Characterization of the bridge pillar foundations using 3d focusing inversion of DC resistivity data

GÜNDOĞDU N. Y., DEMİRCİ İ., Demirel C., CANDANSAYAR M. E.

JOURNAL OF APPLIED GEOPHYSICS, cilt.172, 2020 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 172
  • Basım Tarihi: 2020
  • Doi Numarası: 10.1016/j.jappgeo.2019.103875
  • Dergi Adı: JOURNAL OF APPLIED GEOPHYSICS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Aquatic Science & Fisheries Abstracts (ASFA), Compendex, Geobase, INSPEC
  • Anahtar Kelimeler: DC resistivity, Focusing inversion, Minimum gradient support, SHARP BOUNDARY INVERSION, MAGNETOTELLURIC DATA, CONJUGATE-GRADIENT, 2D INVERSION, STABILITY
  • Ankara Üniversitesi Adresli: Evet

Özet

We investigated the effectiveness of a focusing regularization technique for the inversion of direct current (DC) resistivity data for a typical engineering problem. A smoothing stabilizer (Laplacian of model parameters) is generally preferred in the inversion (OCCAM's inversion) of DC resistivity data. Smooth reconstructions may be produced with this stabilizer, but some specific problems might require more focused images for adequate interpretations. For this reason, we investigated the capabilities of the minimum gradient support (MGS) stabilizer for providing shaper results. This stabilizer allows the a sharper reconstruction because its main effect is to minimize the area where strong differences occur between adjacent model parameters. We also analyze the effects of the focusing parameter, which is the parameter in the MGS expression controlling the level of sharpness of the final result. Our strategy for the selection of the optimal focusing parameter allows the resolution of distinct resistivity contrasts. Moreover, some artifacts that may arise in the use of the a very small focusing parameter disappear while using the normalized focusing parameter. We demonstrate these results by using both synthetic and field data examples. In the field data test, the subsurface image reconstructed using the proposed MGS approach matches well with the lithology inferred from borehole drillings. (C) 2019 Elsevier B.V. All rights reserved.