AI-Driven Reservoir Characterisation and Geologic Modelling
Tuesday, 13 January
Technical Session Room 2
Technical Session
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1130-1150 25211Data-driven Sw Prediction And Porosity Typing From Synthetic Vp/Vs: A Feasibility Approach For Enhancing Hydrocarbon Recovery In NFRs
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1150-1210 25248Combining AI And EM: A Dual Approach For Dynamic Waterflood Monitoring And Geological Modeling
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1210-1230 25213New Exploration Discovery Aided By Automatic Facies Classification In Deepwater Mixed Volcanic-carbonate-igneous Rock, South China Sea
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1230-1250 251923D Geological Modeling Using Generative AI
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Alternate 25229Accelerated Subsurface Characterization Powered By Science-aware Machine Learning
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Alternate 25233Ai-driven Carbonate Reservoir Detection Using Neural Network Seismic Inversion: A 3d Formation Evaluation Approach In The East Java Basin
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Alternate 25218Validity of Pre-trained Deep Learning Models for New Scanning Electron Microscopy (SEM) Rock Image Samples
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Alternate 25196From Rock To Digital: Unveiling Unconventional Reservoir Heterogeneity Through High-resolution Core Analysis And Machine Learning
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Alternate 25223Unveiling Subsurface Pinnacle Reefs Using Seismic Attributes And Machine Learning-based Image Segmentation Of 3D Seismic Data