| Earth modeling methods using machine learning BF Zhang, O De Jesus, TA Sansal, D Chen, T Edward, M Unaldi US Patent 11,704,579, 2023 | 15 | 2023 |
| MDIO: Open-source format for multidimensional energy data A Sansal, S Kainkaryam, B Lasscock, A Valenciano The Leading Edge 42 (7), 465-473, 2023 | 5 | 2023 |
| Improved stratigraphic interpretation using broadband processing–Sergipe Basin, Brazil M Saunders, L Geiger, D Negri, JA Stein, TA Sansal, J Springman first break 33 (3), 2015 | 5 | 2015 |
| Toward generalized models for machine-learning-assisted salt interpretation in the Gulf of Mexico C Warren, S Kainkaryam, B Lasscock, A Sansal, S Govindarajan, ... The Leading Edge 42 (6), 390-396, 2023 | 3 | 2023 |
| Seeing-ahead-of-the-bit: A game changer enabled by Machine Learning G Taylor, B Zhang, M Unaldi, E Tian, E Alvarez, A Sansal ARMA US Rock Mechanics/Geomechanics Symposium, ARMA-2020-1917, 2020 | 3 | 2020 |
| Novel machine learning workflow for rock property prediction in the geologically complex presalt Santos basin, Brazil D Clarke, M Blaauw, J Guha, A Sansal, M Unaldi, B Zhang First International Meeting for Applied Geoscience & Energy, 1520-1524, 2021 | 2 | 2021 |
| Integrating Energy Datasets: The MDIO format A Sansal, B Lasscock, A Valenciano First Break 41 (10), 69-75, 2023 | 1 | 2023 |
| A 2-Stage Approach to Broadband Processing for Improved Stratigraphic Interpretation in the Sergipe Basin, Brazil M Saunders, L Geiger, JA Stein, TA Sansal, J Springman 14th International Congress of the Brazilian Geophysical Society & EXPOGEF …, 2015 | 1 | 2015 |
| Deghosting Ultra High Resolution 3D Geo Hazard Data KJ Hellman, TA Sansal, JA Stein 77th EAGE Conference and Exhibition 2015 2015 (1), 1-5, 2015 | 1 | 2015 |
| Encoding the Subsurface in 3D with Seismic B Lasscock, A Sansal, A Valenciano arXiv preprint arXiv:2403.13593, 2024 | | 2024 |
| Quantifying observational relevance and uncertainty along the US East Coast using a suite of floating LiDAR buoys K Brennan, SJ Eichelberger, P Khapikova, A Sansal, B Lasscock 104th AMS Annual Meeting, 2024 | | 2024 |
| Confidence volumes for earth modeling using machine learning BF Zhang, O De Jesus, TA Sansal, T Edward US Patent 11,699,099, 2023 | | 2023 |
| Earth Model Building in Real-Time with an Automated Machine Learning Framework–A Midland Basin Example A Sansal, M Unaldi, E Tian, G Taylor SPE/AAPG/SEG Unconventional Resources Technology Conference, D021S025R004, 2021 | | 2021 |
| A novel prestack sparse azimuthal AVO inversion BG Lasscock, TA Sansal arXiv preprint arXiv:1710.04104, 2017 | | 2017 |
| Contribution of Seismic Amplitude Anomaly Information in Prospect Risk Analysis TA Sansal | | 2014 |
