Geophysical features of the northern Appalachian transect

Author(s):  
Wallace A. Bothner ◽  
John D. Unger
Keyword(s):  
1999 ◽  
Vol 93 (1-2) ◽  
pp. 75-92 ◽  
Author(s):  
Hubert Fabriol ◽  
Luis A Delgado-Argote ◽  
Juan José Dañobeitia ◽  
Diego Córdoba ◽  
Antonio González ◽  
...  

2020 ◽  
Vol 2 (1) ◽  
Author(s):  
Ahmed Babeker Elhag

The geology and hydro-geophysical features can aid in identifying borehole location. The study aims to investigate groundwater aquifers and best location of boreholes in the crystalline basement area of Abu Zabad near El Obeid Southwest, Sudan. The study area is underlain by two aquifers formations from Precambrian age. The oldest units of basement complex of area under investigation consist of metamorphic rocks including gneiss, schist, and quartzite.The geophysical methods electromagnetic (EM) and vertical electrical sounding (VES) surveys showed that best aquifers yield for construction of boreholes are in weathering and fractures formation. The EM results revealed that structural features are significant for groundwater potential and interpretation of the VES data also revealed four geo-electric layers, but generally two distinct lithologic layers, which include Superficial deposit and bedrock-basement respectively. The curves generated from the data revealed H curve and HK curve, and thickness of these layers varies from 15 m to 50 m in the area. The aquifer thickness range from 20 m to 30 m. The study concludes that these techniques are suitable for identifying borehole location in the basement rock in Abu Zabad Area Sudan.


Geotectonics ◽  
2020 ◽  
Vol 54 (2) ◽  
pp. 266-283 ◽  
Author(s):  
L. V. Eppelbaum ◽  
Y. I. Katz
Keyword(s):  

2013 ◽  
Vol 34 (22) ◽  
pp. 8215-8234 ◽  
Author(s):  
Andrea Vaccari ◽  
Michael Stuecheli ◽  
Brian Bruckno ◽  
Edward Hoppe ◽  
Scott T. Acton

2017 ◽  
Vol 121 (1-2) ◽  
pp. 45-51 ◽  
Author(s):  
Alexandra M. Schmuck ◽  
Jennifer L. Lavers ◽  
Silke Stuckenbrock ◽  
Paul B. Sharp ◽  
Alexander L. Bond

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Michael J. Bianco ◽  
Peter Gerstoft ◽  
Kim B. Olsen ◽  
Fan-Chi Lin

Abstract We use a machine learning-based tomography method to obtain high-resolution subsurface geophysical structure in Long Beach, CA, from seismic noise recorded on a “large-N” array with 5204 geophones (~13.5 million travel times). This method, called locally sparse travel time tomography (LST) uses unsupervised machine learning to exploit the dense sampling obtained by ambient noise processing on large arrays. Dense sampling permits the LST method to learn directly from the data a dictionary of local, or small-scale, geophysical features. The features are the small scale patterns of Earth structure most relevant to the given tomographic imaging scenario. Using LST, we obtain a high-resolution 1 Hz Rayleigh wave phase speed map of Long Beach. Among the geophysical features shown in the map, the important Silverado aquifer is well isolated relative to previous surface wave tomography studies. Our results show promise for LST in obtaining detailed geophysical structure in travel time tomography studies.


2000 ◽  
Vol 11 (3) ◽  
pp. 157-166
Author(s):  
Yukari KIDO ◽  
Toshihiko HIGASHIKATA ◽  
Kantaro FUJIOKA ◽  
Yoshiyuki KANEDA ◽  
Yoshiteru KONO ◽  
...  

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