Bottom hole pressure estimation and ℒ1 adaptive control in managed pressure drilling system

Zhiyuan Li, Naira Hovakimyan, Glenn Ole Kaasa

Research output: Contribution to journalArticlepeer-review


In the past decade, managed pressure drilling, a technology aiming at precise well pressure control, has been gaining increasing popularity and been a key enabler for some of the most challenging well drilling cases such as the offshore deep water well drilling. This paper attempts to solve two of the main challenges involved in the managed pressure drilling systems: first, the bottom-hole states measurements are updated at a low rate, which can be practically viewed as unmeasured and thus need to be estimated in real time for both monitoring and control purposes and second, the drilling process is subject to uncertainties including unknown system parameters (e.g., frictions and densities), unmodeled actuator dynamics, and noise, which require a robust adaptive controller for control of the bottom-hole pressure. Towards this objective, an integrated estimator and L1 adaptive control scheme is proposed. The estimator provides estimation of the bottom-hole pressure and flow rate, based on the available measurements from the topside. The L1 adaptive controller drives the bottom-hole pressure to the desired value following a reference model, which also handles the time delays in the input signal. The design is based on a recently developed nonlinear drilling model. The results demonstrate that the L1 adaptive controller has guaranteed performance bounds for both the input and the output signals of the system while using the estimation of the regulated outputs. Simulation results covering different operational conditions verify the theoretical findings.

Original languageEnglish (US)
Pages (from-to)545-561
Number of pages17
JournalInternational Journal of Adaptive Control and Signal Processing
Issue number4
StatePublished - Apr 2017


  • adaptive control
  • bottom-hole pressure estimation
  • managed pressure drilling

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Signal Processing
  • Electrical and Electronic Engineering


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