Advances in Offshore Geotechnics
03 May 2027
Room 310
Technical Session
This session will explore emerging methods and technologies shaping the characterization, modelling, and design of offshore foundations and seabed systems. The papers in the session will highlight advances in experimental testing and soil characterization, including improved rheological methods for fine-grained sediments and dynamic property prediction for marine clays. The growing role of machine learning, three-dimensional probabilistic ground modelling, and data assimilation in improving geotechnical predictions, quantifying uncertainty, and supporting reliability-based offshore design will also be explored. Complementing these developments, the session will present new insights into the performance and installation of offshore foundation systems, including monopiles, helical piles, and ring anchors, as well as their behaviour under complex loading conditions. Together, these contributions demonstrate how advances in experimental methods, computational modelling, and data-driven engineering can strengthen the safety, reliability, and efficiency of offshore infrastructure.
Chairperson(s)
Proposal JSON
[{"proposaltitle":"A Standardized Rheology Testing Method For Characterizing Fine-grained Seabed Sediments In Submarine Debris Flow Runout Analysis","proposalnumber":"37264","SessionRoleStatus":"Primary","ProposalTime":" ","AuthorBlock":"A. Zakeri, P. Jeanjean, BP America Inc"},{"proposaltitle":"Machine Learning-based Prediction Of Dynamic Soil Properties Of Marine Clay","proposalnumber":"37253","SessionRoleStatus":"Primary","ProposalTime":" ","AuthorBlock":"V.M. Taboada, S. Pant, R. Zhao, A. Singh, K. Gan, Fugro; D. Cruz Roque, Institute Mexicano Del Petroleo; P. Barrera Nabor, Instituto Mexicano Del Petroleo; F.A. Flores Lopez, Ingenieros Geotecnicos Mexicanos"},{"proposaltitle":"Decision-ready 3D Probabilistic Ground Modelling For Reliability-based Offshore Top-hole Design","proposalnumber":"37448","SessionRoleStatus":"Primary","ProposalTime":" ","AuthorBlock":"C. Varady, J. Santos, E. Lima Junior, Federal University of Alagoas; R. Dias, F. Cutrim, Petrobras"},{"proposaltitle":"A Random Forest Machine Learning Model For Predicting Seabed Slope Failure Probability Under Storm Loading","proposalnumber":"37560","SessionRoleStatus":"Primary","ProposalTime":" ","AuthorBlock":"A. Rafiei, P. Sharif, Louisiana State University"},{"proposaltitle":"Installation-informed Probabilistic Design Of Offshore Wind Monopiles: A Cpt-based Data Assimilation Framework For Axial Capacity Updating","proposalnumber":"37507","SessionRoleStatus":"Primary","ProposalTime":" ","AuthorBlock":"S. Jodha, Norwegian Geotechnical Institute"},{"proposaltitle":"Experimental Evaluation Of Enhanced Helical Piles For Offshore Applications","proposalnumber":"37426","SessionRoleStatus":"Primary","ProposalTime":" ","AuthorBlock":"S. Thompson, G. Piercey, A. Giffin, A. Arghya, J. Barrett, C-CORE"},{"proposaltitle":"Numerical Investigation Of Deeply Embedded Ring Anchor Subjected To Cyclic Loading In Cohesive Soils","proposalnumber":"37457","SessionRoleStatus":"Primary","ProposalTime":" ","AuthorBlock":"H. Al-Janabi, State Company for Oil Projects"},{"proposaltitle":"Autonomous Motion Sensors For Verification Of Torpedo Pile Installation","proposalnumber":"37486","SessionRoleStatus":"Primary","ProposalTime":" ","AuthorBlock":"T. Amundsen, L. Jeffrey, 4Subsea AS"},{"proposaltitle":"Numerical Modelling Of The Deeply Embedded Ring Anchor Under Combined Loading","proposalnumber":"37509","SessionRoleStatus":"Primary","ProposalTime":" ","AuthorBlock":"R. Gogoi, NGI Inc.; C. Aubeny, Texas A&M University"}]