CAREER: Control of a Long and Curved String for Deep Underground Exploration

Texas A&M Engineering Experiment Station, College Station TX

Investigators

Abstract

The research funded by this Faculty Early Career Development Program (CAREER) grant will contribute new fundamental knowledge related to modeling and control of a large-scale system with a long, curved string-like geometry. This will lead to advances in deep underground directional drilling systems impacting national strategic areas including energy, the environment and outer space exploration. Potential impacts include enabling automated directional drilling for enhanced geothermal energy systems and unconventional natural gas production, which will significantly reduce the cost of energy production and enhance production safety; enabling evaluation of large-scale climate patterns; and building the fundamental foundation to control a drilling robot to reach potential signs of microbial life and water resources on Mars, to fulfill the ultimate mission of the Mars exploration. Directional drilling control in these applications is challenging, because potentially undesirable working conditions due to vibrations and wellbore formation interaction in the deep underground are difficult to avoid. Existing studies on the directional drilling control cannot ensure avoiding these undesired operating conditions. The geological challenge and the need for a more environment-friendly production process together urge safer, deeper, more accurate and reliable drilling process. Along with the research, this project will encourage the study of controls engineering among student groups through new curriculum development, teacher education, remote lab facilities development and outreach activities. The research goal of this project is to create a new framework of controlling a large-scale system with a long, curved string-like geometry to avoid undesired operating conditions for deep underground exploration. The outcome includes a novel control-oriented model by leveraging the unique string geometry, and a new method for state-barrier avoidance control that can address complex barriers. For modeling, a new hybrid scheme that can integrate an analytical approach with a numerical solution is researched , and can achieve both computation-efficiency and high fidelity to enable control design. For control, a novel method that resolves the barrier avoidance in a cascade fashion is researched. This method enables addressing state barriers with complex shape in a systematic way for the first time, and can broaden the range of applications of state-barrier avoidance control to more types of barriers and systems (especially with high order dynamics). This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.