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Early Kick Detection Using Real-Time Data Analysis With a Lumped Parameter Model

[+] Author Affiliations
M. A. Ojinnaka, J. J. Beaman, S. Fish

University of Texas at Austin, Austin, TX

Paper No. DSCC2016-9931, pp. V001T08A005; 11 pages
  • ASME 2016 Dynamic Systems and Control Conference
  • Volume 1: Advances in Control Design Methods, Nonlinear and Optimal Control, Robotics, and Wind Energy Systems; Aerospace Applications; Assistive and Rehabilitation Robotics; Assistive Robotics; Battery and Oil and Gas Systems; Bioengineering Applications; Biomedical and Neural Systems Modeling, Diagnostics and Healthcare; Control and Monitoring of Vibratory Systems; Diagnostics and Detection; Energy Harvesting; Estimation and Identification; Fuel Cells/Energy Storage; Intelligent Transportation
  • Minneapolis, Minnesota, USA, October 12–14, 2016
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-5069-5
  • Copyright © 2016 by ASME


The risk of kick and lost circulation at the wellbore open-hole increases with water depth due to narrow pressure margins. The safety of drilling operations and mitigation of risk to drilling personnel, equipment, and the environment hinges on the ability of the drilling crew to detect these undesirable events in their early stages and quickly bring the well under control. This paper presents an approach for the estimation of unobserved bottom-hole phenomena during drilling ahead operations by means of combining multiple surface measurements with predictions from a hydraulic model of the well. Bond graph technique is used to formulate a lumped-parameter hydraulic model of the drilling ahead process, the model is linearized, and an estimation method is applied to the proposed stochastic model. This methodology was tested offline with drilling ahead data from a well where a kick occurred and the results showed kick detection earlier than traditional methods allowed.

Copyright © 2016 by ASME



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