern Alberta, which is estimated to be 166 billion barrels. Steam Assisted Gravity Drainage (SAGD) has been the only commercially viable in-situ recovery method available to date. Application of SAGD is known to be energy intensive and has associated environmental impacts. Electromagnetic heating (EMH) has been the focus of ever-increasing theoretical and experimental studies to examine if it can be used to heat up the geomaterials in field scale.
This project will provide guidelines for the design of pipeline systems for deep water locations where fishing activities occur. These pipelines may be subject to loads from trawls and associated trawling equipment. While similar interaction between trawling gear and subsea pipelines has been studied for shallow water pipeline installations, it has not been studied for the deepwater scenario, offshore Newfoundland and Labrador.
In-situ recovery methods for oils sands are applied to reservoirs containing bitumen that are too deep for mining. To date there has been only one commercially viable in-situ recovery method, Steam-Assisted Gravity Drainage (SAGD), involving high pressure steam injection and bitumen production using horizontal well pairs located near the base of oil sands formations. While SAGD has enabled conversion of significant resources to reserves (about 170 billion barrels), SAGD has many economic and environmental limitations.
In northeast British Columbia, earth dams have been constructed to hold water for the oil and gas industry using locally available soils having high clay and silt content. These soils tend to have low shear strength and are susceptible to volume changes from wetting-drying and freeze-thaw cycles, which can lead to increased risk for cracking, slumping, and piping issues in dam embankments.
Mathematical modeling is a powerful tool to understand fluid flow mechanisms, well performance and future resources recovery in petroleum industry. Better and more powerful tool can lead to better reservoir management and more oil production with less cost and less environmental impact.
Based on the original Statistical Inventory Reconciliation(SIR) Test Method (Quantitative), K-folds cross validation is used to increase P(D) and decrease P(FA) by adjusting K, which are related to bias and standard deviation. There is a trade-off between bias and variance, with very flexible models (overfit) having low bias and high variance, and relatively rigid models(underfit) having high bias and low variance. When K is larger, we have lower bias and larger standard deviation. Also, K-folds cross validation is very useful, when data size is small.
While technologies exist for cleaning up marine oil spills, they become decreasingly effective with increased lag-time between spill and initiation of remediation efforts. Rapid-deploy chemicals could potentially reduce the spreading of marine oil spills, increasing the time available for teams to clean it up. The hybrid spill-treating agents (STAs) under development by BC Research Inc. (BCRI) to herd and gel marine oil spills provide great promise in this area. At the current stage of understanding the large-scale behaviour of STAs is unknown, though bench-scale experiments are promising.
Dispersion of various solutes in porous media has been investigated experimentally and theoretically for different scientific purposes. The study of this phenomenon can provide fundamental knowledge of solvent (or gas) flooding in enhanced oil recovery, groundwater contamination, and catalyst-based chemical processes.
The goal of this research is to investigate the extension of upscaling and multiscale methods and their application to efficiently simulate (frequency-dependent and time-dependent) electromagnetic fields in geophysical scenarios that include metallic-cased boreholes and fractures filled with conductive/resistive fluids. Simulating this type of geophysical settings is quite challenging because they consider highly heterogeneous media and features at multiple spatial scales that require a very large mesh to be accurately represented.
Foamy oil behavior is a unique phenomenon associated with cold production of heavy crude oils. It is believed that the foaming mechanism has a significant impact on the abnormally high production rate of viscous crude oils observed in many heavy oil producing reservoirs through solution gas drive.
Due to the non-equilibrium nature of the foamy oil flow, the mathematical modeling of this process involves few challenges. The main non-equilibrium process exist between solution gas and free gas that leads to a significant supersaturation of dissolved gas in the oil phase.