A hybrid approach for tomographic inversion of crosshole seismic first-arrival times

2011 ◽  
Vol 8 (1) ◽  
pp. 99-108 ◽  
Author(s):  
G Göktürkler
Geophysics ◽  
1996 ◽  
Vol 61 (2) ◽  
pp. 509-519 ◽  
Author(s):  
Vladimir Shtivelman

The inversion of first‐arrival times of refracted waves in media with laterally varying parameters can be performed using the refraction tomography technique. Tomographic inversion implemented as a linearized, constrained, least‐squares, iterative scheme requires some a priori information on either refractor depth or velocity above the refractor; however, such information may be unavailable. On the other hand, in many cases a reasonable estimate of the average velocity distribution above the refractor can be obtained by a nontomographic technique such as the generalized reciprocal method (GRM). I propose a combined approach to the inversion problem that uses the advantages of both the refraction tomography and GRM techniques and which does not require additional information not contained in first arrival times. The approach is based upon two assumptions (which prove to be true in most situations). The first is that a reasonable local estimate of refractor velocity can be obtained by tomographic inversion independently of other model parameters, and the second is that the derivative of the velocity analysis function as defined by the GRM, gives a good local approximation of the refractor slowness. The proposed combined inversion scheme can be described as a three‐step procedure. In the first step, the laterally varying refractor velocity is estimated by tomographic inversion. In the second step, local estimation of laterally varying average velocity above the refractor is performed by the GRM on the basis of the previously estimated refractor velocity. In the third step, the estimated values of the average velocity are used as the corresponding constrained initial parameters for tomographic inversion.


2021 ◽  
Vol 17 (1) ◽  
pp. e1008545
Author(s):  
Jun Li ◽  
Juliane Manitz ◽  
Enrico Bertuzzo ◽  
Eric D. Kolaczyk

We investigate the source detection problem in epidemiology, which is one of the most important issues for control of epidemics. Mathematically, we reformulate the problem as one of identifying the relevant component in a multivariate Gaussian mixture model. Focusing on the study of cholera and diseases with similar modes of transmission, we calibrate the parameters of our mixture model using human mobility networks within a stochastic, spatially explicit epidemiological model for waterborne disease. Furthermore, we adopt a Bayesian perspective, so that prior information on source location can be incorporated (e.g., reflecting the impact of local conditions). Posterior-based inference is performed, which permits estimates in the form of either individual locations or regions. Importantly, our estimator only requires first-arrival times of the epidemic by putative observers, typically located only at a small proportion of nodes. The proposed method is demonstrated within the context of the 2000-2002 cholera outbreak in the KwaZulu-Natal province of South Africa.


Author(s):  
Helen Steingroever ◽  
Dominik Wabersich ◽  
Eric-Jan Wagenmakers

Abstract The shifted-Wald model is a popular analysis tool for one-choice reaction-time tasks. In its simplest version, the shifted-Wald model assumes a constant trial-independent drift rate parameter. However, the presence of endogenous processes—fluctuation in attention and motivation, fatigue and boredom—suggest that drift rate might vary across experimental trials. Here we show how across-trial variability in drift rate can be accounted for by assuming a trial-specific drift rate parameter that is governed by a positive-valued distribution. We consider two candidate distributions: the truncated normal distribution and the gamma distribution. For the resulting distributions of first-arrival times, we derive analytical and sampling-based solutions, and implement the models in a Bayesian framework. Recovery studies and an application to a data set comprised of 1469 participants suggest that (1) both mixture distributions yield similar results; (2) all model parameters can be recovered accurately except for the drift variance parameter; (3) despite poor recovery, the presence of the drift variance parameter facilitates accurate recovery of the remaining parameters; (4) shift, threshold, and drift mean parameters are correlated.


Geophysics ◽  
1942 ◽  
Vol 7 (4) ◽  
pp. 393-399
Author(s):  
M. B. Dobrin

A method of weathering is described by which intercept times can be rapidly and accurately computed from first arrival times without the plotting of time‐distance curves. The velocities are determined by a mechanical procedure, based on least squares theory, which normally requires no exercise of judgment on the part of the computer. The application of the method to actual field set‐ups is illustrated by sample calculations.


Geophysics ◽  
2017 ◽  
Vol 82 (4) ◽  
pp. V257-V274
Author(s):  
Necati Gülünay

The diminishing residual matrices (DRM) method can be used to surface-consistently decompose individual trace statics into source and receiver components. The statics to be decomposed may either be first-arrival times after the application of linear moveout associated with a consistent refractor as used in refraction statics or residual statics obtained by crosscorrelating individual traces with corresponding model traces (known as pilot traces) at the same common-midpoint (CMP) location. The DRM method is an iterative process like the well-known Gauss-Seidel (GS) method, but it uses only source and receiver terms. The DRM method differs from the GS method in that half of the average common shot and receiver terms are subtracted simultaneously from the observations at each iteration. DRM makes the under-constrained statics problem a constrained one by implicitly adding a new constraint, the equality of the contribution of shots and receivers to the solution. The average of the shot statics and the average of the receiver statics are equal in the DRM solution. The solution has the smallest difference between shot and receiver statics profiles when the number of shots and the number of receivers in the data are equal. In this case, it is also the smallest norm solution. The DRM method can be derived from the well-known simultaneous iterative reconstruction technique. Simple numerical tests as well as results obtained with a synthetic data set containing only the field statics verify that the DRM solution is the same as the linear inverse theory solution. Both algorithms can solve for the long-wavelength component of the statics if the individual picks contain them. Yet DRM method is much faster. Application of the method to the normal moveout-corrected CMP gathers on a 3D land survey for residual statics calculation found that pick-decompose-apply-stack stages of the DRM method need to be iterated. These iterations are needed because of time and waveform distortions of the pilot traces due to the individual trace statics. The distortions lessen at every external DRM iteration.


Sign in / Sign up

Export Citation Format

Share Document