38 research outputs found
Real time kick estimation and monitoring in managed pressure drilling system
The influx of reservoir fluid (kick) has a significant impact on drilling operations. Unmitigated kick can lead to a blowout causing financial losses and impacting human lives on the rig. Kick is an unmeasured disturbance in the system, and so detection, estimation, and mitigation are essential for the safety and efficiency of the drilling operation. Our main objective is to develop a real time warning system for a managed pressure drilling (MPD) system. In the first part of the research, an unscented Kalman filter (UKF) based estimator was implemented to simultaneously estimate the bit flow-rate, and kick. The estimated kick is further used to predict the impact of the kick. Optimal control theory is used to calculate the time to mitigate the kick in the best case scenario. An alarm system is developed based on total predicted influx and pressure rise in the system and compared with actual well operation control matrix. Thus, the proposed method can estimate, monitor, and manage kick in real time, enhancing the safety and efficiency of the MPD operation. So, a robust warning framework for the operators based on real life operational conditions is created in the second part of the research. Proposed frameworks are successfully validated by applying to several case studies
Design, development and control of a managed pressure drilling setup
Drilling in challenging conditions require precise control over hydrodynamic parameters
for safer and efficient operation in oil and gas industries. Automated managed
pressure drilling (MPD) is one of such drilling solution which helps to maintain operational
parameters effectively over conventional drilling technique. The main goal
is to maintain bottomhole pressure between reservoir formation pressure and fracture
pressure with kick mitigation ability. Real life MPD system has to confront nonlinearity
induced by drilling fluid rheology and flow parameters. To obtain a better
understanding of this operation, a lab scale experimental setup has been developed.
Reynolds number and pressure drop per unit length were considered to obtain hydrodynamic
similarity. A vertical concentric pipe arrangement has been used to represent
the drill string and annular casing region. A linearized gain switching proportional integral
(PI) controller and a nonlinear model predictive controller (NMPC) have been
developed to automate the control operation in the experimental setup. A linearizer
has been designed to address the choke nonlinearity. Based on the flow and pressure
criteria, a gain switching PI controller has been developed which is able to control
pressure and flow conditions during pipe extension, pump failure and influx attenuation
cases. On the other hand, a nonlinear Hammerstein-Weiner model has been
developed which assists in bottomhole pressure estimation using pump flow rate and
choke opening. The identified model has been integrated with a NMPC algorithm
to achieve effective control within predefined pressure and flow constraints. Lastly, a
performance comparison has been provided between the linearized gain switching PI
controller and NMPC controller
Advanced control of managed pressure drilling
Automation of managed pressure drilling (MPD) enhances the safety and increases
efficiency of drilling and that drives the development of controllers and observers
for MPD. The objective is to maintain the bottom hole pressure (BHP) within the
pressure window formed by the reservoir pressure and fracture pressure and also to
reject kicks. Practical MPD automation solutions must address the nonlinearities
and uncertainties caused by the variations in mud flow rate, choke opening, friction
factor, mud density, etc. It is also desired that if pressure constraints are violated the
controller must take appropriate actions to reject the ensuing kick. The objectives
are addressed by developing two controllers: a gain switching robust controller and a
nonlinear model predictive controller (NMPC). The robust gain switching controller
is designed using H1 loop shaping technique, which was implemented using high gain
bumpless transfer and 2D look up table. Six candidate controllers were designed in
such a way they preserve robustness and performance for different choke openings and
flow rates. It is demonstrated that uniform performance is maintained under different
operating conditions and the controllers are able to reject kicks using pressure control
and maintain BHP during drill pipe extension. The NMPC was designed to regulate
the BHP and contain the outlet flow rate within certain tunable threshold. The
important feature of that controller is that it can reject kicks without requiring any
switching and thus there is no scope for shattering due to switching between pressure
and flow control. That is achieved by exploiting the constraint handling capability of
NMPC. Active set method was used for computing control inputs. It is demonstrated
that NMPC is able to contain kicks and maintain BHP during drill pipe extension
Safety and reliability assessment of managed pressure drilling in well control operations
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 â 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
Incident detection and isolation in drilling using analytical redundancy relations
Early diagnosis of incidents that could delay or endanger a drilling operation for oil or gas is essential to limit field development costs. Warnings about downhole incidents should come early enough to allow intervention before it develops to a threat, but this is difficult, since false alarms must be avoided. This paper employs model-based diagnosis using analytical redundancy relations to obtain residuals which are affected differently by the different incidents. Residuals are found to be non-Gaussian - they follow a multivariate -distribution - hence, a dedicated generalized likelihood ratio test is applied for change detection. Data from a 1400 meter horizontal flow loop test facility is used to assess the diagnosis method.
Diagnosis properties of the method are investigated assuming either with available downhole pressure sensors through wired drill pipe or with only topside measurements available. In the latter case, isolation capability is shown to be reduced to group-wise isolation, but the method would still detect all serious events with the prescribed false alarm probability
Evaluation of the âCommand Take-Over Procedureâ in automated well control
The growing need for new technology in the pursuit of oil is creating new challenges
related to well control. Drilling in HPHT (High Pressure High Temperature)
reservoirs, arctic areas, and depleted zones might imply that the drilling window
between the pore pressure and the fracturing pressure is narrow. This presents
challenges in terms of gas influx. As of today kick handling is a manual procedure
with the driller in charge.
Automation of well control procedures can be the solution to several problems related
to kick detection and kick handling. This thesis introduces theory about conventional
well control as well as control theory and automated well control. A part of the work
was experimental, and was performed at a simplified rig model at the two-phase
laboratory at the University of Stavanger. The results are presented in chapter 6.
The main focus in the experimental part is on the Command Take-over procedure.
Several experiments were performed leading to the main experiment. The main
principle of this procedure is that the drilling operation is run in MPD (Managed
Pressure Drilling) mode with a PI-controller (Proportional Integral controller) on the
MPD valve. When a gas kick occurs, the WCV (Well Control Valve) mode is
activated with a PI-controller on the WCV. Further the BOP (Blow Out Preventer) is
closed and the kick is circulated out of the well through the WCV. After the
circulation, the operation is back to MPD mode, and the operation continues as
planned.
The results show that the Command Take-Over Procedure is feasible on actual
drilling rigs. It is further possible to assume that the procedure is safer, because the
procedure is automated, without the dependence of human judgement and ability to
make good decisions in well control incidents. However, it is important to have a
drilling crew available on the rig in case of mechanical failure. The procedure is also
more efficient and time saving since the pump are constantly running during the
procedure, and there might not be a need for a new mud with higher density to regain
well control after a gas kick
Multiphase flow modelling for enhanced oil and gas drilling and production
From the exploration to the abandonment of an oil and gas discovery, operators and engineers are constantly faced with the challenge of achieving the best commercial potential of oil fields. Although the petroleum engineering community has significantly contributed towards maximising the potential of discovered prospects, the approach adopted so far has been compartmentalised with little (heuristics-based) or no quality integration. The highly interconnected nature of the decision factors affecting the management of any field requires increased implementation of Computer-Aided Process Engineering (CAPE) methods, thus presenting a task for which chemical engineers have the background to make useful contributions. Drilling and production are the two primary challenging operations of oilfield activities, which span through different time horizons with both fast and slow-paced dynamics. These attributes of these systems make the application of modelling, simulation, and optimisation tasks difficult. This PhD project aims to improve field planning and development decisions from a Process Systems Engineering (PSE) perspective via numerical (fluid dynamics) simulations and modelbased deterministic optimisation of drilling and production operations, respectively. Also demonstrated in this work is the importance of deterministic optimisation as a reliable alternative to classical heuristic methods. From a drilling operation perspective, this project focuses on the application of Computational Fluid Dynamics (CFD) as a tool to understand the intricacies of cuttings transport (during wellbore cleaning) with drilling fluids of non-Newtonian rheology. Simulations of two-phase solid-liquid flows in an annular domain are carried out, with a detailed analysis on the impact of several drilling parameters (drill pipe eccentricity, inclination angle, drill pipe rotation, bit penetration rate, fluid rheology, and particle properties) on the cuttings concentration, pressure drop profiles, axial fluid, and solid velocities. The influence of the flow regime (laminar and turbulent) on cuttings transport efficiency is also examined using the Eulerian-Eulerian and Lagrangian-Eulerian modelling methods. With experimentally validated simulations, this aspect of the PhD project provides new understanding on the interdependence of these parameters; thus facilitating industrial wellbore cleaning operations. The second part of this project applies mathematical optimisation techniques via reduced-order modelling strategies for the enhancement of petroleum recovery under complex constraints that characterise production operations. The motivation for this aspect of the project stems from the observation that previous PSE-based contributions aimed at enhancing field profitability, often apply over-simplifications of the actual process or neglect some key performance indices due to problem complexity. However, this project focuses on a more detailed computational integration and optimisation of the models describing the whole field development process from the reservoir to the surface facilities to ensure optimal field operations. Nonlinear Programs (NLPs), Mixed-Integer Linear Programs (MILPs), and Mixed-Integer Nonlinear Programs (MINLPs) are formulated for this purpose and solved using high-fidelity simulators and algorithms in open-source and commercial solvers. Compared to previous studies, more flow physics are incorporated and rapid computations obtained, thus enabling real-time decision support for enhanced production in the oil and gas industry
Dynamic Simulation of Dual Gradient Drilling Operation using the Finite Element Method
The deepwater and ultra-deepwater drilling industry has created several techniques to overcome the Well-Control challenge in these scenarios. Dual Gradient Drilling is one of those techniques.
Created in the mid-90âs the technique is relatively new and it is not fully integrated at the market yet. The main concept it is to use a lighter fluid on top of a heavier fluid inside the wellbore and marine riser, which allows the engineer a better control of bottomhole pressure.
This work is focused on understand the fluid dynamics of a Dual Gradient Drilling operation. It uses the conservation equation along with the previous proposed density and rheological model to investigate how mud weight, thermal properties and well configuration affect the pressure and temperature profile. The system of equation is discretized using Finite Element Methods and the code implemented in MatlabÂŽ.
The results demonstrated the importance of an accurate density model and its consideration during the development of the well plan. A sensitivity analysis shows the effects of the Overall Heat Transfer Coefficient over the temperature profile, proving that it is the major parameter controlling the heat exchange in the drilling process