Managed Pressure Drilling now at the pinnacle of the 'Oil Well Drilling' evolution tree, has itself been coined in 2003. It is an umbrella term for a few new drilling techniques and some preexisting drilling techniques, all of them aiming to solve several drilling problems, including non-productive time and/or drilling flat time issues. These techniques, now sub-classifications of Managed Pressure Drilling, are referred to as 'Variations' and 'Methods' of Managed Pressure Drilling. Although using Managed Pressure Drilling for drilling wells has several benefits, not all wells that seem a potential candidate for Managed Pressure Drilling, need Managed Pressure Drilling. The drilling industry has numerous simulators and software models to perform drilling hydraulics calculations and simulations. Most of them are designed for conventional well hydraulics, while some can perform Underbalanced Drilling calculations, and a select few can perform Managed Pressure Drilling calculations. Most of the few available Managed Pressure Drilling models are modified Underbalanced Drilling versions that fit Managed Pressure Drilling needs. However, none of them focus on Managed Pressure Drilling and its candidate selection alone. An 'Managed Pressure Drilling Candidate Selection Model and software' that can act as a preliminary screen to determine the utility of Managed Pressure Drilling for potential candidate wells are developed as a part of this research dissertation. The model and a flow diagram identify the key steps in candidate selection. The software performs the basic hydraulic calculations and provides useful results in the form of tables, plots and graphs that would help in making better engineering decisions. An additional Managed Pressure Drilling worldwide wells database with basic information on a few Managed Pressure Drilling projects has also been compiled that can act as a basic guide on the Managed Pressure Drilling variation and project frequencies and aid in Managed Pressure Drilling candidate selection.

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.

Increasing worldwide demand for petroleum motivates greater efficiency, safety, and environmental responsibility in upstream oil and gas processes. The objective of this research is to improve these areas with advanced control methods. This work develops the integration of optimal control methods including model predictive control, moving horizon estimation, high fidelity simulators, and switched control techniques applied to subsea riser slugging and managed pressure drilling. A subsea riser slugging model predictive controller eliminates persistent offset and decreases settling time by 5% compared to a traditional PID controller. A sensitivity analysis shows the effect of riser base pressure sensor location on controller response. A review of current crude oil pipeline wax deposition prevention, monitoring, and remediation techniques is given. Also, industrially relevant control model parameter estimation techniques are reviewed and heuristics are developed for gain and time constant estimates for single input/single output systems. The analysis indicates that overestimated controller gain and underestimated controller time constant leads to better controller performance under model parameter uncertainty. An online method for giving statistical significance to control model parameter estimates is presented. Additionally, basic and advanced switched model predictive control schemes are presented. Both algorithms use control models of varying fidelity: a high fidelity process model, a reduced order nonlinear model, and a linear empirical model. The basic switched structure introduces a method for bumpless switching between control models in a predetermined switching order. The advanced switched controller builds on the basic controller; however, instead of a predetermined switching sequence, the advanced algorithm uses the linear empirical controller when possible. When controller performance becomes unacceptable, the algorithm implements the low order model to control the process while the high fidelity model generates simulated data which is used to estimate the empirical model parameters. Once this online model identification process is complete, the controller reinstates the empirical model to control the process. This control framework allows the more accurate, yet computationally expensive, predictive capabilities of the high fidelity simulator to be incorporated into the locally accurate linear empirical model while still maintaining convergence guarantees.

Subsea development and production of hydrocarbons is challenging due to remote andharsh conditions. Recent technology development with high speed communication to subsea anddownhole equipment has created a new opportunity to both monitor and control abnormal or undesirableevents with a proactive and preventative approach rather than a reactive approach. Twospecific technology developments are high speed, long-distance fiber optic sensing for productionand completion systems and wired pipe for drilling communications. Both of these communicationsystems offer unprecedented high speed and accurate sensing of equipment and processes that aresusceptible to uncontrolled well situations, leaks, issues with flow assurance, structural integrity,and platform stability, as well as other critical monitoring and control issues. The scope of thisdissertation is to design monitoring and control systems with new theoretical developments andpractical applications. For estimators, a novel `1-norm method is proposed that is less sensitiveto data with outliers, noise, and drift in recovering the true value of unmeasured parameters. Forcontrollers, a similar `1-norm strategy is used to design optimal control strategies that utilize a comprehensivedesign with multivariate control and nonlinear dynamic optimization. A framework forsolving large scale dynamic optimization problems with differential and algebraic equations is detailedfor estimation and control. A first area of application is in fiber optic sensing and automationfor subsea equipment. A post-installable fiber optic clamp is used to transmit structural informationfor a tension leg platform. A proposed controller automatically performs ballast operationsthat both stabilize the floating structure and minimize fatigue damage to the tendons that hold thestructure in place. A second area of application is with managed pressure drilling with movinghorizon estimation and nonlinear model predictive control. The purpose of this application is tomaximize rate of drilling penetration, maintain pressure in the borehole, respond to unexpected gasinflux, detect cuttings loading and pack-off, and better manage abnormal events with the drillingprocess through automation. The benefit of high speed data accessibility is quantified as well asthe potential benefit from a combined control strategy versus separate controllers.

The supply and demand situation is crucial for the oil and gas industry during the first half of the 21st century. For the future, we will see two trends going in opposite directions: a decline in discoveries of conventional oil and gas reservoirs and an increase in world energy demand. Therefore, the need to develop and produce unconventional oil and gas resources, which encompass coal-bed methane, gas-shale, tight sands and heavy oil, will be of utmost importance in the coming decades. In the past, large-scale production from tight gas reservoirs occurred only in the U.S. and was boosted by both price incentives and well stimulation technology. A conservative study from Rogner (1997) has shown that tight gas sandstone reservoirs would represent at least over 7,000 trillion cubic feet (Tcf) of natural gas in place worldwide. However, most of the studies such as the ones by the U.S. Geological Survey (U.S.G.S.) and Kuuskraa have focused on assessing the technically recoverable gas resources in the U.S. with numbers ranging between 177 Tcf and 379 Tcf. During the past few decades, gas production from tight sands field developments have taken place all around the world from South America (Argentina), Australia, Asia (China, Indonesia), the Russian Federation, Northern Europe (Germany, Norway) and the Middle East (Oman). However, the U.S. remains the region where the most extensive exploration and production for unconventional gas resources occur. In fact, unconventional gas formations accounted for 43% of natural gas production and tight gas sandstones represented 66% of the total of unconventional resources produced in the U.S. in 2006. As compared to a conventional gas well, a tight gas well will have a very low productivity index and a small drainage area. Therefore, to extract the same amount of natural gas out of the reservoir, many more wells will have to be drilled and stimulated to efficiently develop and produce these reservoirs. Thus, the risk involved is much higher than the development of conventional gas resources and the economics of developing most tight gas reservoirs borders on the margin of profitability. To develop tight gas reservoirs, engineers face complex problems because there is no typical tight gas field. In reality, a wide range of geological and reservoir differences exist for these formations. For instance, a tight gas sandstone reservoir can be shallow or deep, low or high pressure, low or high temperature, bearing continuous (blanket) or lenticular shaped bodies, being naturally fractured, single or multi-layered, and holding contaminants such as CO2 and H2S which all combined increase considerably the complexity of how to drill a well. Since the first tight gas wells were drilled in the 1940's in the U.S., a considerable amount of information has been collected and documented within the industry literature. The main objective of this research project is to develop a computer program dedicated to applying the drilling technologies and methods selection for drilling tight gas sandstone formations that have been documented as best practices in the petroleum literature.

In the most of the drilling operations it is obvious that a considerable amount of money is spent for drilling related problems / including stuck pipe, lost circulation, and excessive mud cost. In order to decrease the percentage of non-productive time (NPT) caused by these kind of problems, the aim is to control annular frictional pressure losses especially in the fields where pore pressure and fracture pressure gradient is too close which is called narrow drilling window. If we can solve these problems, the budget spent for drilling the wells will fall, therefore enabling the industry to be able to drill wells that were previously uneconomical. Managed Pressure Drilling (MPD) is a new technology that allows us to overcome these kinds of drilling problems by controlling the annular frictional pressure losses. As the industry remains relatively unaware of the full spectrum of benefits, this thesis involves the techniques used in Managed Pressure Drilling with an emphasis upon revealing several of its lesser known and therefore less appreciated applications.