scholarly journals Evaluation of partial k-space strategies to speed up time-domain EPR imaging

2012 ◽  
Vol 70 (3) ◽  
pp. 745-753 ◽  
Author(s):  
Sankaran Subramanian ◽  
Gadisetti V. R. Chandramouli ◽  
Alan McMillan ◽  
Rao P. Gullapalli ◽  
Nallathamby Devasahayam ◽  
...  
Keyword(s):  
Speed Up ◽  
Geophysics ◽  
2021 ◽  
pp. 1-45
Author(s):  
Hai Li ◽  
Guoqiang Xue ◽  
Wen Chen

The Bayesian method is a powerful tool to estimate the resistivity distribution and associate uncertainty from time-domain electromagnetic (TDEM) data. As the forward simulation of the TDEM method is computationally expensive and a large number of samples are needed to globally explore the model space, the full Bayesian inversion of TDEM data is limited to layered models. To make high-dimensional Bayesian inversion tractable, we propose a divide-and-conquer strategy to speed up the Bayesian inversion of TDEM data. First, the full datasets and model spaces are divided into disjoint batches based on the coverage of the sources so that independent and highly efficient Bayesian subsampling can be conducted. Then, the samples from each subsampling procedure are combined to get the full posterior. To obtain an asymptotically unbiased approximation to the full posterior, a kernel density product method is used to reintegrate samples from each subposterior. The model parameters and their uncertainty are estimated from the full posterior. The proposed method is tested on synthetic examples and applied to a field dataset acquired with a large fixed-loop configuration. The 2D section from the Bayesian inversion revealed several mineralized zones, one of which matches well with the information from a nearby drill hole. The field example shows the ability of Bayesian inversion to infer reliable resistivity and uncertainty.


Minerals ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 218
Author(s):  
Yang Su ◽  
Changchun Yin ◽  
Yunhe Liu ◽  
Xiuyan Ren ◽  
Bo Zhang ◽  
...  

Rocks and ores in nature usually appear macro-anisotropic, especially in sedimentary areas with strong layering. This anisotropy will lead to false interpretation of electromagnetic (EM) data when inverted under the assumption of an isotropic earth. However, the time-domain (TD) airborne EM (AEM) inversion for an anisotropic model has not attracted much attention. To get reasonable inversion results from TD AEM data, we present in this paper the forward modeling and inversion methods based on a triaxial anisotropic model. We apply three-dimensional (3D) finite-difference on the secondary scattered electric field equation to calculate the frequency-domain (FD) EM responses, then we use the inverse Fourier transform and waveform convolution to obtain TD responses. For the regularized inversion, we calculate directly the sensitivities with respect to three diagonal conductivities and then use the Gauss–Newton (GN) optimization scheme to recover model parameters. To speed up the computation and to reduce the memory requirement, we adopt the moving footprint concept and separate the whole model into a series of small sub-models for the inversion. Finally, we compare our anisotropic inversion scheme with the isotropic one using both synthetic and field data. Numerical experiments show that the anisotropic inversion has inherent advantages over the isotropic ones, we can get more reasonable results for the anisotropic earth structures.


2014 ◽  
Vol 543-547 ◽  
pp. 922-925 ◽  
Author(s):  
Hao Tian ◽  
Xiao Yong Kang ◽  
Yong Jian Li ◽  
Jun Nuo Zhang

The article explored a new signal processing method called order cepstrum analysis, it can analyze the instantaneous signals of the rotary mechanism, and can process the non-stationary vibration signals such as speed up or speed down signals effectively. Firstly, the start-up vibration signals of the gearbox are sampled at constant time increments in time-domain, then the data are resampled with software at constant angle increments in angle-domain. Therefore, the time domain instantaneously signal is changed into angle domain stationary signal. Then, the stationary signal is analyzed by order cepstrum. From the result we can find that it can avoid the frequency fuzzy phenomenon effectively, which cannot be solved with the traditional frequency spectrum analysis.


2008 ◽  
Vol 35 (3) ◽  
pp. 147-156 ◽  
Author(s):  
Makoto OGAWA ◽  
Youichi YAMADA ◽  
Tomo TAKAHASHI ◽  
Takenobu TSUCHIYA ◽  
Nobuyuki ENDOH

1998 ◽  
Vol 273 (1-2) ◽  
pp. 354-366 ◽  
Author(s):  
Michael Seiter ◽  
Vladimir Budker ◽  
Jing-Long Du ◽  
Gareth R. Eaton ◽  
Sandra S. Eaton

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