Safety and reliability assessment of managed pressure drilling in well control operations

Sule, Idris Olusola (2019) Safety and reliability assessment of managed pressure drilling in well control operations. Doctoral (PhD) thesis, Memorial University of Newfoundland.

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Managed pressure drilling (MPD) is a technique utilized in drilling to manage annular pressure, hold reservoir influx, and divert mud returns away safely from the rig floor through a closed loop system. Thus, MPD plays key roles in well control operations and in drilling deepwater wells. However, despite the operational, safety, and economic benefits, limited information is available on understanding the complexity of MPD system. Furthermore, the oil and gas industry currently relies on a flow monitoring system for earlier kick detection but faces severe flaws and limited progress has been made on approach that monitors kick from downhole due to the complexity of offshore drilling operations. Thus, the main objective of this research is to assess the safety and reliability of MPD. In this research, following novel contributions have been made: several dynamic downhole drilling parameters have been identified to enhance earlier kick detection technique during drilling, including about 33 – 89% damping of bit-rock vibrations due to gas kick; a reliability assessment model has been developed to estimate the failure probability of an MPD system as 5.74%, the assess the increase in reliability of kick control operation increases from 94% to 97% due to structural modification of the MPD components, identify that MPD operational failure modes are non-sequential, and identify that an MPD control system is the most safety-critical components in an MPD system; an automated MPD control model, which implements a nonlinear model predictive controller (NMPC) and a two-phase hydraulic flow model, has been developed to perform numerical simulations of an MPD operation; and lastly, an integrated dynamic blowout risk model (DBRM) to assess the safety during an MPD operation has been developed and its operation involves three key steps: a dynamic Bayesian network (DBN) model, a numerical simulation of an MPD control operation, and dynamic risk analysis to assess the safety of the well control operation as drilling conditions change over time. The DBRM also implemented novel kick control variables to assess the success / failure of an MPD operation, i.e. its safety, and are instrumental in providing useful information to predict the performance of / diagnose the failure of an MPD operation and has been successfully applied to replicate the dynamic risk of blowout risk scenarios presented in an MPD operation at the Amberjack field case study from the Gulf of Mexico.

Item Type: Thesis (Doctoral (PhD))
Item ID: 13956
Additional Information: Includes bibliographical references (pages 172-187).
Keywords: Kick indicators, Dynamic Bayesian Network, MPD, Reliability, NMPC, automation, Pressure control, Flow control, Blowout, drilling
Department(s): Engineering and Applied Science, Faculty of
Date: July 2019
Date Type: Submission
Library of Congress Subject Heading: Managed pressure drilling (Petroleum engineering)--Risk assessment; Managed pressure drilling (Petroleum engineering)--Mathematical models

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