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Reservoir Simulation Featured Image

Reservoir Simulation

Apply analytical and numerical simulation techniques to the development, testing and refining of a reservoir model, and the generation of an optimal reservoir exploitation plan. Upon completion of this module, the participant should be able to:define reservoir simulation objectives, define simulator geometry and dimensions, and assign flow equations to the proposed model, define simulator grid and boundary conditions, compile reservoir model input parameters, develop finite-difference approximations to solve the flow equations, plan numerical simulation computer runs and interpret the results, and use simulation results to determine the optimum exploitation scheme.

Data Analytics in Reservoir Engineering Featured Image

Data Analytics in Reservoir Engineering

Reservoir engineering is rapidly evolving, and traditional methods alone can no longer meet the demands of today's complex reservoirs and business needs. In this course, you will learn how to leverage cutting-edge data analytics techniques to extract valuable insights from vast amounts of reservoir data. In this course, we will explore current applications of data analytics in reservoir engineering, ensuring you develop a clear understanding of how these techniques can enhance your work. Additionally, we will delve into recent trends and developments that merge data-driven and physics-based methods (hybrid reservoir models), enabling you to stay ahead of the curve in this rapidly evolving field with focus on surveillance, reservoir management and field optimization for unconventional and conventional reservoirs. From understanding the methodology behind model development to exploring machine learning algorithms, you'll gain a solid foundation in data analytics and its relevance in reservoir engineering that will allow you to make more informed decisions and optimize reservoir performance. We will guide you through a hands-on model development process, equipping you with the best practices and helping you navigate potential pitfalls. No prior Python knowledge is required, but we will provide optional code samples for those interested in diving deeper. As we wrap up the course, we will explore future trends in data, models, automation, and the human element in reservoir engineering. You'll gain valuable insights into where the industry is headed, ensuring you stay at the forefront of innovation.