Join us for an immersive workshop tailored for professionals in the oil and gas industry to understand how machine learning can be implemented in production engineering and production monitoring domain Through hands-on exercises, attendees will explore data manipulation, visualization, and analysis techniques essential for optimizing production workflows.

This training course will provide delegates a full and comprehensive picture of Oil & Gas Industry. Professional from Oil & Gas Industry and other relevant sectors are able to grasp clearly the critical activities at upstream, middle stream and downstream of this Industry. This training course will also offer contemporary methods in Oil & Gas Industry. A structured approach would be taken whereby delegates have opportunities to engage, relate and contextualise meaningfully the fundamentals of the Oil & Gas Industry.

This advanced workshop dives into dynamic well modeling and simulation techniques to optimize oil and gas well performance under transient flow conditions. Participants will learn to predict, diagnose, and mitigate operational challenges using state-of-the-art numerical models and real-time data integration.Key Topics:Fundamentals of Dynamic Well ModelingApplications in Drilling & ProductionAdvanced Tools & Case Studies

During this workshop, participants will develop a more comprehensive grasp of the geophysical theory of seismic inversion and explore advanced seismic reservoir characterization techniques. Discover the essential steps in the seismic reservoir characterization workflow using machine learning, covering data processing to inversion analysis. Acquire valuable knowledge applicable to your everyday projects.In classical reservoir characterization, it is commonly assumed that the reservoir exhibits both elastic and hydraulic isotropy. However, real reservoirs often exhibit anisotropic characteristics and spatial heterogeneity on multiple scales. Relying solely on core and log data may not accurately represent the larger reservoir volume. Therefore, the most effective way to accurately analyze the physical properties of most actual reservoirs, across their entire volume, involves utilizing advanced machine learning methods for acquired and interpreted seismic data.

Join our engaging workshop designed for geologists, researchers, and professionals to master Python for statistical analysis, data processing, and machine learning in geology. Learn to analyze geological datasets, create insightful visualizations, and apply machine learning models to solve real-world geological challenges. This workshop blends expert instruction with practical, hands-on exercises to elevate your data science skills in Earth sciences.

This workshop teaches practical Python programming tailored for the oil and gas industry. Participants will learn to automate workflows, manage large datasets, perform petrophysical and production data analysis, and integrate Python with industry-standard software tools. The course emphasizes real-world applications such as reservoir monitoring, production optimization, and data-driven decision-making.

This workshop focuses on applying reservoir engineering principles using Microsoft Excel to analyze and manage hydrocarbon reservoirs effectively. Participants will learn to perform key calculations, model reservoir behavior, and optimize recovery through practical Excel-based exercises, enhancing their ability to make data-driven decisions in reservoir management.

This workshop introduces geologists and geoscientists to Python programming tailored for their field. Participants will learn how to use Python for data analysis, visualization, geospatial applications, and numerical modeling relevant to geology and geosciences. The course covers practical skills to automate workflows, interpret large datasets, and create 3D geological models, empowering professionals to enhance their research and decision-making capabilities.

This workshop introduces machine learning techniques applied specifically to reservoir and production engineering challenges. Attendees will learn how to build predictive models, analyze complex datasets, and optimize reservoir performance using data-driven algorithms. The course combines theoretical concepts with practical exercises to demonstrate ML applications in well performance forecasting and reservoir characterization.