Artificial intelligence techniques to the interpretation of geophysical measurements
Author:
Affiliation:
1. Intrepid Geophysics 110,3 Male Street, Brighton, VIC 3186
Publisher
Informa UK Limited
Link
https://www.tandfonline.com/doi/pdf/10.1080/22020586.2019.12073000
Reference11 articles.
1. Calcagno, P., Courrioux, G., Guillen, A., Chiles, J.P., 2008. Geological modelling from field data and geological knowledge. Part I. Modelling method coupling 3D potentialfield interpolation and geological rules. Physics of the earth and planetary interiors. Vol 171
2. FitzGerald, D. Holstein, H., Foss, C., 2011, Automatic modelling and inversion for dykes from magnetic tensor gradient profiles – recent progress: SEG Extended Abstracts, Houston.
3. FitzGerald, D., and H. Holstein, 2014, Structural geology observations derived from full tensor gravity gradiometry over rift systems: 84th SEG Annual meeting, Expanded Abstracts.
4. FitzGerald, D., Milligan, P., 2013, Defining a deep fault network for Australia, using 3D “worming”: ASEG Extended Abstracts, Melbourne.
5. Guillen, A., Calcagno, P., Courrioux, G., Joly, A., Ledru, P., 2008. Geological modelling from field data and geological knowledge, Part II. Modelling validation using gravity and magnetic data inversion. Physics of the Earth and Planetary Interiors 171, 158–169.
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