TU Darmstadt / ULB / TUbiblio

Data-driven Adaptive Surface Control for Automated Directional Drilling

Häusser, Felix ; Himmel, Andreas ; Karvinen, Kai S. ; Findeisen, Rolf (2023)
Data-driven Adaptive Surface Control for Automated Directional Drilling.
2023 IEEE Conference on Control Technology and Applications. Bridgetown, Barbados (16.-18.08.2023)
doi: 10.1109/CCTA54093.2023.10252434
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

Directional drilling is the process of drilling boreholes that adhere to a specified reference well plan as closely as possible while ensuring safe operation. This process is typically controlled by repeatedly manipulating the steering inputs of an underground bottom-hole assembly. In contrast, the surface inputs, such as the mud flow rate, the drill string rotation speed, or the hook load, are only occasionally adjusted, requiring expert knowledge. This is due to the fact that it is challenging to model the influence of the surface inputs on the drilling process - especially the downhole activity. To tackle this challenge, a data-driven adaptive two degree of freedom control concept is proposed. This control concept applies a simplified data-based surrogate model of the directional drilling process. The surrogate model is subsequently used in an adaptive two degree of freedom control concept, splitting the tasks into reference tracking and disturbance rejection. The control concept is tested in a virtual directional drilling test environment to automatically adjust the drill string rotation speed and hook load to achieve a desired trajectory curvature.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2023
Autor(en): Häusser, Felix ; Himmel, Andreas ; Karvinen, Kai S. ; Findeisen, Rolf
Art des Eintrags: Bibliographie
Titel: Data-driven Adaptive Surface Control for Automated Directional Drilling
Sprache: Englisch
Publikationsjahr: 22 September 2023
Verlag: IEEE
Buchtitel: 2023 IEEE Conference on Control Technology and Applications (CCTA)
Veranstaltungstitel: 2023 IEEE Conference on Control Technology and Applications
Veranstaltungsort: Bridgetown, Barbados
Veranstaltungsdatum: 16.-18.08.2023
DOI: 10.1109/CCTA54093.2023.10252434
Kurzbeschreibung (Abstract):

Directional drilling is the process of drilling boreholes that adhere to a specified reference well plan as closely as possible while ensuring safe operation. This process is typically controlled by repeatedly manipulating the steering inputs of an underground bottom-hole assembly. In contrast, the surface inputs, such as the mud flow rate, the drill string rotation speed, or the hook load, are only occasionally adjusted, requiring expert knowledge. This is due to the fact that it is challenging to model the influence of the surface inputs on the drilling process - especially the downhole activity. To tackle this challenge, a data-driven adaptive two degree of freedom control concept is proposed. This control concept applies a simplified data-based surrogate model of the directional drilling process. The surrogate model is subsequently used in an adaptive two degree of freedom control concept, splitting the tasks into reference tracking and disturbance rejection. The control concept is tested in a virtual directional drilling test environment to automatically adjust the drill string rotation speed and hook load to achieve a desired trajectory curvature.

Fachbereich(e)/-gebiet(e): 18 Fachbereich Elektrotechnik und Informationstechnik
18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Automatisierungstechnik und Mechatronik
18 Fachbereich Elektrotechnik und Informationstechnik > Institut für Automatisierungstechnik und Mechatronik > Control and Cyber-Physical Systems (CCPS)
Hinterlegungsdatum: 19 Okt 2023 10:14
Letzte Änderung: 31 Okt 2023 07:44
PPN: 512782504
Export:
Suche nach Titel in: TUfind oder in Google
Frage zum Eintrag Frage zum Eintrag

Optionen (nur für Redakteure)
Redaktionelle Details anzeigen Redaktionelle Details anzeigen