LNG Storage and Transportation
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This workshop provides a focused overview of Liquefied Natural Gas (LNG) storage and transportation practices, emphasizing design standards, operational safety, and regulatory requirements. Participants will gain insights into LNG’s unique cryogenic properties, storage technologies, and the logistics of transporting LNG safely and efficiently across global markets.
Workshop Objectives
• Understand the physical and chemical characteristics of LNG relevant to storage and transport.
• Examine key storage systems including tanks, terminals, and safety mechanisms.
• Explore transportation methods by land and sea, including pipelines, trucks, and LNG carriers.
• Review international codes, standards, and compliance requirements for LNG handling.
• Identify risk management strategies to enhance operational safety and reliability.
About the Presenter
The workshop will be delivered by an experienced industry professional in LNG operations, facility design, and energy logistics. With a background spanning engineering, safety management, and international project execution, the presenter brings practical knowledge and case-based insights to ensure participants gain both technical understanding and applied skills.
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For PEA Members Only
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.