Asymptotic behavior of vertical travel-time sensitivity kernels with increasing propagation range

2011 ◽  
Vol 130 (4) ◽  
pp. 2392-2392
Author(s):  
E. K. Skarsoulis ◽  
B. D. Cornuelle ◽  
M. A. Dzieciuch
Keyword(s):  
Asymptotic Behavior ◽  
Travel Time ◽  
Time Sensitivity ◽  
Vertical Travel

Long-range asymptotic behavior of vertical travel-time sensitivity kernels

2013 ◽  
Vol 134 (4) ◽  
pp. 3201-3210 ◽  
Author(s):  
E. K. Skarsoulis ◽  
B. D. Cornuelle ◽  
M. A. Dzieciuch
Keyword(s):  
Asymptotic Behavior ◽  
Travel Time ◽  
Long Range ◽  
Time Sensitivity ◽  
Vertical Travel

A VELOCITY FUNCTION INCLUDING LITHOLOGIC VARIATION

Geophysics ◽  
1953 ◽  
Vol 18 (2) ◽  
pp. 271-288 ◽  
Author(s):  
L. Y. Faust
Keyword(s):  
Travel Time ◽  
Direct Measurement ◽  
General Knowledge ◽  
Velocity Function ◽  
Geologic Time ◽  
True Resistivity ◽  
Resistivity Log ◽  
Vertical Travel ◽  
Water Resistivity

Assuming velocity (V) a function of depth (Z), geologic time (T), and lithology (L) the resistivity log is an approach to the determination of L. Since general knowledge of water resistivity values [Formula: see text] is lacking, the values of true resistivity [Formula: see text] against [Formula: see text] were compared for 670,000 feet of section widely distributed geographically. Variations in [Formula: see text] were presumably averaged out thereby, and the results indicate that statistically [Formula: see text] and [Formula: see text] This formula was applied to an additional 270,000 feet of section more localized geographically to observe its accuracy in predicting vertical travel time. If a correction map for [Formula: see text] variations is applied the results are encouraging but less accurate than good velocity surveys. Examination of an inconclusively small amount of data with more careful measurements of [Formula: see text] suggests that accuracy comparable to direct measurement may be attainable. The cooperation of other investigators and of the electric‐logging specialists is desired.

Travel‐time sensitivity kernels in long‐range propagation

2008 ◽  
Vol 123 (5) ◽  
pp. 3913-3913
Author(s):  
Emmanuel Skarsoulis ◽  
Bruce Cornuelle ◽  
Matthew Dzieciuch
Keyword(s):  
Travel Time ◽  
Long Range ◽  
Time Sensitivity

Travel Time Sensitivity Kernels

2001 ◽  
pp. 193-201
Author(s):  
A. C. Birch ◽  
A. G. Kosovichev
Keyword(s):  
Travel Time ◽  
Time Sensitivity

Travel-Time Sensitivity Kernels In Long-Range Propagation

2007 ◽  
Author(s):  
Emmanuel Skarsoulis ◽  
Bruce Cornuelle
Keyword(s):  
Travel Time ◽  
Long Range ◽  
Time Sensitivity

scholarly journals INVESTIGATIONS INTO VERTICAL TRAVEL TIME OF THE FRONT OF BUOYANT FIRE PLUMES

1997 ◽  
Vol 62 (502) ◽  
pp. 1-8 ◽  
Author(s):  
Takashi FUJITA ◽  
Jun-ichi YAMAGUCHI ◽  
Takeyoshi TANAKA ◽  
Takao WAKAMATSU
Keyword(s):  
Travel Time ◽  
Fire Plumes ◽  
Vertical Travel

Travel-time sensitivity kernels in ocean acoustic tomography

2004 ◽  
Vol 116 (1) ◽  
pp. 227-238 ◽  
Author(s):  
E. K. Skarsoulis ◽  
B. D. Cornuelle
Keyword(s):  
Travel Time ◽  
Acoustic Tomography ◽  
Time Sensitivity ◽  
Ocean Acoustic Tomography

scholarly journals Sensitivity kernels for time-distance helioseismology

2018 ◽  
Vol 616 ◽  
pp. A156 ◽  
Author(s):  
Damien Fournier ◽  
Chris S. Hanson ◽  
Laurent Gizon ◽  
Hélène Barucq
Keyword(s):  
Travel Time ◽  
Born Approximation ◽  
Computation Time ◽  
Meridional Flow ◽  
Solar Interior ◽  
Computationally Efficient ◽  
Time Sensitivity ◽  
Wave Travel ◽  
Harmonic Decomposition ◽  
Time Distance

Context. The interpretation of helioseismic measurements, such as wave travel-time, is based on the computation of kernels that give the sensitivity of the measurements to localized changes in the solar interior. These kernels are computed using the ray or the Born approximation. The Born approximation is preferable as it takes finite-wavelength effects into account, although it can be computationally expensive. Aims. We propose a fast algorithm to compute travel-time sensitivity kernels under the assumption that the background solar medium is spherically symmetric. Methods. Kernels are typically expressed as products of Green’s functions that depend upon depth, latitude, and longitude. Here, we compute the spherical harmonic decomposition of the kernels and show that the integrals in latitude and longitude can be performed analytically. In particular, the integrals of the product of three associated Legendre polynomials can be computed. Results. The computations are fast and accurate and only require the knowledge of the Green’s function where the source is at the pole. The computation time is reduced by two orders of magnitude compared to other recent computational frameworks. Conclusions. This new method allows flexible and computationally efficient calculations of a large number of kernels, required in addressing key helioseismic problems. For example, the computation of all the kernels required for meridional flow inversion takes less than two hours on 100 cores.

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