@article{AllroggenHeinckeKoyanetal.2022,
  author    = {Allroggen, Niklas and Heincke, Bjorn H. and Koyan, Philipp and Wheeler, Walter and Ronning, Jan S.},
  title     = {3D ground-penetrating radar attribute classification},
  series = {Geophysics},
  volume    = {87},
  journal   = {Geophysics},
  number    = {4},
  publisher = {Society of Exploration Geophysicists},
  address   = {Tulsa},
  issn      = {0016-8033},
  doi       = {10.1190/GEO2021-0651.1},
  pages     = {WB19 -- WB30},
  year      = {2022},
  abstract  = {Ground-penetrating radar (GPR) is a method that can provide detailed information about the near subsurface in sedimentary and carbonate environments. The classical interpretation of GPR data (e.g., based on manual feature selection) often is labor-intensive and limited by the experience of the intercally used for seismic interpretation, can provide faster, more repeatable, and less biased interpretations. We have recorded a 3D GPD data set collected across a paleokarst breccia pipe in the Billefjorden area on Spitsbergen, Svalbard. After performing advanced processing, we compare the results of a classical GPR interpretation to the results of an attribute-based classification. Our attribute classification incorporates a selection of dip and textural attributes as the input for a k-means clustering approach. Similar to the results of the classical interpretation, the resulting classes differentiate between undisturbed strata and breccias or fault zones. The classes also reveal details inside the breccia pipe that are not discerned in the classical fer that the intrapipe GPR facies result from subtle differences, such as breccia lithology, clast size, or pore-space filling.},
  language  = {en}
}