Automatic Wave Selection In Model Based Vsp Data Processing

Author(s):  
V. Ferentsi ◽  
A. Tabakov ◽  
L. Sevastyanov ◽  
E. Fursova ◽  
V. Eliseev
Keyword(s):  
First Break ◽  
2020 ◽  
Vol 38 (6) ◽  
pp. 29-36
Author(s):  
G. Yu ◽  
J.L. Xiong ◽  
J.J. Wu ◽  
Y.Z. Chen ◽  
Y.S. Zhao

2019 ◽  
Vol 12 (12) ◽  
pp. 3254-3264 ◽  
Author(s):  
José Aagel Pecina Sánchez ◽  
Daniel U. Campos‐Delgado ◽  
Diego R. Espinoza‐Trejo ◽  
Andres A. Valdez‐Fernández ◽  
Cristian H. De Angelo

2012 ◽  
Vol 253-255 ◽  
pp. 2091-2096
Author(s):  
Yan Feng Tang ◽  
Hui Mei Li ◽  
Xiang Kai Liu ◽  
Shao Qing Liu

Bayesian method was introduced and leaded into the vehicle fault data processing. The parameter estimation and the selection of the optimal distribution model based on Bayesian method were studied, and an example was given. The references are provided for the application of Bayesian method in the large complicated systems, such as vehicle equipments.


Geophysics ◽  
1995 ◽  
Vol 60 (2) ◽  
pp. 341-353 ◽  
Author(s):  
Xiao‐Gui Miao ◽  
Wooil M. Moon ◽  
B. Milkereit

A multioffset, three‐component vertical seismic profiling (VSP) experiment was carried out in the Sudbury Basin, Ontario, as a part of the LITHOPROBE Sudbury Transect. The main objectives were determination of the shallow velocity structure in the middle of the Sudbury Basin, development of an effective VSP data processing flow, correlation of the VSP survey results with the surface seismic reflection data, and demonstration of the usefulness of the VSP method in a crystalline rock environment. The VSP data processing steps included rotation of the horizontal component data, traveltime inversion for velocity analysis, Radon transform for wavefield separation, and preliminary analysis of shear‐wave data. After wavefield separation, the flattened upgoing wavefields for both P‐waves and S‐waves display consistent reflection events from three depth levels. The VSP-CDP transformed section and corridor stacked section correlate well with the high‐resolution surface reflection data. In addition to obtaining realistic velocity models for both P‐ and S‐waves through least‐square inversion and synthetic seismic modeling for the Chelmsford area, the VSP experiment provided an independent estimation for the reflector dip using three component hodogram analysis, which indicates that the dip of the contact between the Chelmsford and Onwatin formations, at an approximate depth of 380 m in the Chelmsford borehole, is approximately 10.5° southeast. This study demonstrates that multioffset, three‐component VSP experiments can provide important constraints and auxiliary information for shallow crustal seismic studies in crystalline terrain. Thus, the VSP technique bridges the gap between the surface seismic‐reflection technique and well‐log surveys.


F1000Research ◽  
2017 ◽  
Vol 6 ◽  
pp. 967 ◽  
Author(s):  
Ting-Li Han ◽  
Yang Yang ◽  
Hua Zhang ◽  
Kai P. Law

Background: A challenge of metabolomics is data processing the enormous amount of information generated by sophisticated analytical techniques. The raw data of an untargeted metabolomic experiment are composited with unwanted biological and technical variations that confound the biological variations of interest. The art of data normalisation to offset these variations and/or eliminate experimental or biological biases has made significant progress recently. However, published comparative studies are often biased or have omissions. Methods: We investigated the issues with our own data set, using five different representative methods of internal standard-based, model-based, and pooled quality control-based approaches, and examined the performance of these methods against each other in an epidemiological study of gestational diabetes using plasma. Results: Our results demonstrated that the quality control-based approaches gave the highest data precision in all methods tested, and would be the method of choice for controlled experimental conditions. But for our epidemiological study, the model-based approaches were able to classify the clinical groups more effectively than the quality control-based approaches because of their ability to minimise not only technical variations, but also biological biases from the raw data. Conclusions: We suggest that metabolomic researchers should optimise and justify the method they have chosen for their experimental condition in order to obtain an optimal biological outcome.


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