scholarly journals Using SAS functions and high-resolution isotope data to unravel travel time distributions in headwater catchments

2017 ◽  
Vol 53 (3) ◽  
pp. 1864-1878 ◽  
Author(s):  
Paolo Benettin ◽  
Chris Soulsby ◽  
Christian Birkel ◽  
Doerthe Tetzlaff ◽  
Gianluca Botter ◽  
...  
Keyword(s):  
High Resolution ◽  
Travel Time ◽  
Headwater Catchments ◽  
Isotope Data

High‐Resolution Lithospheric Velocity Structure of Continental China by Double‐Difference Seismic Travel‐Time Tomography

2018 ◽  
Vol 90 (1) ◽  
pp. 229-241 ◽  
Author(s):  
Hailiang Xin ◽  
Haijiang Zhang ◽  
Min Kang ◽  
Rizheng He ◽  
Lei Gao ◽  
...  
Keyword(s):  
High Resolution ◽  
Travel Time ◽  
Velocity Structure ◽  
Double Difference ◽  
Travel Time Tomography

Extended use of migration based travel time approach for inversion of very high resolution seismics

1996 ◽  
Author(s):  
Yann‐Hervé De Roeck ◽  
René‐Edouard Plessix ◽  
Guy Chavent
Keyword(s):  
High Resolution ◽  
Travel Time ◽  
Very High

scholarly journals Electromagnetic wave speed in polar ice: validation of the common-midpoint technique with high-resolution dielectric-profiling and γ-density measurements

2002 ◽  
Vol 34 ◽  
pp. 150-156 ◽  
Author(s):  
O. Eisen ◽  
U. Nixdorf ◽  
F. Wilhelms ◽  
H. Miller
Keyword(s):  
High Resolution ◽  
Travel Time ◽  
Ice Core ◽  
Field Measurements ◽  
Complex Dielectric Constant ◽  
Density Data ◽  
Density Measurements ◽  
Drilling Site ◽  
Interval Velocities ◽  
Ground Penetrating

AbstractThe accuracy of the travel-time–velocity and travel-time–depth profile derived from ground-penetrating radar (GPR) common-midpoint (CMP) surveys at different frequencies is investigated for the first time ever by direct comparison with the profile calculated from high-resolution dielectric-profiling (DEP) ice-core data. In addition, we compare two travel-time profiles calculated from ice-core density data by means of different dielectrical mixture models with the DEP-based profile. CMP surveys were carried out at frequencies of 25,50,100 and 200 MHz near the new European deep-drilling site DML05 in Dronning Maud Land, Antarctica, during the 1998/99 field season. An improved scanning capacitor for high-resolution DEP and a γ-densiometer for density measurements were used to determine the complex dielectric constant and the density at 5 mm increments along the ice core B32, retrieved in 1997/98 at DML05. The comparisons with DEP- and density-based velocity series show that the CMP velocity series are slightly higher but asymptotically approach the core-based velocities with depth. Root-mean-square differences of the DEP velocity series range between 8% for the 25 MHz CMP and 2% in the case of the 200 MHz survey. Density-based velocities differ from the DEP velocities by 51 %. The travel-time–depth series calculated from the interval velocities show a better agreement between all series than the velocity series. Differences are 5.7–1.4% for the 25 and 200 MHz CMP measurements, and <0.6% for the density data. Based on these comparisons, we evaluate the accuracy with which the depth of electromagnetic reflectors observed in common-offset profiles can be determined, and discuss reasons for the observed differences between CMP- and core-based profiles. Moreover, we compare the errors determined from the field measurements with those estimated from GPR system characteristics to provide a measure that can be used to estimate the accuracy of GPR analyses for the planning of GPR campaigns. Our results show that CMP surveys are a useful technique to determine the depth of radar reflectors in combination with common-offset measurements, especially on a region-wide basis.

scholarly journals Using high-resolution isotope data and alternative calibration strategies for a tracer-aided runoff model in a nested catchment

2017 ◽  
Vol 31 (22) ◽  
pp. 3962-3978 ◽  
Author(s):  
Claire Tunaley ◽  
Doerthe Tetzlaff ◽  
Christian Birkel ◽  
Chris Soulsby
Keyword(s):  
High Resolution ◽  
Isotope Data ◽  
Runoff Model

scholarly journals High-resolution seismic tomography of Long Beach, CA using machine learning

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Michael J. Bianco ◽  
Peter Gerstoft ◽  
Kim B. Olsen ◽  
Fan-Chi Lin
Keyword(s):  
Machine Learning ◽  
High Resolution ◽  
Travel Time ◽  
Phase Speed ◽  
Small Scale ◽  
Long Beach ◽  
Travel Time Tomography ◽  
Tomography Method ◽  
Dense Sampling ◽  
Geophysical Features

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.

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