Machine Learning Applications in Geomodeling and Formation Evaluations
Tuesday, 17 October
Room 214 D
Technical Session
This session highlights state-of-the-art machine learning (ML) applications in geomodeling and formation evaluation domains. It covers not only the latest developments of GAN application in subsurface modeling but also some successful ML uses cases such as seismic facies classification, CT rock image enhancement and rock properties prediction.
-
1400-1425 215099Attention Mechanism Neural Network For Seismic Facies Classification
-
1425-1450 214985Efficient Subsurface Modeling with Sequential Patch Generative Adversarial Neural Networks
-
1450-1515 215065Machine Learning Based Automatic Marker Clustering
-
1545-1610 214866A Data Analytics And Machine Learning Study On Site Screening Of CO2 Geological Storage In Depleted Oil And Gas Reservoirs In The Gulf Of Mexico
-
1610-1635 214883Enhancing The Resolution Of Micro CT Images Of Rock Samples Via Unsupervised Machine Learning Based On A Diffusion Model
-
1635-1700 215117A Comparative Study Of Deep Learning Models For Fracture And Pore Space Segmentation In Synthetic Fractured Digital Rocks
-
Alternate 214831A Data-driven Approach For Stylolite Detection
-(1200x628-px).png)