Japan Geoscience Union Meeting 2022

Presentation information

[J] Poster

H (Human Geosciences ) » H-TT Technology & Techniques

[H-TT20] New Developments in Shallow Geophysics

Thu. Jun 2, 2022 11:00 AM - 1:00 PM Online Poster Zoom Room (20) (Ch.20)

convener:Kyosuke Onishi(Public Works Research Institute), convener:Tishiyuki Yokota(National Institute of Advanced Industrial Science and Technology), Shinichiro Iso(Fukada Geological Institute), convener:Hiroshi Kisanuki(OYO corporation), Chairperson:Toshiyuki Yokota(National Institute of Advanced Industrial Science and Technology), Kyosuke Onishi(Public Works Research Institute)

11:00 AM - 1:00 PM

[HTT20-P03] Probabilistic soil type estimation from three-dimensional integrated geophysical survey and database

*Chisato Konishi1, Hiroshi Kisanuki1, Kazunori Takahashi1, Ken Sakurai1, Syoichi Nishiyama1, Hiromasa Shima1 (1.OYO Corporation)

Keywords:3-dimensional geophysical survey, database, integrated geophysical survey, uncertainty

A three-dimensional integrated geophysical survey, a combination of a 3D microtremor array survey using node type receivers and a 3D resistivity survey using a distributed transmitter/receiver system, was carried out at OYO Corporation’s Tsukuba property. The survey area was 120 m x 40 m, and the investigation depth was 30 m. The probabilistic soil type was estimated by comparing the obtained S-wave velocity and resistivity with a two-dimensional probability distribution created from the database of integrated geophysical surveys conducted at river levees. The investigation depth was deeper than the depth covered by the database; thus, the obtained S-wave velocity was corrected by assuming an effect of the confining pressure, and then it was compared with the S-wave velocity in the database. As a result, reasonable soil type distribution for each soil type, gravel, sand, and clay, was estimated. The result would be used for different problems such as permeability estimation, liquefaction, and compaction depending on a purpose of a project. A soil type showing the highest probability among the three soil types can be interpreted as the most probable soil type. In addition, the probability for each soil type is transformed to RGB color, and the blended color shows the ambiguity of the estimated soil type distribution. Moreover, the reliability of the result is displayed using the opacity of the voxel. These expressions help evaluate the geological risks and show uncertainty in the 3D geological model.