Design and analysis of robust controllers for directional drilling tools

Directional drilling is a very important tool for the development of oil and gas deposits. Attitude control which enables directional drilling for the efficient placement of the directional drilling tools in petroleum producing zones is reviewed along with the various engineering requirements or constraints. This thesis explores a multivariable attitude governing plant model as formulated in Panchal et al. (2010) which is used for developing robust control techniques. An inherent input and measurement delay which accounts for the plant's dead-time is included in the design of the controllers. A Smith Predictor controller is developed for reducing the effect of this dead-time. The developed controllers are compared for performance and robustness using structured singular value analysis and also for their performance indicated by the transient response of the closed loop models. Results for the transient non-linear simulation of the proposed controllers are also presented. The results obtained indicate that the objectives are satisfactorily achieved

Path optimization advisory and analytical tools for directional drilling

In directional drilling, well positioning and drilling instructions are planned based on human experiences and may require excessive computation and drilling times. Directional drilling process nowadays lacks optimization and automation to improve performance and efficiency. A path optimization advisor is developed with novel cost analysis, to support real-time directional drilling decisions. Spline in tension is used to simulated drilling path in the path optimization algorithms; more accurate and convenient for optimization purposes than commonly used survey calculation methods. The best valued path is solved using multi-loop optimization process, by determining the path with the lowest accumulated cost. Costs specified for each section are formulated and transformed into equal units. Actual drilling instruction is fitted to the optimal path with consideration of motor tendency and capabilities. The advisor developed using Matlab is validated that such a system can be used in real time directional drilling environments, to provide suggestions. Test cases using simulated drilling situation and historical data are tested for resulting instruction validation. Produced instruction and path results proved to be realistic and optimized based on specified cost functions. Comparing the optimized path with actual drilling instruction and survey drilled in historical cases, plan suggested by the path optimization advisor provides a better valued correction path.Petroleum and Geosystems Engineerin

Deep borehole disposal of nuclear waste: US perspective

Radioactive waste disposal in deep boreholes may be more "ready" than disposal in mined geologic repositories since mankind has greater experience operating small deep holes - boreholes, than big shallow holes - mines. There are several thousand precedents for constructing >2 km deep boreholes and several hundred precedents for disposing long-lived wastes in boreholes. Borehole disposal is likely to be faster, cheaper, and more flexible than mined disposal, while also offering greater long-term isolation. Isolation would rely on the great depth, water density gradients, and reducing conditions to prevent vertical movement of waste up the borehole.Comment: 24 pages, 8 figure

Making risk-informed decisions to optimize drilling operations using along string measurements with Wired drill pipe a high-speed, high-quality telemetry alternative to traditional mud pulse telemetry.

The ever-increasing demand for energy resources has led to drilling more complex and challenging wells. The information required to navigate through these complex geologies is provided by highly sophisticated sensors embedded in logging-while-drilling and measurements-while-drilling downhole tools. These combined with rotary steerable systems have made it possible to drill highly deviated, extended reach, and multilateral wells with high precision. Drilling operations can be considered high-risk operations due to the large number of sources that can lead to undesirable outcomes. Therefore, data transmission from downhole sensors and communication with downhole tools is vital to drill safely and successfully a well. Mud-pulse telemetry is the most used telemetry method to transmit the data from downhole tools to the surface. However, advancements in sensor technology and the development of new tools have resulted in higher amounts of data needed to be transmitted to the surface to take advantage of the resolution they now provide fully. The reliance on mud-pulse telemetry, which offers relatively low data transmission speed and broadband, has been the limiting factor, often sacrificing higher drilling rates to obtain the required data quality. The introduction of wired drill pipe, capable of delivering bi-directional telemetry at speeds up to 10.000 times faster than traditional mud-pulse, has removed the reliance on mud-pulse, making it possible to obtain memory-mode quality real-time data. Wired drill pipe also enables the use of along string measurements. These measurement tools are placed along the string and gather pressure, temperature, and drilling dynamics data. Thus, it is now possible to understand the downhole environment along the wellbore and not just a few meters behind the bit. This makes it possible to timely identify well control and well stability events, thereby making risk-informed decisions to mitigate the risk of hazardous events and additionally optimizing drilling operations. The objective of this thesis is to provide a description of the drilling process and the tools that have made it possible to drill the wells that nowadays are drilled. Further, it describes different telemetry methods but focuses on mud-pulse telemetry and its limitations. Then, the wired drill pipe system is extensively described, and it is presented the way it allows the integration of measurement tools along the string. Furthermore, it is shown how these tools enable making risk-informed decisions to reduce the risk during drilling operations. The result is safer drilling operations to be achieved while also saving time by reducing the telemetry time, preventing tool failures, and avoiding resource-demanding well remediation operations. Finally, it is discussed how the availability of real-time high-quality data and full bi-directional instantaneous communication with downhole tools has enabled a step towards more automated drilling operations. The combination of high-speed data transfer with machine learning and artificial intelligence has made it possible to develop autonomous drilling services capable of optimizing the well path and reducing well times

Online Control and Optimization of Directional Drilling

Directional Steering System (DSS) has been established for well drilling in the oilfield in order to accomplish high reservoir productivity and to improve accessibility of oil reservoirs in complex locations. In this thesis, dynamic modeling of two different DSS were developed and optimized using different control and optimization techniques. Firstly, the Rotary Steerable System (RSS) which is the current state of the art of directional steering systems. In this work, we address the problem of real time control of autonomous RSS with unknown formation friction and rock strength. The work presents an online control scheme for real time optimization of drilling parameters to maximize rate of penetration and minimize the deviation from the planned well bore trajectory, stick-slip oscillations, and bit wear. Nonlinear model for the drilling operation was developed using energy balance equation, where rock specific energy is used to calculate the minimum power required for a given rate of penetration. A proposed mass spring system was used to represent the phenomena of stick-slip oscillation. The bit wear is mathematically represented using Bourgoyne model. Secondly, the autonomous quad-rotor DSS which has 4 downhole motors, is considered. In this work, a novel feedback linearization controller to cancel the nonlinear dynamics of a DSS is proposed. The proposed controller design problem is formulated as an optimization problem for optimal settings of the controller feedback gains. Gravitational Search Algorithm (GSA) is developed to search for optimal settings of the proposed controller. The objective function considered is to minimize the tracking error and drilling efforts. Detailed mathematical formulation and computer simulation were used for evaluation of the performance of the proposed techniques for both systems, based on real well data

Trajectory Control via Reinforcement Learning with RSS Model

Various researchers proposed several types of methods, algorithms, and simulator to control bottom hole assembly (BHA) while drilling a deviated well. These works consist of drilling, control, mechanical and electrical engineering knowledge. The last year at University of Stavanger, Jerez established a work for this purpose. The aim of this work developing a physical method to control bit directions through the well path inside RSS simulator environment. This study structured upon RSS simulator developed at University of Stavanger and propose a different perspective on trajectory control. After a serious struggle on RSS model to shape for reinforcement learning, managed to have a new environment for the trajectory control. This new environment cleaned all possible errors of RSS model. On the other hand, make possible to control path by weight on bit and rotational speed. Also, the observation parameters selected as coordinates, measured depth, and drilling time. Adding tool face angle and dog leg severity values to observation caused bad training for the agents. Afterward, according to discrete observations and actions there was two RL agent options given by MATLAB reinforcement learning toolbox. The first one is proximity policy optimization agent, and the other one is deep q-network agent. After countless training sessions on J shape well, managed to create significant reward functions to test the environment on different well shapes. First try made on J shape well with both RL agents offered by MATLAB and results were satisfactory. However, simulations attempt for S and complex shape wells were not precise and needs more development. Therefore, utilization of RL environment, reward function and optimization of time demand became crucial outputs of these attempts

Анализ работы роторно-управляемых систем в различных геолого-технических условиях

Объект исследования. Роторно-управляемые системы. Цель работы. Выявить наиболее эффективную роторно-управляемую систему для различных геолого-технических условий. Результаты исследования. Основным результатом исследовательской работы является выявление наиболее эффективной РУС и получение проранжированного перечня роторно-управляемых систем для различных геолого-технических условий. Сопутствующим результатом является разработка способа оценки роторно-управляемых систем. Методы проведения исследования. Был проведен сбор данных по рынку и работе роторно-управляемых систем, а затем выполнен сравнительный и морфологический анализ полученных данных в табличном виде. Область применения. Технологии наклонно-направленного бурения.Object of research. Rotary steerable systems. Purpose of work. Identify the most effective rotary steerable system for various geological and technical conditions. Research result. The main result of the research work is to identify the most effective RSS and obtain a ranked list of rotary steerable systems for various geological and technical conditions. A related result is the development of a method for evaluating rotary-controlled systems. Methods of conducting research. Data was collected on the market and operation of rotary steerable systems, and then a comparative and morphological analysis of the data obtained in tabular form was performed. Application. Technologies of directional drilling

Trajectory Control Optimization Using the RSS Model

Master's thesis in Petroleum EngineeringDirectional drilling has become a standard method to drill a well since the last decades, mainly caused by directional technologies and methods developments. The next step that the drilling industry is ready to take is to increase its automation levels to reduce their cost and increase the safe environment for field crews. Moreover, the use of computers has allowed the creation of virtual tools that help drilling staffs visualize and foresee the issues and advantages through different phases from planning to post-analysis. Therefore, the present MSc thesis work focuses on developing a new approach (an in-house directional drilling simulator) to automatically and precisely estimate and control bit positions in real time. This simulator is called Rotary Steerable System (RSS) Simulator and is based on the Trajectory Control Optimizer (TCO) and the RSS Model. The TCO was developed to plan the optimal trajectory, set the simulation targets, detect the bit deviations and create a correction path to return to the planned trajectory. Each of those processes is fulfilled without any human interaction during the simulation. The second element makes the simulation’s calculations on physics including Newton’s third law, beam bending analysis, bit force analysis, rate of penetration (ROP) to determine the bit position and then conduct RSS control to steer the bit accordingly. Such model is an upgraded version of the RSS Model developed by the University of Stavanger in 2020. Besides, the RSS Simulator is a new tool that could interact with external models to interchange data and generate simulations closer to reality according to the factors involved. Furthermore, the simulator considers some uncertainty analysis and adds some noises (systematic and random) to the input data to give a more realistic behaviour to the results. Thus, the RSS Simulator is the potential tool that might help the drilling industry walk towards automating most of its processes in the future