Optimal scheduling of field activities using constraint satisfaction problem theory

The challenge of identifying problematic wells and planning their workover operations is common in oil and gas fields. On top of this, the well intervention resources are seldom easily accessible so it is crucial to target the right set of wells at the right time. Oil and gas reservoirs are complex dynamic systems the production and injection patterns of which can significantly affect the reservoir and well response. This represents a complex mathematical optimisation problem where the overall life performance of the field strongly depends on the workover planning decisions. This work presents a reliable and effective tool that is able to screen and explore the large search space of the potential work-overs that adds value to the reservoir management process. The proposed solution considers the overall performance of the field throughout a specified period while respecting all operational limitations as well as considering the risks and costs of the interventions. The proposed workflow combines the commercial optimiser techniques with constraint satisfaction problem optimiser to identify the optimal workover scheduling. The schedule found is guaranteed to satisfy all predefined field constraints. The presented results showed better performance achieved by the proposed hybrid optimiser compared to classical gradient-free optimisation techniques such as Genetic Algorithm in maximising the defined objective function. The suggested workflow can greatly enhance the decisions related to field development and asset management involved with large number of wells and with limited intervention resources

Proposta de Modelo Matemático para o Problema de Roteamento de Sondas de Intervenção a Poços de Petróleo Terrestres Revelados Dinamicamente com Período de Atendimento Viável

Durante a fase de produção em poços de petróleo terrestres uma das atividades mais importantes e caras é o uso de sondas de intervenção. O funcionamento de cada um desses poços ocorre, na maioria das vezes, em condições difíceis com perfil de produção com grande variação em função da sua geologia, localização e a maneira como o poço é desenvolvido. Estas características levam ao longo da vida produtiva dos poços à necessidade de intervenções de manutenção nomeadas como workover, que são fundamentais para manter a produção ou mesmo melhorar a produtividade ao corrigir falhar que tipicamente ocorrem nos equipamentos dos poços. Como as sondas de intervenção são equipamentos caros e, por isto, em menores quantidades comparadas a quantidade de poços terrestres que demandam intervenções de manutenção, ocorre a geração de filas de poços aguardando atendimento. Isto leva a necessidade de geração de rotas de atendimento aos diferentes poços com as escassas sondas existentes, desafio conhecido como Problema de Roteamento de Sondas de Intervenção (PRSI). Na literatura, verificam-se modelos e métodos de solução para o PRSI estático, ou seja, que busca minimizar a perda total de produção, não considerando a possibilidade de novas informações relevantes para o roteamento serem reveladas ao longo do horizonte de planejamento. Sendo assim, busca-se neste trabalho estudar e propor um modelo matemático com abordagem dinâmica para o PRSI que minimize a perda total de produção dos poços revelados ao longo de um horizonte de planejamento. O PRSI Dinâmico foi resolvido ao ser criado algoritmo estrutural executado ao longo de um horizonte de planejamento, contendo o modelo matemático proposto, linearizado para execução no solver CPLEX, utilizando técnicas de Programação Linear Inteira Mista. Os resultados computacionais foram obtidos considerando instâncias geradas artificialmente, e a conclusão dessa pesquisa mostra que o modelo proposto aproxima o PRSI Dinâmico do contexto operacional do problema, o que impacta no processo de definição das rotas e agendamento dos atendimentos

Uma meta-heurística Adaptive Large Neighborhood Search com mecanismos de paralelismo, detecção de estagnação e perturbações para o problema de roteamento de veículos com frota heterogênea, periódico e Multi-Trips

The planning of vehicle routes is a major issue involved in supply chains. In real environment we can find situations involving a very large number of clients or constraints witch indicate that exact methods should be avoided. In this context, this work presents an metaheuristic for solving some variants of the vehicle routing problem (VRP): Heterogeneous VRP, VRP Periodic and VRP with multi-trips. The metaheuristic chosen, called Adaptive Large Neighborhood Search (ALNS), combines the power of successful strategies in the literature as a large neighborhood search and adaptive mechanisms with new features such as parallelism, detection of stagnation and perturbations. Our ALNS was implemented in such a way that all variants of the VRP are solved without changes in the code. The results for several instances proposed in the literature are satisfactory, showing the good performance of the approach.A atribuição e o planejamento de rotas de veículos são problemas importantes envolvidos nas cadeias de suprimentos. Em ambiente real é comum encontrar situações que envolvam uma quantidade muito grande de clientes ou de restrições que consequentemente fogem do alcance de métodos exatos. Neste contexto, este trabalho apresenta uma meta-heurística capaz de resolver algumas variantes do problema de roteamento de veículos (PRV) combinadas: o PRV capacitado com frota heterogênea, o PRV periódico e o PRV com multi-trips. A meta-heurística escolhida, denominada Adaptive Large Neighborhood Search (ALNS), combina a força de estratégias bem-sucedidas na literatura como busca em vizinhança ampla e mecanismos adaptativos e também novos mecanismos como paralelismo, detecção de estagnação e perturbações. O ALNS foi implementado de tal maneira que todas as variantes do PRV citadas pudessem ser resolvidas sem alterações de código. Os resultados obtidos, em diversas instâncias propostas na literatura foram satisfatórios, mostrando o bom desempenho do método proposto

DECISION SUPPORT FOR OPTIMAL WELL PLACEMENT, INFRASTRUCTURE INSTALLATION AND PRODUCTION PLANNING IN OIL FIELDS

Ph.DDOCTOR OF PHILOSOPH

Um algoritmo de busca híbrido para o problema de roteamento de embarcações de suprimento periódico

High quality maritime petroleum transportation is critical to ensure timely flow of goods, reducing the total logistics cost and guaranteeing an efficient process. In this thesis, we focus on the transportation of deck cargo to offshore units as observed in the operations of our industrial partner in Rio de Janeiro, Brazil. The main objective of this research is to define the maritime routes to solve a periodic supply vessels routing problem, taking into account the port departure and opening hours at the offshore facilities. We describe the solution procedures currently used by the company, and we formally formulate the problem mathematically. Given that the sizes of the instances are too large to be solved exactly, we propose different methods to achieve better solutions with a reduced computational time. The first method, composed of three phases, uses a clustering heuristic combined with an exact method in order to perform the routing and ends with a resenquencing according to the operating hours, port departures and time between services constraits. The second method uses the adaptive large neighborhood search (ALNS) heuristic in an attempt to reduce the number of operations performed by the previous heuristic and the computational time. Finally, a hybrid method is proposed based on the ALNS heuristic and innovates with the concepts of the clustering search algorithm that proposes a detection of promising regions of the search space. The computational results indicate that the hybrid heuristic brings benefits to the ALNS by finding better solutions in less time and still reduces the coefficient of variation within a sample of solutions in different executions.O transporte marítimo de petróleo de alta qualidade é fundamental para assegurar um fluxo de mercadorias dentro do prazo previsto, reduzindo o custo total da logística e garantindo operações eficientes. Nesta tese, o focus está no transporte de carga de convés para unidades marítimas como observado nas operações do parceiro industrial no Rio de Janeiro, Brasil. O principal objetivo desta pesquisa é definir as rotas marítimas para resolver um problema de roteamento de embarcações de suprimento periódico, levando em consideração a programação do porto e o horário de abertura em algumas instalações. Os procedimentos atualmente utilizados pela empresa são descritos, e o problema é matematicamente formulado. Dado que o tamanho das instâncias é muito grande para serem resolvidos exatamente, propõem-se diferentes métodos visando alcançar melhores soluções com um baixo tempo computacional. O primeiro método, composto por três fases, usa uma heurística de agrupamento de unidades marítimas combinada a um método exato a fim de realizar o roteamento das mesmas e finaliza com o sequenciamento das rotas de acordo com as restrições de horários de funcionamento, partidas do porto e tempo entre atendimentos. O segundo método utiliza a heurística adaptive large neighborhood search (ALNS) na tentativa de reduzir a quantidade de operações realizadas pela heurística anterior e o tempo computacional. Por fim, propõe-se um método híbrido baseando-se na heurística ALNS e inovando com conceitos do algoritmo clustering search que propõe uma detecção de regiões promissoras do espaço de busca. Os resultados computacionais indicam que a heurística híbrida traz benefícios ao ALNS ao encontrar melhores soluções em menos tempo e ainda reduz o coeficiente de variação dentro de uma amostra de soluções em diferentes execuções

Efficient heuristics for the workover rig routing problem with a heterogeneous fleet and a finite horizon

Onshore oil fields may contain hundreds of wells that use sophisticated and complex equipments. These equipments need regular maintenance to keep the wells at maximum productivity. When the productivity of a well decreases, a specially-equipped vehicle called a workover rig must visit this well to restore its full productivity. Given a heterogeneous fleet of workover rigs and a set of wells requiring maintenance, the workover rig routing problem (WRRP) consists of finding rig routes that minimize the total production loss of the wells over a finite horizon. The wells have different loss rates, need different services, and may not be serviced within the horizon. On the other hand, the number of available workover rigs is limited, they have different initial positions, and they do not have the same equipments. This paper presents and compares four heuristics for the WRRP: an existing variable neighborhood search heuristic, a branch-price-and-cut heuristic, an adaptive large neighborhood search heuristic, and a hybrid genetic algorithm. These heuristics are tested on practical-sized instances involving up to 300 wells, 10 rigs on a 350-period horizon. Our computational results indicate that the hybrid genetic algorithm outperforms the other heuristics on average and in most cases

On-orbit serviceability of space system architectures

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics; and, (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division, Technology and Policy Program, 2006.Includes bibliographical references (p. 171-182).On-orbit servicing is the process of improving a space-based capability through a combination of in-orbit activities which may include inspection; rendezvous and docking; and value-added modifications to a satellite's position, orientation, and operational status. As a means to extend the useful life or operational flexibility of spacecraft, on-orbit servicing constitutes one pathway to a responsive space enterprise. Following launch, traditional satellite operations are tightly constrained by an inability to access the orbiting vehicle. With the exception of software upgrades from ground controllers, operators are wedded to supporting payload technologies that become rapidly obsolete and to bus structures that deform during the stress of launch and degrade in the harsh environment of space. On-orbit servicing offers satellite operators an option for maintaining or improving space-based capabilities without launching a new spacecraft. Numerous studies have been performed on on-orbit servicing, particularly regarding the architecture of the servicing provider. Several customer valuation case studies have also been performed to identify the economic case (or lack thereof) for different categories of servicing missions.(cont.) Little work, however, has been done to analyze the tradespace of potential on-orbit servicing customers-a global analysis of operational satellites currently orbiting the Earth. The goal of this research is to develop and test a methodology to assess the physical amenability of satellites currently in operation to on-orbit servicing. As defined here, physical amenability of a target satellite, or "serviceability," refers to the relative complexity required of a teleoperated or autonomously controlled robotic vehicle to accomplish on-orbit servicing. A three-step process is followed to perform serviceability assessments. First, a taxonomy of space systems is constructed to add structure to the problem and to identify satellite attributes that drive servicing mission complexity. Second, a methodology is proposed to assess serviceability across the four servicing activities of rendezvous, acquire, access, and service.(cont.) This includes development of an agent-based model based on orbital transfers as well as a generalized framework in which serviceability is decomposed into four elements: (1) knowledge, (2) scale, (3) precision, and (4) timing. Third, the value of architecture frameworks and systems engineering modeling languages for conducting serviceability assessments is explored through the development of a discrete event simulation of the Hubble Space Telescope. The thesis concludes with prescriptive technical considerations for designing serviceable satellites and a discussion of the political, legal, and financial challenges facing servicing providers.by Matthew G. Richards.S.M

Safety and Reliability - Safe Societies in a Changing World

The contributions cover a wide range of methodologies and application areas for safety and reliability that contribute to safe societies in a changing world. These methodologies and applications include: - foundations of risk and reliability assessment and management - mathematical methods in reliability and safety - risk assessment - risk management - system reliability - uncertainty analysis - digitalization and big data - prognostics and system health management - occupational safety - accident and incident modeling - maintenance modeling and applications - simulation for safety and reliability analysis - dynamic risk and barrier management - organizational factors and safety culture - human factors and human reliability - resilience engineering - structural reliability - natural hazards - security - economic analysis in risk managemen