Stochastic simulation by image quilting of process-based geological models J Hoffimann, C Scheidt, A Barfod, J Caers Computers & Geosciences 106, 18-32, 2017 | 44 | 2017 |
Compiling a national resistivity atlas of Denmark based on airborne and ground-based transient electromagnetic data AAS Barfod, I Møller, AV Christiansen Journal of Applied Geophysics 134, 199-209, 2016 | 40 | 2016 |
Hydrostratigraphic modeling using multiple-point statistics and airborne transient electromagnetic methods AAS Barfod, I Møller, AV Christiansen, AS Høyer, J Hoffimann, ... Hydrology and Earth System Sciences 22 (6), 3351-3373, 2018 | 35 | 2018 |
Machine learning based fast forward modelling of ground-based time-domain electromagnetic data TS Bording, MR Asif, AS Barfod, JJ Larsen, B Zhang, DJ Grombacher, ... Journal of Applied Geophysics 187, 104290, 2021 | 21 | 2021 |
Contributions to uncertainty related to hydrostratigraphic modeling using Multiple-Point Statistics AAS Barfod, TN Vilhelmsen, F Jørgensen, AV Christiansen, J Straubhaar, ... | 21* | |
Combining clustering methods with MPS to estimate structural uncertainty for hydrological models TN Vilhelmsen, E Auken, AV Christiansen, AS Barfod, PA Marker, ... Frontiers in Earth Science 7, 181, 2019 | 17 | 2019 |
Effect of data pre-processing on the performance of neural networks for 1-D transient electromagnetic forward modeling MR Asif, TS Bording, AS Barfod, DJ Grombacher, PK Maurya, ... IEEE Access 9, 34635-34646, 2021 | 15 | 2021 |
Automatic processing of time domain induced polarization data using supervised artificial neural networks AS Barfod, L Lévy, JJ Larsen Geophysical Journal International 224 (1), 312-325, 2021 | 13 | 2021 |
Successful sampling strategy advances laboratory studies of NMR logging in unconsolidated aquifers AA Behroozmand, R Knight, M Müller‐Petke, E Auken, AAS Barfod, ... Geophysical Research Letters 44 (21), 11,021-11,029, 2017 | 8 | 2017 |
Improving computational efficiency of forward modelling for ground-based time-domain electromagnetic data using neural networks T Sylvester Bording, AS Barfod, B Zhang, JJ Larsen, E Auken EGU General Assembly Conference Abstracts, 7067, 2020 | 1 | 2020 |
Effect of Data Normalization on Neural Networks for the Forward Modelling of Transient Electromagnetic Data MR Asif, TS Bording, AS Barfod, E Auken, JJ Larsen NSG2020 26th European Meeting of Environmental and Engineering Geophysics …, 2020 | | 2020 |
Automating the pre-processing of time-domain induced polarization data using machine learning JJ Larsen EGU General Assembly Conference Abstracts, 6922, 2020 | | 2020 |
Quantification of subsurface structural uncertainty in groundwater models using 3D geophysical data TN Vilhelmsen, E Auken, AV Christiansen, A Barfod, N Foged, J Pedersen, ... | | 2018 |
Investigating lithological and geophysical relationships with applications to geological uncertainty analysis using Multiple-Point Statistical methods A Barfod Aarhus universitet, 2017 | | 2017 |
A detailed comparison of laboratory and borehole NMR estimated parameters in unconsolidated aquifers AA Behroozmand, E Auken, AV Christiansen, M Müller-Petke, ... AGU Fall Meeting Abstracts 2016, NS32A-07, 2016 | | 2016 |
Geostatistical analysis of the relationship between airborne electromagnetic data and borehole lithological data AAS Barfod, I Møller, AV Christiansen ASEG Extended Abstracts 2015 (1), 1-4, 2015 | | 2015 |
Geostatistical analysis of the relationship between airborne Geostatistical analysis of the relationship between airborne electromagnetic data and borehole lithological data AAS Barfod, I Møller, AV Christiansen ASEG Extended Abstracts 2015 (1), 1-4, 2015 | | 2015 |
An analysis of the lithology to resistivity relationships using airborne EM and boreholes AAS Barfod, AV Christiansen, I Møller EGU General Assembly Conference Abstracts, 3752, 2014 | | 2014 |
Automatic processing of time domain induced polarization data using AS Barfod, L Lévy, JJ Larsen Geophysical Journal International, 0 | | |