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20172025
most citedOn modelling bicycle power-meter measurements: Part I. Estimating effects of air, rolling and drivetrain resistance

3 citations · 7 across the 8 of their papers we have counts for

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8 papers · 1 filter

physics.geo-ph2020

Selecting velocity models using Bayesian Information Criterion

Tomasz Danek, Bartosz Gierlach, Ayiaz Kaderali +2

We present a strategy for selecting the values of elasticity parameters by comparing walk-away vertical seismic profiling data with a multilayered model in the context of Bayesian…

physics.geo-ph2020

On anisotropy and inhomogeneity parameter estimation using traveltimes

Ayiaz Kaderali, Theodore Stanoev

We consider an anisotropic inhomogeneous model to simulate measured vertical-seismic-profile traveltimes. In this model, we assume that velocity increases linearly with depth and a…

physics.geo-ph2019

On relations of anisotropy and linear inhomogeneity using Backus average

Md Abu Sayed, Theodore Stanoev

The anisotropy of an equivalent medium resulting from the Backus (1962) average is induced by the vertical inhomogeneity among its constituent layers. The velocity field of the con…

physics.geo-ph2019

On orthogonal transformations of Christoffel equations

Len Bos, Michael A. Slawinski, Theodore Stanoev +1

The purpose of this paper is to prove the equivalenceunder rotations of distinct termsof different forms of a determinantal equation that appears in the studies of wave propa…

physics.geo-ph2018

On the Backus average of layers with randomly oriented elasticity tensors

Len Bos, Michael A. Slawinski, Theodore Stanoev

As shown by Backus (1962), the average of a stack of isotropic layers results in a transversely isotropic medium. Herein, we consider a stack of layers consisting of a randomly ori…

physics.geo-ph2018

On possible issues of Backus average

Ayiaz Kaderali, Izabela Kudela, Theodore Stanoev

In this paper, we continue the study of Bos et al. (2018) regarding statistical and numerical considerations of the Backus (1962) product approximation. While the approximation is…