The Future of Metocean: Observations, Geospatial Intelligence, AI & Offshore Decision Making
05 May 2027
Room 600
Technical Session
As offshore operations move into increasingly complex and data-rich environments, the metocean discipline is rapidly evolving beyond traditional forecasting into an integrated decision-support ecosystem. This invited session will explore how advances in ocean observations, operational forecasting, geospatial technologies, and artificial intelligence are reshaping offshore decision-making across the full metocean lifecycle — from scientific research and sensor deployment to real-time operational risk management. The session will bring together academia, technology providers, and industry leaders to highlight emerging capabilities in multidimensional data integration, autonomous observations, high-resolution forecasting, digital twins, and AI-enabled analytics. Particular emphasis will be placed on how geospatial platforms and advanced computational techniques are improving situational awareness, operational efficiency, and risk-informed decision-making offshore. Topics will span foundational ocean research, operational metocean services, remote sensing and autonomous systems, GIS-enabled visualization, and next-generation AI applications supporting offshore energy, marine operations, and resilience planning.
Chairperson(s)
Proposal JSON
[{"proposaltitle":"Rea Real-time Ocean Monitoring: Wireless Subsea-to-surface Data Transmission For Offshore Metocean Observations","proposalnumber":"37421","SessionRoleStatus":"Primary","ProposalTime":" ","AuthorBlock":"M. Rhodes, Csignum; S.F. Dimarco, Texas A&M University; L. Lee III, GERG - Texas A&M University; J. Paul, CSignum Ltd; A. Knap, Texas A&M University"},{"proposaltitle":"Developing The Applied Quantum Ocean: Transforming Metocean Observations And Offshore Decision-making In A Quantum Era","proposalnumber":"37394","SessionRoleStatus":"Primary","ProposalTime":" ","AuthorBlock":"S.F. Dimarco, Texas A&M University - GERG; N. Altangerel, A. Hazrathosseini, P. Hemmer, Texas A&M University - IQSE; X. Ge, Texas A&M Geochemical & Environmental Research Group; Y. Liu, Texas A&M University - GERG; R. Ramos, Woods Hole Group; P. Leung, Shell Technology; A. Sokolov, A. Zheltikov, Texas A&M University - IQSE; H. Potter, A. Knap, Texas A&M University - GERG; M. Scully, Texas A&M University - IQSE"},{"proposaltitle":"Observing Surface Currents Using Unmanned Aerial Systems And Fixed Video Cameras","proposalnumber":"37339","SessionRoleStatus":"Primary","ProposalTime":" ","AuthorBlock":"S. Socolofsky, K. Chang, V. Bheeroo, M. Lee, Texas A&M University"},{"proposaltitle":"Collaborative Intelligence For Autonomous Observing Systems In The Gulf","proposalnumber":"37502","SessionRoleStatus":"Primary","ProposalTime":" ","AuthorBlock":"P.F. Lermusiaux, P. Haley, C. Mirabito, MIT; S.F. Dimarco, Texas A&M University; N. Shay, U Miami; A. Knap, Texas A&M University; S. Glenn, Rutgers; S. Morey, FAMU; E. Chassignet, FSU; T. Miles, Rutgers; B. de la Cruz, Miami; M. Leber, John Wood Group PLC; S. Mahmud, TAMU; R. Ramos, H. Nowak, J. Storie, Woods Hole Group; M. Tenreiro, CIGOM; E. Pallas, CICESE; G.A. Stuart, Frugo; J.R. Van Smirren, Ocean Sierra LLC; J. Sheinbaum, CICESE; A. Bower, WHOI"},{"proposaltitle":"Open AI Weather Models For Offshore Decision Making: Where Earth-2 Meets Metocean Practice","proposalnumber":"37548","SessionRoleStatus":"Primary","ProposalTime":" ","AuthorBlock":"S. Posey, NVIDIA"},{"proposaltitle":"Esri ArcGIS As An Integrated Platform For Metocean Data Management And Analysis","proposalnumber":"37443","SessionRoleStatus":"Primary","ProposalTime":" ","AuthorBlock":"S. Mallavaram, A. Boone, ESRI"},{"proposaltitle":"Forecasting Change: Making The Most Of Artificial Intelligence And Machine Learning Within The Metocean Discipline","proposalnumber":"37415","SessionRoleStatus":"Primary","ProposalTime":" ","AuthorBlock":"E. Steele, M. Juniper, Met Office; S. Jaramillo, Shell Global Solutions US Inc.; J. McConochie, Shell Australia Pty Ltd."},{"proposaltitle":"A Hybrid Statistical Dynamical Ensemble Framework For Probabilistic Ocean Forecasting In The Intra Americas Sea","proposalnumber":"37439","SessionRoleStatus":"Primary","ProposalTime":" ","AuthorBlock":"A. Srinivasan, Tendral; J. Storie, R. Ramos, Woods Hole Group"},{"proposaltitle":"From Research To Operations: The Value Of Purposeful Stakeholder Engagement In Advancing Gulf Ocean Prediction","proposalnumber":"37408","SessionRoleStatus":"Primary","ProposalTime":" ","AuthorBlock":"A. Knap, S.F. Dimarco, Texas A&M University; S. Glenn, Rutgers University; R. Ramos, Woods Holte Group; E. Steele, Met Office; O.E. Esenkov, ExxonMobil Upstream Integrated Solutions Co; J. Stear, Chevron Corporation; M. Forbes, Oceanographer; S. Jaramillo, Shell Oil Co.; G. Jacobs, University of Southern Mississippi; R. Monreal Jimenez, D. Salas de Leon, UNAM"}]