Derivative-Free Optimization with Proxy Models for Oil Production Platforms Sharing a Subsea Gas Network

The deployment of offshore platforms for the extraction of oil and gas from subsea reservoirs presents unique challenges, particularly when multiple platforms are connected by a subsea gas network. In the Santos basin, the aim is to maximize oil production while maintaining safe and sustainable levels of CO2 content and pressure in the gas stream. To address these challenges, a novel methodology has been proposed that uses boundary conditions to coordinate the use of shared resources among the platforms. This approach decouples the optimization of oil production in platforms from the coordination of shared resources, allowing for more efficient and effective operation of the offshore oilfield. In addition to this methodology, a fast and accurate proxy model has been developed for gas pipeline networks. This model allows for efficient optimization of the gas flow through the network, taking into account the physical and operational constraints of the system. In experiments, the use of the proposed proxy model in tandem with derivativefree optimization algorithms resulted in an average error of less than 5% in pressure calculations, and a processing time that was over up to 1000 times faster than the phenomenological simulator. These results demonstrate the effectiveness and efficiency of the proposed methodology in optimizing oil production in offshore platforms connected by a subsea gas network, while maintaining safe and sustainable levels of CO2 content and pressure in the gas stream.N/

Hybrid Systems for Marine Energy Harvesting

Technologies to harvest marine renewable energies (MREs) are at a pre-commercial stage, and significant R&D progress is still required in order to improve their competitiveness. Therefore, hybridization presents a significant potential, as it fosters synergies among the different harvesting technologies and resources. In the scope of this Special Issue, hybridization is understood in three different manners: (i) combination of technologies to harvest different MREs (e.g., wave energy converters combined with wind turbines); (ii) combination of different working principles to harvest the same resource (e.g., oscillating water column with an overtopping device to harvest wave energy); or (iii) integration of harvesting technologies in multifunctional platforms and structures (e.g., integration of wave energy converters in breakwaters). This Special Issue presents cutting-edge research on the development and testing of hybrid technologies for harvesting MREs and intends to inform interested readers on the most recent advances in this key topic

Innovation in energy sector: a comparative study in Brazil and Portugal

Comunicação apresentada no 8th European Conference on Innovation and Entrepreneurship - ECIE, 19-20 setembro 2013, Bruxelas, Bélgica     

Reservoir Characterisation: - Multi-Scales Permeability Data Integration: Lake Albert Basin, Uganda

Imperial Users onl

Abordagem multi-escalar para a construção de um modelo de reservatorio carbonatico com feições cársticas e tendências do pré-sal brasileiro usando simulação numérica

Orientador: Denis José SchiozerDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica e Instituto de GeociênciasResumo: O pré-sal brasileiro é formado principalmente por carbonatos nos quais podem ocorrer cenários de desenvolvimento cárstico. Este tipo de reservatório apresenta um desafio para modelagem e simulação de fluxo, dado seu comportamento multiescalar heterogêneo. O uso de abordagens hierárquicas multiescalar tem mostrado ser útil para representar heterogeneidades em reservatórios complexos. Metodologias relacionadas ao gerenciamento de reservatórios podem ser testadas em modelos sintéticos de reservatórios. No presente trabalho, apresentamos a elaboração de um modelo sintético de reservatório com características do pré-sal brasileiro e feições cársticas, baseado em uma abordagem hierárquica de transferência de escala. O método integra modelagem e transferência de escala entre malhas que possuem diferentes tamanhos de bloco e geometria. O modelo geológico de campo completo, denominado Lira-G, é gerado pela combinação de dois modelos denominados Lira-M e Lira-K. O modelo Lira-M tem as mesmas dimensões de bloco que Lira-G e representa a simulação estocástica de saída usando dados de perfil de dois poços. O Lira-K tem uma resolução maior, os carstes são heterogeneidades em pequena escala além da escala dos blocos Lira-M. O procedimento de transferência de escala foi ajustado através de simulação de fluxo. O processo de validação mostrou a influência das feições cársticas na recuperação no comportamento dinâmico. Usando pseudo-curvas foi possível combinar os dados dinâmicos de produção. Finalmente, Lira-G é transferido para uma malha mais grossa, chamada Lira-S para ser usado em simulação numérica de fluxo. Este trabalho contribuiu com uma abordagem hierárquica de transferência de escala para construir um modelo geológico cárstico, integrando modelagem e simulação de reservatório. O modelo proposto Lira-G, acrescenta uma oportunidade para ser utilizado como modelo de referência numa proposta de benchmark para avaliar e comparar diferentes metodologias com foco em transferência de escala e simulação numérica de reservatóriosAbstract: The Brazilian pre-salt is formed mainly by carbonates in which karstic development scenarios can occur. This type of reservoir presents a challenge for modeling and flow simulation given its heterogeneous multiscale behavior. The use of hierarchical upscaling approach has shown to be useful to represent heterogeneities in complex reservoirs. Methodologies regarding reservoir management can be tested in synthetic reservoir models. In this work, we present the elaboration of a synthetic reservoir model with Brazilian pre-salt characteristics and karst features, based on a hierarchical upscaling approach. The method integrates modeling and scale transfer between grids with different block sizes and geometry. The full field geological model, called Lira-G, is generated by combining two models, Lira-M and Lira-K. Lira-M has the same cell dimensions as Lira-G and represents the output stochastic simulation using well log data. Lira-K has a finer cell resolution; karsts are small-scale heterogeneities beyond the Lira-M cell. The upscale procedure was validated using flow simulation. The validation process showed the influence of karst features in recovery and dynamic behavior. By using pseudo-curves, it was possible to match the dynamic production data. Finally, Lira-G is upscaled to a coarser grid, called Lira-S, to be used in numerical flow simulation. This work contributed to a hierarchical upscaling approach to construct a karstic geological model, integrating modeling and reservoir simulations. The proposed model provides an opportunity to be used as a benchmark to evaluate and compare different methodologies regarding upscaling procedures and reservoir numerical simulationMestradoReservatórios e GestãoMestre em Ciências e Engenharia de Petróleo33003017CAPE

Intelligent data-driven decision-making to mitigate or stop lost circulation

”Lost circulation is a challenging problem in the oil and gas industry. Each year, millions of dollars are spent to mitigate or stop this problem. The aim of this work is to utilize machine learning and other intelligent solutions to help to make better decision to mitigate or stop lost circulation. A detailed literature review on the applications of decision tree analysis, expected monetary value, and artificial neural networks in the oil and gas industry was provided. Data for more than 3000 wells were gathered from many sources around the world. Detailed economics and probability analyses for lost circulation treatments’ strategies were conducted for three formations in southern Iraq which are the Dammam, Hartha, and Shuaiba formations. Multiple machine learning methods such as support vector machine, decision trees, logistic regression, artificial neural networks, and ensemble trees were used to create models that can predict lost circulation and recommend the best lost circulation treatment based on the type of loss and reason of loss. The results showed that the created models can predict lost circulation and recommend the best lost circulation strategy within a reasonable margin of error. The created models can be used globally which avoids the shortcoming in the literature. Intelligence solutions and machine learning have proven their applicability to solve complicated problems and make better future decisions. With the large data available in the oil and gas industry, these methods can help the decision-makers to make better future decisions that will save time and money”--Abstract, page iv

Climate Change Mitigation Technologies: Carbon Capture and Storage in the Brazilian scenario

In the present paper, it is intended to analyze how CCS (Carbon Capture, Transport, and Storage) activities are linked to the Sustainable Development Goals and how Brazil can adjust itself in regulatory terms to the activities in question, especially in the ambit of the requirements for its environmental licensing. The Environmental Impact Assessment (EIA) is a necessary support for the Environmental Licensing process of activities that cause significant environmental degradation, as it is suggested that the activities of Carbon Capture, Storage, and Transport associated with the exploration and production of oil and gas. After the assessment, the environmental agency may grant environmental licenses. Based on the analogy to existing norms in our planning, this paper presents possible alternatives to the environmental licensing of CCS activities in Brazil. Thus, from a study case, specifically, considering the potential for the construction of salt caves for carbon storage in the pre-salt area, we concluded that it is possible to draw alternatives rules to achieve offshore storage. Keywords: Sustainable Development Goals, CCS (Carbon Capture, Transport, and Storage), Regulation, Environmental License, Salt Cavern DOI: 10.7176/RHSS/11-20-01 Publication date:October 31st 202

Heat of Absorption of CO2 in Aqueous Solutions of DEEA, MAPA and their Mixture

AbstractA reaction calorimeter was used to measure the differential heat of absorption of CO2 in phase change solvents as a function of temperature, CO2 loading and solvent composition. The measurements were taken for aqueous solutions of 2-(diethylamino)ethanol (DEEA), 3-(methylamino)propylamine (MAPA) and their mixture. The tested compositions were 5M DEEA, 2M MAPA and their mixture, 5M DEEA + 2M MAPA which gives two liquid phases on reacting with CO2. Experimental measurements were also carried out for 30% MEA used as a base case. The measurements were taken isothermally at three different temperatures 40, 80 and 120°C at a CO2 feed pressure of 600kPa. In single aqueous amine solutions, heat of absorption increases with increase in temperature and depends on thetype of amine used. DEEA, a tertiary amine, has lower heat of absorption compared to MAPA being a diamine with primary and secondary amine functional groups. For amine mixtures, heat of absorption is a function of CO2 loading and temperature. The heat of absorption against CO2 loading depends on the composition of the amines in the mixture. All the measured data in this work were compared with 30% MEA at absorption (40°C) and desorption (120°C) conditions

Measuring renewables’ impact on biosphere integrity: A review

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