Grant: Collaborative Research and Development Grants
University of Alberta
$96,990.00
Oilsand slurry image and video analysis
FY 2018-19
Summary
In oil sands mining, mined ore which is rich in bitumen is crushed, screened, mixed with water, and transported in a pipeline before extraction takes place to separate bitumen from sand. Recovery rate of bitumen fluctuates and it is known that a portion of the bitumen can be lost to tails due to suboptimal conditions of the extraction process. We propose to conduct collaborative research with Syncrude Canada - the largest oil sands producer of the world - to gain a further scientific understanding of the recovery process by using image processing techniques and data analysis. This understanding will help to improve bitumen recovery rate, and result in benefits that are both economical - through increased production - and environmental - through reduced bitumen in tails.*Specifically, we will develop image processing algorithms to study images of the moving suspended particles or droplets in ore slurry sampled by a novel sensor developed recently by Syncrude, called slurry image analyzer (SIA). These real-time algorithms will derive the characteristics of droplets of both bitumen and sand such as their size, direction and magnitude of motion, shape, and color. Since these characteristics directly translate into bitumen recovery rate, when they are examined under different extraction conditions that can be controlled, Syncrude can then attempt to construct a model that relates the conditions to the recovery rate. With the help of this model, Syncrude's SIA can be installed online to allow field engineers to monitor recovery rate, adjust operating conditions, and achieve optimal extraction performance.*
Program
Collaborative Research and Development Grants
Recipient
Location
Alberta, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
492823-2015
Name nom
Zhang, Hong
Department département
Computing Science
Organization id
9
Institution établissement
University of Alberta
Province en
Alberta
Province fr
Alberta
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2018
Competition year année de concours
2015
Award amount
96990
Program id
CRDPJ
Program name en
Collaborative Research and Development Grants
Program name fr
Subventions de recherche et développement coopérative
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
202
Area of application group en
Natural resources (economic aspects)
Area of application group fr
Ressources naturelles (aspects économiques)
Area of application en
Mineral resources ( prospecting, exploration, mining, extraction, processing)
Area of application fr
Ressources minérales (prospection, exploration, mines, extraction et préparation)
Research subject code
2708
Research subject group en
Information technology
Research subject group fr
Technologie de l'information
Research subject en
Image processing
Research subject fr
Traitement des images
Partie
3
Nb partie
3
Application title
Oilsand slurry image and video analysis
Keyword
NSERC
Application summary
In oil sands mining, mined ore which is rich in bitumen is crushed, screened, mixed with water, and transported in a pipeline before extraction takes place to separate bitumen from sand. Recovery rate of bitumen fluctuates and it is known that a portion of the bitumen can be lost to tails due to suboptimal conditions of the extraction process. We propose to conduct collaborative research with Syncrude Canada - the largest oil sands producer of the world - to gain a further scientific understanding of the recovery process by using image processing techniques and data analysis. This understanding will help to improve bitumen recovery rate, and result in benefits that are both economical - through increased production - and environmental - through reduced bitumen in tails.*Specifically, we will develop image processing algorithms to study images of the moving suspended particles or droplets in ore slurry sampled by a novel sensor developed recently by Syncrude, called slurry image analyzer (SIA). These real-time algorithms will derive the characteristics of droplets of both bitumen and sand such as their size, direction and magnitude of motion, shape, and color. Since these characteristics directly translate into bitumen recovery rate, when they are examined under different extraction conditions that can be controlled, Syncrude can then attempt to construct a model that relates the conditions to the recovery rate. With the help of this model, Syncrude's SIA can be installed online to allow field engineers to monitor recovery rate, adjust operating conditions, and achieve optimal extraction performance.*