Intelligent sensing and control of the drilling process for fully closed loop automated drilling systems

全闭环自动化钻井系统的钻井过程智能传感和控制

• 批准号: 530374-2018
• 负责人: Shor, Roman
• 金额: $ 14.57万
• 依托单位: University of Calgary
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=694378
• 关键词: Intelligent; sensing; control; drilling; process

The proposed CRD project, "Intelligent sensing and control of the drilling process for fully closed loop automated drilling systems" will seek to attain complete closed loop automated control of drilling operations. Closed loop control has been achieved for many surface operations, however, for operations requiring sensor feedback from downhole sensors - such as directional steering - humans remain in the loop because of significant delays in acquiring data and the small number of data points, typically limited to a few per minute. Attaining full closed loop automation of drilling operations will reduce drilling time and well incidents, increase safety, separate personnel from moving machinery and reduce environmental impacts.This proposal has two aspects: sensing and control. First, we will develop and validate soft sensors, by combining existing sensors with models, which then can be used as inputs into feed forward control systems. As part of this sensor improvement and integration, we will improve data management and analytics through applications of big data, machine learning and the Industrial Internet of Things (IIoT). Secondly, we will develop, validate and implement control strategies that streamline directional drilling operations and improve detection of and reaction to drilling incidents.This project promises to speed the adoption of IIoT and big data by the drilling industry and at the same timestrengthen Canada's IIoT, Artificial Intelligence and Energy industries.

拟议的CRD项目“全闭环自动化钻井系统的钻井过程智能传感和控制”将寻求实现钻井作业的完全闭环自动化控制。许多地面作业已经实现了闭环控制，但是，对于需要井下传感器反馈的作业（例如定向转向），由于获取数据的显着延迟和数据点数量较少（通常仅限于每分钟几个。实现钻井作业的全闭环自动化将减少钻井时间和井事故、提高安全性、将人员与移动机械分开并减少对环境的影响。该建议有两个方面：传感和控制。 首先，我们将通过将现有传感器与模型相结合来开发和验证软传感器，然后将其用作前馈控制系统的输入。作为传感器改进和集成的一部分，我们将通过大数据、机器学习和工业物联网 (IIoT) 的应用来改进数据管理和分析。 其次，我们将开发、验证和实施控制策略，以简化定向钻井作业并改善对钻井事件的检测和反应。该项目有望加快钻井行业对工业物联网和大数据的采用，同时加强加拿大的工业物联网，人工智能和能源行业。