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Bulbul Ahmmed
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Year
Chemical effects of carbon dioxide sequestration in the Upper Morrow Sandstone in the Farnsworth, Texas, hydrocarbon unit
B Ahmmed, MS Appold, T Fan, BJOL McPherson, RB Grigg, MD White
Environmental Geosciences 23 (2), 81-93, 2016
272016
Discovering signatures of hidden geothermal resources based on unsupervised learning
VV Vesselinov, MK Mudunuru, B Ahmmed, S Karra, RS Middleton
,”, 2020
122020
Machine learning to identify geologic factors associated with production in geothermal fields: a case-study using 3D geologic data, Brady geothermal field, Nevada
DL Siler, JD Pepin, VV Vesselinov, MK Mudunuru, B Ahmmed
Geothermal Energy 9 (1), 1-17, 2021
112021
Numerical modeling of CO2-water-rock interactions in the Farnsworth
B Ahmmed
Texas hydrocarbon unit, USA: Master’s thesis, University of Missouri—Columbia, 2015
92015
Numerical modeling of CO2-water-rock interactions in the Farnsworth, Texas hydrocarbon unit, USA
B Ahmmed
University of Missouri--Columbia, 2015
82015
A comparative study of machine learning models for predicting the state of reactive mixing
B Ahmmed, MK Mudunuru, S Karra, SC James, VV Vesselinov
Journal of Computational Physics 432, 110147, 2021
62021
Prospectivity Analyses of the Utah FORGE Site using Unsupervised Machine Learning
B Ahmmed, VV Vesselinov
Geothermal Rising, San Diego, CA, 2021
62021
Unsupervised machine learning to discover attributes that characterize low, moderate, and high-temperature geothermal resources
V Vesselinov, B Ahmmed, MK Mudunuru
Geotherm Resour Council Trans 44, 1363, 2020
62020
Geochemical characteristics of low-, medium-, and hot-temperature geothermal resources of the Great Basin, USA
B Ahmmed, VV Vesselinov, MM Mudunuru, RS Middleton, S Karra
Los Alamos National Lab.(LANL), Los Alamos, NM (United States), 2020
52020
Hidden Geothermal Signatures of the southwest New Mexico
VV Vesselinov, B Ahmmed, MM Mudunuru, S Karra, RS Middleton
Los Alamos National Lab.(LANL), Los Alamos, NM (United States), 2020
52020
Unsupervised machine learning to extract dominant geothermal attributes in Hawaii Island Play Fairway data
B Ahmmed, N Lautze, VV Vesselinov, D Dores, MK Mudunuru
Proceedings of the Geothermal Resources Council’s Annual Meeting & Expo …, 2020
52020
Unsupervised machine learning to extract dominant geothermal attributes in Hawaii Island Play Fairway data. Geothermal Resources Council, Reno, NV
B Ahmmed, N Lautze, V Vesselinov, D Dores, M Mudunuru
October, 2020
52020
Machine learning to characterize regional geothermal reservoirs in the western USA. Fall Conference, Geological Society of America, Abstract T185-358249
B Ahmmed, V Vesselinov, M MK
October, 2020
52020
Non-negative matrix factorization to discover dominant attributes in Utah FORGE Data. Geothermal Resources Council, Reno, NV
B Ahmmed, V Vesselinov, M MK
October, 2020
52020
Integration of data, numerical inversion, and unsupervised machine learning to identify hidden geothermal resources in southwest New Mexico
B Ahmmed, MK Mudunuru, VV Vesselinov
AGU Fall Meeting 2020, 2020
42020
Machine learning to discover mineral trapping signatures due to CO2 injection
B Ahmmed, S Karra, VV Vesselinov, MK Mudunuru
International Journal of Greenhouse Gas Control 109, 103382, 2021
32021
Non-negative matrix factorization to discover dominant attributes in Utah FORGE Data
B Ahmmed, V Vesselinov, M Mudunuru
Geotherm Resour Council Trans 44, 1281, 2020
32020
AdjointNet: Constraining machine learning models with physics-based codes
S Karra, B Ahmmed, MK Mudunuru
arXiv preprint arXiv:2109.03956, 2021
22021
Machine learning to characterize regional geothermal reservoirs in the western USA
B Ahmmed, V Vesselinov, M Mudunuru
Fall conference, Geological Society of America, Abstract T185-358249, 2020
22020
Hydrological perspectives on integrated, coordinated, open, networked (ICON) science
BS Acharya, B Ahmmed, Y Chen, JH Davison, L Haygood, RT Hensley, ...
Earth and Space Science 9 (4), e2022EA002320, 2022
12022
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Articles 1–20