| Machine Learning model interpretability using SHAP values: application to a seismic facies classification task D Lubo-Robles, D Devegowda, V Jayaram, H Bedle, KJ Marfurt, ... SEG Technical Program Expanded Abstracts 2020, 1460-1464, 2020 | 36 | 2020 |
| Independent component analysis for reservoir geomorphology and unsupervised seismic facies classification in the Taranaki Basin, New Zealand D Lubo-Robles, KJ Marfurt Interpretation 7 (3), SE19-SE42, 2019 | 35 | 2019 |
| Exhaustive probabilistic neural network for attribute selection and supervised seismic facies classification D Lubo-Robles, T Ha, S Lakshmivarahan, KJ Marfurt, MJ Pranter Interpretation 9 (2), T421-T441, 2021 | 19 | 2021 |
| Quantifying the sensitivity of seismic facies classification to seismic attribute selection: An explainable machine-learning study D Lubo-Robles, D Devegowda, V Jayaram, H Bedle, KJ Marfurt, ... Interpretation 10 (3), SE41-SE69, 2022 | 14 | 2022 |
| An in-depth analysis of logarithmic data transformation and per-class normalization in machine learning: Application to unsupervised classification of a turbidite system in the … TN Ha, D Lubo-Robles, KJ Marfurt, BC Wallet Interpretation 9 (3), T685-T710, 2021 | 13 | 2021 |
| Some machine learning applications in seismic interpretation S Chopra, D Lubo-Robles, KJ Marfurt AAPG Search and Discovery 42270, 2018 | 13 | 2018 |
| Supervised seismic facies classification using probabilistic neural networks: Which attributes should the interpreter use? D Lubo-Robles, T Ha, S Lakshmivarahan, KJ Marfurt SEG Technical Program Expanded Abstracts 2019, 2273-2277, 2019 | 12 | 2019 |
| DEVELOPMENT OF INDEPENDENT COMPONENT ANALYSIS FOR RESERVOIR GEOMORPHOLOGY AND UNSUPERVISED SEISMIC FACIES CLASSIFICATION IN THE TARANAKI BASIN, NEW ZEALAND. D Lubo-Robles | 8 | 2018 |
| Evaluation of principal component analysis for seismic attribute selection and self-organizing maps for seismic facies discrimination in the presence of gas hydrates D Lubo-Robles, H Bedle, KJ Marfurt, MJ Pranter Marine and Petroleum Geology 150, 106097, 2023 | 7 | 2023 |
| Statistical characterization and geological correlation of wells using automatic learning Gaussian mixture models D Lubo, K Marfurt, V Jayaram* Unconventional Resources Technology Conference, Denver, Colorado, 25-27 …, 2014 | 7 | 2014 |
| Delineation of thick incised canyons using spectral-decomposition analysis, curvature and self-organizing maps in the Exmouth plateau, Australia D Lubo-Robles, K Marfurt SEG Technical Program Expanded Abstracts 2017, 2420-2424, 2017 | 6 | 2017 |
| Unsupervised seismic-facies classification using independent-component analysis D Lubo-Robles, KJ Marfurt SEG Technical Program Expanded Abstracts 2018, 1603-1607, 2018 | 5 | 2018 |
| CO2 injectivity and storage potential of the Arbuckle Group using supervised machine learning and seismic-constrained reservoir modeling and simulation … AB Caf, D Lubo-Robles, MJ Pranter, H Bedle, KJ Marfurt, ZA Reza Second International Meeting for Applied Geoscience & Energy, 462-466, 2022 | 1 | 2022 |
| Discrimination of Deep Water Sediments Using Machine Learning Techniques for CO2 Storage Characterization B Benjumea, H Bedle, E Llave, FJ Hernández-Molina, ZL Ng, ... The Fourth EAGE Global Energy Transition Conference and Exhibition 2023 (1), 1-5, 2023 | | 2023 |
| Combining seismic attributes and machine learning for seismic facies analysis D Lubo-Robles | | 2022 |
Matthew J. PranterProfessor and Victor E. Monnett Endowed Chair, School of Geosciences, University of OklahomaVerified email at ou.edu
