3-D inversion of airborne electromagnetic data parallelized and accelerated by local mesh and adaptive soundings D Yang, DW Oldenburg, E Haber Geophysical Journal International 196 (3), 1942-1507, 2014 | 178 | 2014 |
Three-dimensional inversion of airborne time-domain electromagnetic data with applications to a porphyry deposit D Yang, DW Oldenburg Geophysics 77 (2), B23-B34, 2012 | 172 | 2012 |
3D DC resistivity modeling of steel casing for reservoir monitoring using equivalent resistor network D Yang, D Oldenburg, L Heagy SEG Technical Program Expanded Abstracts 2016, 932-936, 2016 | 36 | 2016 |
3D inversion of total magnetic intensity data for time-domain EM at the Lalor massive sulphide deposit D Yang, DW Oldenburg Exploration Geophysics 48 (2), 110-123, 2017 | 29 | 2017 |
Review of development of surface nuclear magnetic resonance R ZHANG, X HU, D YANG, X HAO, M DAI Progress in Geophysics 1, 042, 2006 | 26 | 2006 |
Survey decomposition: A scalable framework for 3D controlled-source electromagnetic inversion D Yang, DW Oldenburg Geophysics 81 (2), E69-E87, 2016 | 24 | 2016 |
Electrical imaging of hydraulic fracturing fluid using steel-cased wells and a deep-learning method Y Li, D Yang Geophysics 86 (4), E315-E332, 2021 | 23 | 2021 |
Deep mineral exploration using multi-scale electromagnetic geophysics: The Lalor massive sulphide deposit case study D Yang, D Fournier, S Kang, DW Oldenburg Canadian Journal of Earth Sciences, 2018 | 23 | 2018 |
3-D Numerical Study on Controlled Source Electromagnetic Monitoring of Hydraulic Fracturing Fluid With the Effect of Steel-Cased Wells Y Hu, D Yang, Y Li, Z Wang, Y Lu IEEE Transactions on Geoscience and Remote Sensing 60, 1-10, 2022 | 20 | 2022 |
The developing trends of environmental and engineering geophysics HU Xiang-yun, Y Di-kun, LIU Shao-hua, HU Zheng-wang PROGRESS IN GEOPHYSICS, 598-604, 2006 | 19* | 2006 |
3D conductivity model of the Lalor Lake VMS deposit using ground and airborne EM data D Yang, D Oldenburg ASEG Extended Abstracts 2013 (1), 1-4, 2013 | 17 | 2013 |
Inversion of noisy data by probabilistic methodology Y Di-Kun, H Xiang-Yun CHINESE JOURNAL OF GEOPHYSICS-CHINESE EDITION 51 (3), 901-907, 2008 | 17* | 2008 |
1-D Controlled source electromagnetic forward modeling for marine gas hydrates studies Z Luanxiao, G Jianhua, Z Shengye, Y Dikun Applied Geophysics 5 (2), 121-126, 2008 | 16 | 2008 |
Inversion of surface nuclear magnetic resonance M DAI, XY HU, HB WU, LC JIANG, DK YANG Acta Geophysica 52 (10), 2009 | 15 | 2009 |
Interpreting Surface Large-Loop Time-Domain Electromagnetic Data for Deep Mineral Exploration Using 3D Forward Modeling and Inversion M Cheng, D Yang, Q Luo Minerals 13 (1), 34, 2023 | 13 | 2023 |
Practical 3D inversion of large airborne time domain electromagnetic data sets D Yang, DW Oldenburg ASEG Extended Abstracts 2012 (1), 1-4, 2012 | 10 | 2012 |
Lighting Up a 1 km Fault near a Hydraulic Fracturing Well Using a Machine Learning‐Based Picker R Wang, D Yang, Y Chen, C Ren Seismological Research Letters 94 (4), 1836-1847, 2023 | 9 | 2023 |
Joint 3D inversion of gravity and magnetic data using deep learning neural networks N Wei, D Yang, Z Wang, Y Lu Second International Meeting for Applied Geoscience & Energy, 1457-1461, 2022 | 7 | 2022 |
Modeling and Inversion of Airborne and Semi-Airborne Transient Electromagnetic Data with Inexact Transmitter and Receiver Geometries T Chen, D Yang Remote Sensing 14 (4), 915, 2022 | 7 | 2022 |
On Recovering Induced Polarization Information From Airborne Time Domain EM Data S Kang, D Oldenburg, D Yang, D Marchant 2014 SEG Annual Meeting, 2014 | 7 | 2014 |