Virtual Networking EventStarts: Thu, Sep 3, 2020 5:00 PM
Ends: Thu, Sep 3, 2020 6:30 PM
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Reeling is the fastest and most efficient method for installing offshore pipelines. The pipe joints of a certain diameter and wall thickness are lined up and welded together onshore to make long pipe stalks before being spooled onto the reels mounted on the deck of a reel lay vessel. This presentation outlines the engineering fundamentals of the reeling process, discusses the practical aspects and applications of reeling mechanism from spoolbase fabrication to reeling process, up to the unspooling process and offshore installation.
The presentation on risk assessment will provide a brief walkthrough of the process of technical research and its application in consulting practice. The process is exemplified by a case study on probabilistic risk assessment in the field offshore geotechnical engineering.
Mark your calendar for Thursday September 3rd 5pm-6:30pm to join us for a great live-virtual discussion. This event is FREE, so invite your friends and colleagues to join.
About the Presenters
Georgiy Makedonov graduated from University of Houston with a dual MS degree in Mechanical and Subsea Engineering. His past involvement on campus included being a President of Society of Underwater Technology - Subsea Engineering Society (SUT-SES). Georgiy is the winner of 2019 UH SPE Paper Contest and was awarded the second place at the 2019 Regional SPE Paper Contest with the topic of "Novel design of mitigating pipeline erosion". He past experience included working as a Rigid Pipeline Engineer at TechnipFMC. Georgiy has recently started his new career path at VIAS as a FEA Engineer.
Roneet Das is a geotechnical engineer/consultant with Norwegian Geotechnical Institute in Houston, TX focusing on the offshore energy business. He currently serves as the Vice-chair of SUT-YP and a mentor in the SUT mentorship program. He received a Master's of Science in Geotechnical Engineering from Texas A&M University at College Station. His graduate research focused on probabilistic risk assessment using Bayesian Inference.
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