“Automated drilling algorithms implementation on a laboratory drilling rig”

Authors: Erik Andreas Løken, Jens Løkkevik and Dan Sui,
Affiliation: University of Stavanger
Reference: 2020, Vol 41, No 1, pp. 1-11.

Keywords: Drilling rig, drilling automation, drilling algorithm, drilling optimization

Abstract: Considering the state of art technology that exists today and the significant resources that are being invested into the technology of tomorrow, an idea of intelligent and fully automated machineries working on a drilling floor that is capable of consistently selecting best decisions or predictions based on realtime information available and providing drillers and operators with such recommendations, becomes closer to a reality every day. This work shows results of the research carried out on the topic of drilling automation. Its objectives are to design and test proof of concept technologies conducted on a laboratory-scale autonomous drilling rig developed at University of Stavanger, Norway. Main contribution of the study is on drilling speed (ROP) optimization with considering operational safety to personnel and environment (HSE) and drilling efficiency along with a digitized drilling program for directional drilling. The case studies are presented to show the different scenarios for drilling vertical wells and inclined wells.

PDF PDF (3359 Kb)        DOI: 10.4173/mic.2020.1.1

DOI forward links to this article:
[1] Jingfei Zhang, Haifei Lin, Shugang Li, Erhao Yang, Yang Ding, Yang Bai and Yuxuan Zhou (2022), doi:10.1016/j.jclepro.2022.134372
[2] Zheng Zhou, Yuanbiao Hu, Baolin Liu, Kun Dai and Yudong Zhang (2023), doi:10.3390/app13021059
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  title={{Automated drilling algorithms implementation on a laboratory drilling rig}},
  author={Løken, Erik Andreas and Løkkevik, Jens and Sui, Dan},
  journal={Modeling, Identification and Control},
  publisher={Norwegian Society of Automatic Control}