Orientador: Gabriel Alves da Costa Lima / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica e Instituto de Geociências / Made available in DSpace on 2018-08-18T06:55:19Z (GMT). No. of bitstreams: 1 Guimaraes_BrunnoRodrigues_M.pdf: 3690412 bytes, checksum: 215a44334a505aed1642d1450eb2097c (MD5) Previous issue date: 2011 / Resumo: O problema de estimativa de tempo para perfuração de poços de petróleo é um desafio importante para os tomadores de decisão porque envolve alocação de recursos físicos (sondas, equipes de operadores etc.) e custos. Por isso, o desenvolvimento de ferramentas que forneçam informações pode contribuir para a tomada de decisões no sentido de agregar valor. Neste trabalho desenvolve-se uma abordagem probabilística para realizar estimativas do tempo para perfuração de poços de petróleo utilizando-se o método de Monte Carlo. Esta consiste em modelar a sequência lógica de atividades (manobra, cimentação, perfuração etc.) que compõem a perfuração de um poço. Tal sequência é composta de atividades que devem ser realizadas consecutivamente e também de outras que podem ser executadas paralelamente. Depois, são inseridas informações na forma de distribuições de probabilidade que são usadas na modelagem da variável aleatória tempo para completar cada uma das operações da perfuração, as quais são selecionadas a partir de dados históricos de tempos de poços realizados em situações semelhantes. Ao empregar simulação de Monte Carlo juntamente com o modelo proposto pode-se obter uma estimativa da distribuição de probabilidade do tempo total para perfurar determinado poço. Desta forma, podem-se obter respostas a perguntas diversas, tais como: 1) Qual é o tempo médio (mais provável) de perfuração do poço?; 2) Qual a probabilidade de que o tempo real seja X% superior ao valor esperado?; 3) Qual a probabilidade de que ocorram atrasos nas duas últimas fases?; 4) Caso a duração das fases concluídas seja diferente do esperado, qual a probabilidade de que o tempo total de perfuração ainda se encontre dentro do planejado?; 5) etc. Adicionalmente, incorpora-se a abordagem dentro do ciclo do PDCA de forma a gerenciar as informações e os resultados, tornando o processo padronizado e de fácil utilização pelos profissionais da indústria de petróleo / Abstract: The problem of estimation of the total time to drill wells in oil and gas industry can be considered as a challenge for decision-makers because it is associated with scarce resource allocation (rigs, labour, time etc.) and also restrictions in expenditures. Then, the development of a methodology that provides more information can contribute to the improve quality of decisions and add value to companies. In this dissertation the research is focused on probabilistic approach to forecast the total time to drill wells in oil and gas industry using Monte Carlo simulation. It is based on logical modeling of activities that must be carried out over time. Some of them are in series whereas others can be in parallel. After that, information about variability in time to complete each activity is modeled using probability distributions, which are selected from the use of statistical test applied to available historical data. By putting together Monte Carlo simulation and the proposed model, the analyst can estimate the probability distribution of the random variable total time of drilling. With this information, it is possible the answer to questions such as: (1) What is the expected time to drill a well?; (2) What is the probability that the real time is X% higher that of the original forecast?; (3) What is the probability that delays can occur in the time do complete some of the activities?; (4) In case of the time to complete initial activities is above the expected, what is the probability that the total will not be longer that originally forecasted?; (5) etc. Additionally, this methodology is run according to the PDCA model, which as a standard and familiar tool, in an attempt to make easier the management of information and results, make the entire process standard and easily employed by practitioners of the petroleum industry / Mestrado / Reservatórios e Gestão / Mestre em Ciências e Engenharia de Petróleo

After the calamitous and environmentally devastating occurrence of the Deepwater Horizon Oil Spill in the Gulf of Mexico in 2010, the sobering realities of the United States' failure to successfully protect its ocean waters have caused several modifications in policy, legislation, and overall direction ofthe entire nation. Although there has been a general shift towards ecological safety and away from the pursuit to drill, oil-drilling explorations have continued to take place in internationally. This research will focus on the future operations of Repsol YPF, S.A., a Spanish oil company stationed in Cuba, whose drilling ambitions have caused a myriad of problems for the United States. The intent of this paper is to investigate the legalities surrounding Cuba's forthcoming deepwater oil drilling plan within the Florida Straights and how the existing relations between Cuba and the United States will shape the outcome. The majority of United States officials, senators, and policymakers are experiencing a great deal of anxiety and apprehension as Cuba's oil drilling plan continues to solidify. Recent changes in legislation and congressional opinion display the United States' overall objective to shape the manner in which the drilling operations will be carried out. This thesis will ultimately explore what progress the United States has made thus far in the sector of dialogue with Cuban officials, the various options the United States could seek in regards to taking part in the drilling operations that will soon commence in Cuba, and the current risks involved with the entirety of the drilling endeavor.

Face à la complexité croissante des trajectoires et des conditions opérationnelles des forages pétroliers et géothermiques, le phénomène de fatigue est devenu la cause principale de rupture des garnitures de forage. La fatigue des tiges est essentiellement liée à leur flexion cyclique due à leur rotation dans une section courbe du puits. L'objectif de ce travail est d'élaborer une méthodologie ainsi que les modèles numériques nécessaires pour évaluer la fatigue des tiges au cours du forage de puits à trajectoire complexe. Pour ce faire, nous proposons d'abord de choisir parmi les approches existantes de prévision de la durée de vie en fatigue d'une structure celles qui nous ont semblé les plus pertinentes pour le problème de fatigue des systèmes de forage. Puis, ces approches (qui comprennent les théories de la fatigue et de la rupture ainsi que des lois empiriques), et des logiciels de calcul de structures sont ensuite intégrés dans des algorithmes de calcul incrémental de la fatigue d'un système en fonction de l'évolution de l'opération du forage. Du fait que les contraintes dans les tiges restent souvent dans le domaine élastique, deux modèles de fatigue des tiges sont développés : un premier est basé sur le calcul du cumul de fatigue et un second sur le calcul de la propagation de fissure par fatigue. Ces deux modèles peuvent être utilisés dans la phase de conception de la trajectoire du puits et de la garniture pour le forer, de même qu'en opération pour prédire les risques de rupture par fatigue du train de tiges. Ceci permet à l'opérateur de planifier la gestion des tiges et leurs inspections en fonction de l'historique de leur utilisation. / Facing the growing complexity of trajectories and operating conditions of oil and geothermal drillings, the fatigue phenomenon has become the main cause of drill-string failure. The fatigue of drill-pipes is essentially due to their cyclic bending caused by their rotation in a curved section of the well. The objective of this work is to develop a methodology and the necessary numerical models to assess the fatigue of drill-pipes during drilling operations of complex trajectory wells. For this purpose, we propose firstly to choose among the available approaches for structure fatigue life prediction those that seem most relevant to drill-string fatigue problem. Then, these approaches (which include the fatigue and fracture theories as well as empirical laws), and structural calculation software are then integrated into incremental computation algorithms of drill-pipe fatigue in function of drilling operation evolution. Since the stresses in drill-pipes remain often within the elastic domain, two fatigue models for drill-pipes are developed: the first one is based on the cumulative fatigue calculation and the second one on the fatigue crack growth calculation. These models can be used in the well and drill-string design, or in real time during drilling to predict the fatigue failure in the drill-string. This allows the drill operator to plan the management of drill-pipes and their inspections depending on their usage history.

The oil and gas industry faces a lack of compact drilling devices capable of performing horizontal drilling maneuvers in depleted or abandoned wells in order to enhance oil recovery. The purpose of this project was to design and develop a smart sensing system that can be later implemented in compact drilling devices used to perform horizontal drilling to enhance oil recovery in wells. A smart sensor is the combination of a sensing element (sensor) and a microprocessor. Hence, a smart sensing system is an arrangement that consists of different sensors, where one or more have smart capabilities. The sensing system was built and tested in a laboratory setting. For this, a test bench was used as a case study to simulate the operation from a micro-drilling device. The smart sensing system integrated the sensors essential for the direct operational measurements required for the robot. The focus was on selecting reliable and sturdy components that can handle the operation Down the Hole (DTH) on the final lateral micro-drilling robot. The sensing system's recorded data was sent to a microcontroller, where it was processed and then presented visually to the operator through a User Interface (UI) developed in a cloud-based framework. The information was filtered, processed, and sent to a controller that executed commands and sent signals to the test bench’s actuators. The smart sensing system included novel modules and sensors suitable for the operation in a harsh environment such as the one faced in the drilling process. Furthermore, it was designed as an independent, flexible module that can be implemented in test benches with different settings and early robotic prototypes. The outcome of this project was a sensing system able to provide robotic drilling devices with flexibility while providing accurate and reliable measurements during their operation.

<p dir="ltr">This project aimed to develop an instrumentation and control system for a micro-drilling robot based on Industrial Internet of Things (IIoT) technologies. The automation system integrated IIoT technological tools to create a robust automation system capable of being used in drilling operations. The system incorporated industrial-grade sensors, which carried out direct measurements of the critical variables of the process. The indirect variables relevant to the control of the robot were calculated from the measured parameters. The system also considered the telemetry architecture necessary to reliably transmit data from the down-the-hole (DTH) robot to a receiver on the surface. Telemetry was based on wireless communication through long-range radio frequency (LoRa). The system developed had models based on Artificial Intelligence (AI) and Machine Learning (ML) for determining the mode of operation, detecting changes in the process, and changes in drilling variables in critical hydraulic components for the drilling process. Algorithms based on AI and ML models also allowed the user to make better decisions based on the variables' correlation to optimize the drilling process (e.g., dynamic change of flow, pressure, and RPMs based on automatic rock identification). A user interface (UI) was developed, and digital tools to perform data analysis were implemented. Safety assessment in all robot systems (e.g., electrical, hardware, software) was contemplated as a critical design component. The result of this research project provides innovative micro-drilling robots with the necessary technological tools to optimize the drilling process. The system made drilling more efficient, reliable, and safe, providing diagnostic and prognostic tools that allowed planning maintenance based on the actual health of the devices. The system that was developed was tested in a test bench under controlled conditions within a laboratory to characterize the system and collect data that allowed ML models' development, training, validation, and testing. The prototype of a micro-drilling robot installed on the test bench served as a case study to assess the implemented models' reliability and the proposed telemetry.</p>