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The upstream oil and gas industry has witnessed a marked increase in the number of wells drilled in areas with elevated subsurface formation pressures and narrow drilling margins. Managed Pressure Drilling (MPD) techniques have been developed to deal with the challenge of narrow margin wells, offering great promise for improved rig safety and reduced non-productive time. Automation of MPD operations can ensure improved control over wellbore pressure profiles, and there are several commercial solutions currently available. However, these automation efforts seldom take into account the uncertainty and complex dynamics inherent in subsurface environments, and usually assume ideally functioning sensors and actuators, which is rarely the case in real-world drilling operations. This dissertation describes a set of tools and methods that can form the basis for an automation framework for MPD systems, with specific focus on the surface back-pressure technique of MPD. Model-based control algorithms with robust reference tracking, as well as methods for detecting system faults and handling modeling uncertainty, are integrated with a novel multi-phase hydraulics model. The control system and event detection modules are designed using physics-based representations of the drilling processes, as well as models relating uncertain variables in a probabilistic fashion. Validation on high-fidelity simulation models is conducted in order to ascertain the effectiveness of the developed methods.
If done properly, MPD can improve economics for any well being drilled by reducing a rig's nonproductive time. Written for engineers, drilling managers, design departments, and operations personnel, Managed Pressure Drilling Modeling is based on the author's on experience and offers instruction on planning, designing and executing MPD projects. Compact and readable, the book provides a step by step methods for understanding and solve problems involving variables such as backpressure, variable fluid density, fluid rheology, circulating friction, hole geometry and drillstring diameter. All MPD variations are covered, including Constant Bottomhole Pressure, Pressurized MudCap Drilling and Dual Gradient Drilling. Case histories from actual projects are designed and analyzed using proprietary simulation software online.
With extraction out of depleted wells more important than ever, this new and developing technology is literally changing drilling engineering for future generations. Never before published in book form, these cutting-edge technologies and the processes that surround them are explained in easy-tounderstand language, complete with worked examples, problems and solutions. This volume is invaluable as a textbook for both the engineering student and the veteran engineer who needs to keep up with changing technology.
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.
Managed Pressure Drilling (MPD) is a modified drilling process designed to accurately manage the annular pressures of the wellbore with a combination of surface back pressure (SBP), flow rate and drilling mud density. MPD is designed to identify and circulate out kicks (uncontrolled flow of formation fluids into the wellbore) that possess blowout risk. Since MPD allows fast changes in the bottom hole pressure, the reaction to an undesirable inflow is not automatically to shut in the well and increase the density of the mud which is the well control procedure in conventional drilling. This feature of MPD can aid in lowering the non-productive time (NPT) as well as drilling related problems such as stuck pipe that results from well control operations. The objective of this research is to compare and evaluate the current conventional and MPD well control methods for gas kicks in a deepwater well. A total of seven well control methods are chosen from literature and subjected to an effectiveness criterion such as total time to control and circulate the kick, maximum pressures imposed on surface equipment and whether each well control method resulted in fracturing the formation at the casing shoe. Two different kick volumes (2 bbl and 10 bbl) with two different values of formation permeability (10 mD and 500 mD) and three different kick intensities (0.1 ppge, 0.5 ppge, 1.0 ppge) are chosen for kick scenarios in this study. The kick scenarios are selected to resemble realistic events that occur during drilling operations. In this study, only kicks resulting from drilling into a higher-pressure zone than expected are subjected to analysis. DrillbenchTM Dynamic Well Control simulator, is used in this research. A model validation, in terms of drilling hydraulics and rising gas velocities in the annuli, is included in this study to verify the reliability of the software's output. The validation is carried out using analytical relations and experimental correlations obtained from literature. The Bingham Plastic fluid model is used in the drilling hydraulics validation and the correlations suggested by Caetano (1985) and Hassan and Kabir (1992) are used for the verification of rising gas velocity in the annular space. In general, validation results show a reasonable agreement with the software's output. The results of 84 simulations showed that in the scenarios with low permeability, with both kick volumes and with the three different kick intensities, MPD well control methods were able to reduce the total well control time by more than 50% compared to the driller's method. ii Furthermore, in the same scenarios with high permeability, the MPD methods outperformed the driller's method in terms of time to stop the kick as well as maximum pressures imposed on surface equipment. The MPD well control method that combines Qin-SBP increments shows to have better results in terms of the total time to control and circulate the kick as well as lower imposed pressures in the casing shoe and surface equipment. This study can be used as a basis for further research in well control with MPD, with more attention to the method of combining Qin-SBP to stop the kick. Finally, this research can be used as a guide to determine the best combination of well control practices for wells with similar characteristics of the well studied in this thesis.
The exploration and development of oil and gas reserves located in harsh offshore environments are characterized with high risk. Some of these reserves would be uneconomical if produced using conventional drilling technology due to increased drilling problems and prolonged non-productive time. Seeking new ways to reduce drilling cost and minimize risks has led to the development of Managed Pressure Drilling techniques. Managed pressure drilling methods address the drawbacks of conventional overbalanced and underbalanced drilling techniques. As managed pressure drilling techniques are evolving, there are many unanswered questions related to safety and operating pressure regimes. Quantitative risk assessment techniques are often used to answer these questions. Quantitative risk assessment is conducted for the various stages of drilling operations - drilling ahead, tripping operation, casing and cementing. A diagnostic model for analyzing the rotating control device, the main component of managed pressure drilling techniques, is also studied. The logic concept of Noisy-OR is explored to capture the unique relationship between casing and cementing operations in leading to well integrity failure as well as its usage to model the critical components of constant bottom-hole pressure drilling technique of managed pressure drilling during tripping operation. Relevant safety functions and inherent safety principles are utilized to improve well integrity operations. Loss function modelling approach to enable dynamic consequence analysis is adopted to study blowout risk for real-time decision making. The aggregation of the blowout loss categories, comprising: production, asset, human health, environmental response and reputation losses leads to risk estimation using dynamically determined probability of occurrence. Lastly, various sub-models developed for the stages/sub-operations of drilling operations and the consequence modelling approach are integrated for a holistic risk analysis of drilling operations.
The world’s energy demand has been rapidly increasing and is projected to continue growing for at least the next two decades. With increasing global energy demand and competition from renewable energy, the oil and gas industry is striving for more efficient petroleum production. Many technical breakthroughs have enabled the drilling industry to expand the exploration to more difficult drilling such as deepwater drilling and multilateral directional drilling. For example, managed pressure drilling (MPD) offers ceaseless operation with multiple manipulated variables (MV) and wired drill pipe (WDP) provides two-way, high-speed measurements from bottom hole and along-string sensors. These technologies have maximum benefit when applied in an automation system or as a real-time advisory tool. The objective of this study is to investigate the benefit of nonlinear model-based control and estimation algorithms with various types of models. This work presents a new simplified flow model (SFM) for bottomhole pressure (BHP) regulation in MPD operations. The SFM is embedded into model-based control and estimation algorithms that use model predictive control (MPC) and moving horizon estimation (MHE), respectively. This work also presents a new Hammerstein-Wiener nonlinear model predictive controller for BHP regulation. Hammerstein-Wiener models employ input and output static nonlinear blocks before and after linear dynamics blocks to simplify the controller design. The control performance of the new Hammerstein-Wiener nonlinear controller is superior to conventional PID controllers in a variety of drilling scenarios. Conventional controllers show severe limitations in MPD because of the interconnected multivariable and nonlinear nature of drilling operations. BHP control performance is evaluated in scenarios such as drilling, pipe connection, kick attenuation, and mud density displacement and the efficacy of the SFM and Hammerstein-Wiener models is tested in various control schemes applicable to both WDP and mud pulse systems. Trusted high-fidelity drilling simulators are used to simulate well conditions and are used to evaluate the performance of the controllers using the SFM and Hammerstein-Wiener models. The comparison between non- WDP (semi-closed loop) and WDP (full-closed loop) applications validates the accuracy of the SFM under the set of conditions tested and confirms comparability with model-based control and estimation algorithms. The SFM MPC maintains the BHP within 1 bar of the setpoint for each investigated scenario, including for pipe connection and mud density displacement procedures that experience a wider operation range than normal drilling.
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.
Managed Pressure Drilling Operations is a significant technology worldwide and beginning to make an impact all over the world. Often reservoir and drilling engineers are faced with the decision on how best to construct a well to exploit zones of interest while seeking to avoid drilling problems that contribute to reservoir damage or cause loss of hole. The decision to pursue a MPD operation is based on the intent of applying the most appropriate technology for the candidate and entails either an acceptance of influx to the surface or avoidance of influx into the wellbore. In today's exploration and production environment, drillers must now drill deeper, faster and into increasingly harsher environments where using conventional methods could be counter-productive at best and impossible at worst. Managed Pressure Drilling (MPD) is rapidly gaining popularity as a way to mitigate risks and costs associated with drilling in harsh environments. With this book in hand drilling professionals gain knowledge of the various variations involved in managed pressure drilling operations; understand the safety and operational aspects of a managed pressure drilling project; and be able to make an informed selection of all equipment required to carry out a managed pressure drilling operation.