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

先进地热系统硬岩钻探的建模和在线优化

• 批准号: 561118-2020
• 负责人: Shor, Roman
• 金额: $ 16.08万
• 依托单位: University of Calgary
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=721889
• 关键词: Modeling; Online; Optimization; Hard; Rock

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.

由于加拿大大部分地区的热岩很深，地热资源的经济开发仍然有限。最近成功的浅层低温地热能生产试点验证了新一代闭环地热系统所需的技术，然而，经济的电力生产依赖于对火成岩基岩的有效钻探。在钻探较软沉积岩方面有着丰富的经验，但在通过坚硬花岗岩地层钻探深威尔斯井方面，在知识和经验方面还存在差距。允许进入这些热的基底热储层将允许地热系统的广泛、经济的开发。与Eavor Technology，Inc.合作，该项目旨在开发和验证（1）硬岩钻井模型，（2）将该模型与现有的经验证的钻柱动力学模型联合收割机相结合，（3）开发可用于优化、系统监控和自动化的硬岩钻井系统的数字孪生模型。此外，（4）将研究高流速流体的流体和热特性;（5）将开发、比较数据驱动模型，并将其与物理推导模型相结合，以扩展模型功能。在这个项目的过程中，三位博士将培训一名学生、一名博士后研究员和一名研究助理。