Rate of penetration (ROP) optimization in drilling with vibration control
作者: Chiranth HegdeHarry MillwaterMichael PyrczHugh DaigleKen Gray
作者单位: 1Hildebrand Department of Petroleum and Geosystems Engineering, The University of Texas, Austin, USA
2Department of Mechanical Engineering, The University of Texas at San Antonio, USA
刊名: Journal of Natural Gas Science and Engineering, 2019, Vol.67 , pp.71-81
来源数据库: Elsevier Journal
DOI: 10.1016/j.jngse.2019.04.017
关键词: ROPMachine learningDrillingOptimizationData analytics
原始语种摘要: Abstract(#br)Drilling optimization is typically tackled by optimizing the rate of penetration (ROP). However, most ROP optimization models do not consider the effect of drilling vibrations, a major ROP inhibitor. To resolve this limitation, this paper introduces a workflow that combines the ROP optimization process with a machine learning-based vibration model. This model determines optimal drilling parameters that not only increase ROP but mitigate excessive vibrations. Analytical ROP models are used to model the ROP in a given formation. An optimization algorithm (gradient ascent with random restarts) is used to find the optimal drilling control parameters, weight on bit (WOB) and revolutions per minute (RPM), required to improve ROP ahead of the bit. The vibrations classification model...
全文获取路径: Elsevier  (合作)

  • penetration 穿透
  • ROP Organic Peroxide
  • optimization 最佳化
  • drilling 钻进
  • vibration 振荡
  • control 控制