Prefácio do livro: Fetch em Lagos e Reservatórios

Minha parceria com o Marcelo começou quando nos conhecemos no Programa de Pós-graduação em Engenharia de Recursos Hídricos e Ambiental da Universidade Federal do Paraná (PPGERHA-UFPR). O Marcelo concluía seu segundo ano de doutoramento e eu iniciava um período de pós-doutoramento. Nossos interesses de pesquisa na área de modelagem de vento e onda eram similares, de modo que pudemos trabalhar de forma complementar, produzindo resultados para verificação das simulações desenvolvidas. Eu me concentrava na aplicação de modelos numéricos de base física, disponíveis em software de domínio público, para cálculo de altura significativa de ondas, enquanto o Marcelo desenvolvia seu próprio programa computacional chamado ONDACAD, com o objetivo de automatizar a geração de campos de fetch e de altura significativa de onda para aplicação em corpos de águas continentais. Este período no PPGERHA-UFPR foi bastante produtivo. Diariamente nos reuníamos, com participação também de professores e pesquisadores do programa, para discussões frutíferas acerca do desenvolvimento da metodologia que o Marcelo estava desenvolvendo. Naquele espaço foram discutidas ideias inovadoras que o Marcelo colocou em prática no seu trabalho de doutorado, tais como as abordagens de cálculo rápido de fetch máximo e uma nova visão das equações paramétricas, mediante análise da influência da velocidade do vento na correlação altura significativa de onda-fetch adimensionais. Nesta época também presenciei a concepção da versão piloto do sistema HIDRONDA, desenvolvido para simulação e previsão de altura significativa de onda em corpos de água continentais, em tempo real e com divulgação dos resultados em uma página da internet. Após a defesa da tese de doutorado do Marcelo, houve um período de aplicação do programa computacional ONDACAD com o objetivo de validar a metodologia para diversos corpos de água continentais, caracterizados por uma grande variedade de formatos dendríticos e sob diferentes regimes de vento. Estas aplicações resultaram em estudos que foram publicados no decorrer dos anos no âmbito de congressos nacionais e internacionais, como no Simpósio Brasileiro de Recursos Hídricos em Brasília e Florianópolis, e no Congresso Latino-americano de Hidráulica em Santiago, Lima e Buenos Aires. Também foram publicados trabalhos na Revista Brasileira de Recursos Hídricos e no periódico científico norte americano Lake and Reservoir Management. Hoje é gratificante para mim escrever o prefácio deste livro, que apresenta de forma didática e concisa uma parte do trabalho produzido pelo Marcelo na área de modelagem de vento e onda nos últimos anos. O livro se concentra no entendimento do conceito de fetch, aplicado aos corpos de água continentais como lagos e reservatórios. São realizadas considerações fundamentais sobre os métodos de determinação de fetch e, subsequentemente, é proposto um método rápido para determinação do fetch máximo. Por fim, um capítulo é dedicado ao programa computacional ONDACAD que permite o cálculo de campos bidimensionais de fetch de maneira automatizada. Este livro é uma contribuição valiosa que serve como referência para quem pretende se dedicar ao estudo do comportamento do vento e sua influência na formação de ondas em lagos e reservatórios.

An Integrated and Automated Workflow to Enhance Production Efficiency and Compliance in a Giant Offshore Field

Daily production compliance is fundamental to sustain reservoir management excellence and ultimately achieve an optimum oil recovery. The production activities execution is critical to adhere to the reservoir management guidelines and best practices. It is a more challenging task in brownfields due to the limitation of controlling system and limited access especially in offshore fields. A timely and efficient approach is undoubtedly necessary to enhance production efficiency and compliance. An integrated and automated tool has been innovated to analyze and report well production status against the guidelines and requirements in a mature offshore field with more than 50 years history. This systematic approach has been developed through integrating the planned rate, daily actual production rate, latest flow tests, and current well performance. Noncompliance is reported automatically on a user defined time scale, including daily, weekly, monthly or any customized time range within the month time. Daily violation report is generated automatically and sent to production operation for prompt adjustments and other requested actions. The automated workflow enables both daily production reporting and production compliance reporting. Daily production reporting is a routine work, which usually takes a lot of time every day. The workflow is capable of reducing 90% of the time comparing to the manual way. Production compliance reporting is currently mainly focusing on the comparison of actual production to planned rate and guideline rate. Any exception will be reported as violation. The violation dashboard summarizes the details based on the user selected time range. On daily basis, an email containing the violation details could be generated and sent to the corresponding teams for corrective actions. In this giant brown field, production GOR is a primary controlling parameter. The latest flow tests have been taken into account to evaluate the gas production compliance. Any violation to the GOR guidelines will be reported in the same communication email for timely correction. With the innovated tool, the violation ratio of the giant offshore field has been successfully reduced and controlled. The usual responding time for corrections has been dramatically reduced from months to days.

Integrated Automation and Data-Driven Workflow for CO2 Project Management – Case Study from a Smart Oil Field in the Middle-East

Automation and data-driven models have been proven to yield commercial success in several oil fields worldwide with reported technical advantages related to improved reservoir management. This paper demonstrates the implementation of an integrated workflow to enhance CO2 injection project performance in a giant onshore smart oil field in Abu Dhabi. Since commissioning, proactive evaluation of the reservoir management strategy is enabled via smart-exception-based surveillance routines that facilitate reservoir/pattern/well performance review and supporting the decision making process. Prolonging the production sustainability of each well is a key pillar of this work, which has been made more quantifiable using live-tracking of the produced CO2 content and corrosion indicators. The intensive computing technical tasks and data aggregation from different sources; such as well testing and real time production/injection measurements; are integrated in an automatic workflow in a single platform. Accordingly, real-time visualizations and dashboards are also generated automatically; to orchestrate information, models and multidisciplinary knowledge in a systematic and efficient manner; allowing engineers to focus on problematic wells and giving attention to opportunity generation in a timely manner. Complemented with numerical techniques and other decision support tools, the intelligent system data-driven model assist to obtain a reliable short-term forecast in a shorter time and help making quick decisions on day-to-day operational optimization aspects. These dashboards have allowed measuring the true well/pattern performance towards operational objectives and production targets. A complete set of KPI's has helped to identify well health-status, potential risks and thus mitigate them for short/long term recovery to obtain an optimum reservoir energy balance in daily bases. In case of unexpected well performance behaviors, the dashboards have provided data insights on the root causes of different well issues and thus remedial actions were proposed accordingly. Maintaining CO2 miscibility is also ensured by having the right pressure support around producers, taking proactive actions from continues evaluation of producer-injector connectivity/interdependency, improving injection/production schedule, validating/tuning streamline model based on surveillance insights, avoiding CO2 recycling, optimizing data acquisition plan with potential cost saving while taking preventive measures to minimize well/facility corrosion impact. In this work, best reservoir management practices have been implemented to create a value of 12% incremental oil recovery from the field. The applied methodology uses an integrated automation and data-driven modeling approach to tackle CO2 injection project management challenges in real-time.

Enterprise-Driven, Asset-Focused Digital Oilfield DOF Assessment - Strategic Framework and Roadmap

A new integrated growth strategy of an oil & gas company is focusing on maximizing the value of reserves and production in order to meet the value proposition of the highest possible return to the company. The strategy is built on the strategic foundation of the company of People, Performance, Profitability and Efficiency. From a business performance perspective, the strategy will bear fruit through increased production capacity, improved operational and cost efficiencies, re-energizing mature fields and uncovering new resources whilst maintaining safety and asset integrity. The objective of this global level exercise aims to assess and evaluate various Digital Oilfield (DOF) practices and initiatives against industry best practices, to perform a landscape assessment of the upstream assets, to review the asset digital gap, to develop a strategic framework and roadmap ensuring that the company strategic pillars are supported across all relevant aspects, by closing the digital gap between current and future states. The assessment scope covers the following domains: Reservoir management Production optimisation Operation management & integrity Engineering & projects Drilling Efficiency Logistics & Planning The landscape assessment and gap analysis consist of several stages that starts from documenting the information received from the assets capturing their current business practices and processes, analyzing the "as-is" condition, designing the future state, assessing the impact to the specific assets, define the benefits and value and creating a 5-year business roadmap. Aligned with the company DOF strategy, understanding the asset digital gap and enhancing the asset digital maturity will improve: HSE and asset integrity by reducing hazard exposure, optimizing energy usage and improving wells and facilities integrity Collaboration and faster analysis leading to timely decision making Integrated operations by optimized drilling planning, operations, optimized production forecasting and integrated planning Optimum Reservoir Management through enhanced reservoir surveillance and recovery

NOC Subsurface Organization Transformation to Boost Its Resource Base and Secure Country's Energy Needs

UkrGasVydobuvannya (UGV) is an E&P organization of the National Oil Company (NOC) of Ukraine – Naftogaz Group. UGV's existing gas fields represent one of the largest reservoir portfolios in the Eastern Europe; however, the current depletion level of the company's fields is also among the highest; the bulk of the fields have depletion levels between 70 and 90%. The E&P Company (UGV) has created a resource base development strategy to plan and deliver exploration activities and reservoir management based on industry best practices to maintain and grow the company's production and bookable reserves for years to come. The subsurface transformation program (including both exploration and reservoir management domains) addresses the actions taken to ensure success for the Strategy. Actions consider not only increase in exploration acreage or acquiring new fields and prospects, but also the organizational, cultural, technological and process level changes across the subsurface domain in the company. The program is still in the early implementation phase; however, the first material results are confirming the validity of the program: Organization re-design per industry standards: asset development teams were established and aligned with the portfolio priorities; Digital database of subsurface data is being created and systemic reservoir surveillance is being executed; Growth source secured: Black Sea, new onshore unconventional and conventional licenses; Modern exploration practices, including risk-based probabilistic exploration drilling decisions and launching of Petroleum Systems Analysis and Basin modeling; Reshaping the obsolete rigid structure of the research institute into a modern R&D center; and, Professional development program tailored to build-up the modern skills and competencies of company's subsurface teams. These and other important steps of the transformation will ultimately help the company to ensure a healthy reserves replacement ratio and increase the production share of greenfields in its portfolio. This case study can serve as a blueprint for any medium-sized subsurface organization (especially in NOCs) that faces similar resource base challenges and wishes to improve its production performance.

A Tale of Two Dams: The Impact of Reservoir Management on Rural Depopulation in Central Spain

In rural areas, depopulation is mainly due to a lack of economic and employment opportunities. In this context, the reservoirs already built can be a source of socioeconomic development based on tourism and outdoor leisure activities. The condition for this development to materialize is that reservoir management considers these activities. In Central Spain, a process of rural depopulation has been generated in the municipalities around the reservoirs at the Upper Tagus River, as water management allows water transfers from the Tagus to the Segura River without taking into account regulations that prioritize and protect donor basin users. Through the comparison of reservoir water management and demographic data of two rural areas close to the reservoirs, this article reveals the direct relationship between reservoir management that enables recreational uses with its consequent socioeconomic development and the maintenance of the population in the territory. Consequently, reservoir water management based on the socioeconomic development of reservoir banks is necessary and a priority over transfers to another basin.

A Proxy Flow Modelling Workflow to Estimate Gridded Dynamic Properties and Well Production Rates by Deep Learning Algorithms

This paper proposes a deep learning-based framework for proxy flow modeling to predict gridded dynamic petroleum reservoir properties (like pressure and saturation) and production rates for wells in a single framework. It approximates the solution of a full physics-based numerical reservoir simulator, but runs much more rapidly, allowing users to generate results for a much wider range of scenarios in a given time than could be done with a full physics simulator. The proxy can be used for reservoir management tasks like history matching, uncertainty quantification, and field development optimization. A deep-learning based methodology for accurate proxy-flow modeling is presented which combines U-Net (a variant of convolutional neural network) to predict gridded dynamic properties and deep neural network (DNN) models to forecast well production rates. First, gridded dynamic properties, such as reservoir pressure and phase saturations, are predicted from static properties like reservoir rock porosity and absolute permeability using a U-Net. Then, the static properties and the dynamic properties predicted by the U-Net are input to a DNN to predict production rates at the well perforations. The inclusion of U-net predicted pressure and saturations improves the quality of the well rate predictions. The proposed methodology is presented with the synthetic Brugge reservoir discretized into grid blocks. The U-Net input consists of three properties: dynamic gridded reservoir properties (such as pressure or fluid saturation) at the current state, static gridded porosity, and static gridded permeability. The U-Net has only one output property, the target gridded property (such as pressure or saturation) at the next time step. Training and testing datasets are generated by running 13 full physics flow simulations and dividing them in a 12:1 ratio. Nine U-Net models are calibrated to predict pressures/saturations, one for each of the nine grid layers present in the Brugge model. These outputs are then concatenated to obtain the complete pressure/saturation model for all nine layers. The constructed U-Net models match the distributions of generated pressures/saturations of the numerical reservoir simulator with a correlation coefficient value of approximately 0.99 and above 95% accuracy. The DNN models approximate well production rates accurately from U-Net predicted pressures and saturations along with static properties like transmissibility and horizontal permeability. For each well and each well perforation, the production rate is predicted with the DNN model. The use of the constructed proxy flow model generates reservoir predictions within a few minutes compared to the hours or days typically taken by a full physics flow simulator. The direct connection that is established between the gridded static and dynamic properties of the reservoir and well production rates using U-Net and DNN models has not been presented previously. Using only a small number of runs for its training, the workflow matches the numerical reservoir simulator results with reduced computational effort. This helps reservoir engineers make informed decisions more quickly, resulting in more efficient reservoir management.