LNG Regasification and End Use
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This workshop explores the critical processes of LNG regasification and its integration into downstream applications. It covers terminal design, regasification technologies, and the delivery of natural gas for industrial, commercial, and power generation use. Participants will gain a practical understanding of how LNG is converted back to gas and efficiently supplied to end-users.
Workshop Objectives
• Understand the regasification process and its role in the LNG value chain.
• Examine terminal infrastructure and vaporization technologies.
• Review safety, operational, and environmental considerations in regasification.
• Analyze key end-use sectors including power generation, city gas distribution, and industrial consumption.
• Assess economic and regulatory factors influencing LNG market adoption.
About the Presenter
The workshop will be led by a seasoned professional in LNG terminal operations, gas markets, and energy infrastructure. With a proven track record in technical design, operations, and strategy, the presenter combines deep industry knowledge with practical insights to equip participants with relevant, real-world skills.
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Modern Reservoir Characterization : Integrating Artificial Intelligence (AI) with Traditional Methods
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.