Results 21 to 30 of about 477 (145)

Deghosting, Demultiple, and Deblurring in Controlled-Source Seismic Interferometry [PDF]

open access: yesInternational Journal of Geophysics, 2011
With controlled-source seismic interferometry we aim to redatum sources to downhole receiver locations without requiring a velocity model. Interferometry is generally based on a source integral over cross-correlation (CC) pairs of full, perturbed (time ...
Joost van der Neut   +4 more
doaj   +5 more sources

Triangulation and Deghosting

open access: yes2006 International Radar Symposium, 2006
Triangulation and deghosting is the most complex part in multitarget tracking. It considers the relationship between the directions measured by the sensors and the original, real targets. This paper gives an overview and comparison, how advanced multisensor multitarget tracking methods can be applied and combined.
Felix Opitz, Guy Kouemou
openaire   +2 more sources

Over-Under Deghosting

open access: yesPGCE 2010, 2010
For streamer acquisition, the reflection of the up-going wave field at the sea surface (or ghost) contaminates the recordings, and in particular, significantly attenuates the lower frequencies. In order to eliminate the ghost, we may choose to advocate the recording of the wave field at several different depths: the so-called ‘Over-Under’ technique. In
Bruno Gratacos
openaire   +2 more sources

Deghosting in multipassive acoustic sensors

open access: yesSPIE Proceedings, 2004
In this paper, we describe a deghosting algorithm in multiple passive acoustic sensor environment. In a passive acoustic sensor system, a target is detected by its bearing to the sensor, and the target location is obtained from triangulation of bearings on different sensors. However, in multi-passive sensor and multi-target scenario, triangulation is
Rong Yang, Gee Wah Ng
openaire   +2 more sources

Segmentation Guided Deep HDR Deghosting

open access: yesCoRR, 2022
We present a motion segmentation guided convolutional neural network (CNN) approach for high dynamic range (HDR) image deghosting. First, we segment the moving regions in the input sequence using a CNN. Then, we merge static and moving regions separately with different fusion networks and combine fused features to generate the final ghost-free HDR ...
K. Ram Prabhakar   +2 more
openaire   +2 more sources

A low-frequency deghosting method: Analysis and numerical tests [PDF]

open access: yes, 2017
The low-frequency component of seismic data can be beneficial for several reasons: improved signal penetration into the earth, enhanced resolution, and better constrained inversion results.
Adriana Citlali Ramirez   +5 more
core   +2 more sources

Deghosting

open access: yes, 1993
J.T. Fokkema, P.M. van den Berg
openaire   +2 more sources

Seismic Reflection Imaging of a Deep‐Penetrating Red River Fault in the Yinggehai Basin, Northwest of the South China Sea

open access: yesGeophysical Research Letters, Volume 50, Issue 19, 16 October 2023., 2023
Abstract The Yinggehai Basin (YB) in the northwest of the South China Sea (SCS) has preserved the complete evolution of the Red River Fault (RRF), whose motion over time has largely contributed to shaping the current tectonic framework of the southeastern Tibetan Plateau and Indochina Block.
Lun Li, Shaoping Lu, Rui Gao, Chao Lei
wiley   +1 more source

Predicting visual difference maps for computer‐generated images by integrating human visual system model and deep learning

open access: yesIET Image Processing, Volume 17, Issue 3, Page 901-915, 28 February 2023., 2023
This paper proposed a novel model, Human Visual Perception and Deep Learning Image Difference Metric (HPDL‐IDM), for visibility difference prediction. Unlike other models that take as input images directly, HPDL‐IDM first extracts spatial features of images and then predicts the difference.
Ling Li   +3 more
wiley   +1 more source

An effective scheme of joint migration inversion in the pseudo‐time domain

open access: yesGeophysical Prospecting, Volume 71, Issue 2, Page 191-205, February 2023., 2023
Abstract Traditional full‐waveform inversion is a non‐linear and ill‐posed inversion problem. To reduce the non‐linearity of it, joint migration inversion (joint migration inversion) was proposed as an alternative. Joint migration inversion tries to minimize the mismatch between measured and modelled reflection data.
Shan Qu, Dirk Jacob Verschuur
wiley   +1 more source

Home - About - Disclaimer - Privacy