Revisiting NMO stretch and velocity analysis

2011 ◽  
Author(s):  
Bo Zhang ◽  
Tang Wang ◽  
Kurt J. Marfurt
2011 ◽  
Author(s):  
F. Martin ◽  
M. Almutairi ◽  
S. Fernández

Geophysics ◽  
2014 ◽  
Vol 79 (6) ◽  
pp. U15-U23 ◽  
Author(s):  
Bo Zhang ◽  
Tao Zhao ◽  
Jie Qi ◽  
Kurt J. Marfurt

With higher capacity recording systems, long-offset surveys are becoming common in seismic exploration plays. Long offsets provide leverage against multiples, have greater sensitivity to anisotropy, and are key to accurate inversion for shear impedance and density. There are two main issues associated with preserving the data fidelity contained in the large offsets: (1) nonhyperbolic velocity analysis and (2) mitigating the migration/NMO stretch. Current nonhyperbolic velocity analysis workflows first estimate moveout velocity [Formula: see text] based on the offset-limited gathers, then pick an effective anellipticity [Formula: see text] using the full-offset gathers. Unfortunately, estimating [Formula: see text] at small aperture may be inaccurate, with picking errors in [Formula: see text] introducing errors in the subsequent analysis of effective anellipticity. We have developed an automated algorithm to simultaneously estimate the nonhyperbolic parameters. Instead of directly seeking an effective stacking model, the algorithm finds an interval model that gives the most powerful stack. The searching procedure for the best interval model was conducted using a direct, global optimization algorithm called differential evolutionary. Next, we applied an antistretch workflow to minimize stretch at a far offset after obtaining the optimal effective model. The automated velocity analysis and antistretch workflow were tested on the data volume acquired over the Fort Worth Basin, USA. The results provided noticeable improvement on the prestack gathers and on the stacked data volume.


2009 ◽  
Vol 2009 (9) ◽  
pp. 6402-6413
Author(s):  
G. Ying ◽  
C. Berretta ◽  
I. Gnecco ◽  
G. Becciu ◽  
J. Sansalone

BMC Surgery ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Benjamin De Witte ◽  
Charles Barnouin ◽  
Richard Moreau ◽  
Arnaud Lelevé ◽  
Xavier Martin ◽  
...  

Abstract Background There is a general agreement upon the importance of acquiring laparoscopic skills outside the operation room through simulation-based training. However, high-fidelity simulators are cost-prohibitive and elicit a high cognitive load, while low-fidelity simulators lack effective feedback. This paper describes a low-fidelity simulator bridging the existing gaps with affine velocity as a new assessment variable. Primary validation results are also presented. Methods Psycho-motor skills and engineering key features have been considered e.g. haptic feedback and complementary assessment variables. Seventy-seven participants tested the simulator (17 expert surgeons, 12 intermediates, 28 inexperienced interns, and 20 novices). The content validity was tested with a 10-point Likert scale and the discriminative power by comparing the four groups’ performance over two sessions. Results Participants rated the simulator positively, from 7.25 to 7.72 out of 10 (mean, 7.57). Experts and intermediates performed faster with fewer errors (collisions) than inexperienced interns and novices. The affine velocity brought additional differentiations, especially between interns and novices. Conclusion This affordable haptic simulator makes it possible to learn and train laparoscopic techniques. Self-assessment of basic skills was easily performed with slight additional cost compared to low-fidelity simulators. It could be a good trade-off among the products currently used for surgeons' training.


Author(s):  
Dechao Cai ◽  
Guifang Fa ◽  
Jia Li ◽  
Xing Xing ◽  
Yanjing Yi

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