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Grant: Alliance Grants

University of Calgary

$182,000.00

Modeling and Online Optimization of Hard Rock Drilling for Advanced Geothermal Systems

EF 2023-24

Résumé
Due to the depth of hot rock in most regions of Canada, the economic development of geothermal resources remains limited. Recent successful pilots of shallow, low temperature, geothermal energy production have validated the technology necessary for new generations of closed-loop geothermal systems, however, economic electricity production relies on the efficient drilling of igneous basement rock. There is significant experience in drilling softer sedimentary rock, but there is a gap in knowledge and experience in drilling deep wells through hard granitic formations. Allowing access to these hot basement thermal reservoirs would allow for widespread, economic development of geothermal systems. In partnership with Eavor Technology, Inc, this project aims to develop and validate (1) a hard-rock drilling model and (2) combine this model with existing, validated drillstring dynamics models to (3) develop a digital twin of a hard rock drilling system which may be used for optimization, system monitoring, and automation. Additionally, (4) fluid and thermal properties of high flow rate fluids will be investigated and (5) a data-driven model will be developed, compared, and combined with the physics derived model to extend the model capabilities. Over the course of this project, three Ph.D. students, one postdoctoral fellow, and one research associate will be trained.
Programme
Alliance Grants
Bénéficiaire
Emplacement
Alberta, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data

Tel que publié

Application id
561118-2020
Name nom
Kantzas, Apostolos A
Department département
Chemical and Petroleum Engineering
Organization id
11
Institution établissement
University of Calgary
Province en
Alberta
Province fr
Alberta
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2023
Competition year année de concours
2020
Award amount
182000
Program id
ALLRP
Program name en
Alliance Grants
Program name fr
Subventions Alliance
Group en
RESEARCH PARTNERSHIPS
Group fr
PARTENARIATS DE RECHERCHE
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
303
Area of application group en
Energy resources
Area of application group fr
Ressources d'énergie
Area of application en
Alternative energy resources
Area of application fr
Autres ressources d'énergie
Research subject code
2303
Research subject group en
Fuel and energy technology
Research subject group fr
Other sources of energy (solar, wind, etc.)
Research subject en
Combustibles et technologie de l'énergie
Research subject fr
Autres sources d'énergie (combustibles solaire, éolien, etc).
Application title
Modeling and Online Optimization of Hard Rock Drilling for Advanced Geothermal Systems
Keyword
Digital Twin; Drilling Automation; Drillstring Dynamics; Geothermal Drilling; Hammer bit; Hard-rock drilling
Application summary
Due to the depth of hot rock in most regions of Canada, the economic development of geothermal resources remains limited. Recent successful pilots of shallow, low temperature, geothermal energy production have validated the technology necessary for new generations of closed-loop geothermal systems, however, economic electricity production relies on the efficient drilling of igneous basement rock. There is significant experience in drilling softer sedimentary rock, but there is a gap in knowledge and experience in drilling deep wells through hard granitic formations. Allowing access to these hot basement thermal reservoirs would allow for widespread, economic development of geothermal systems. In partnership with Eavor Technology, Inc, this project aims to develop and validate (1) a hard-rock drilling model and (2) combine this model with existing, validated drillstring dynamics models to (3) develop a digital twin of a hard rock drilling system which may be used for optimization, system monitoring, and automation. Additionally, (4) fluid and thermal properties of high flow rate fluids will be investigated and (5) a data-driven model will be developed, compared, and combined with the physics derived model to extend the model capabilities. Over the course of this project, three Ph.D. students, one postdoctoral fellow, and one research associate will be trained.