OCEAN BOTTOM NODES - PXGEO
Ocean bottom node (OBN) acquisition is adaptable to more challenging imaging objectives providing full azimuth 4C sampling. PXGEO provides a range of ocean bottom nodes suitable …
Elastic Seismic Imaging Enhancement of Sparse 4C Ocean-Bottom …
The ocean-bottom node (OBN) seismic acquisition system is designed to gather high-fidelity, wide-azimuth, and long-offset four-component (4C) data, which includes shear waves and …
OBN Acquisition - TGS
Learn more about our fully modular OBN systems that acquire quality 4C data for critical decision-making. See how TGS marine seismic source solutions and RTQC technology, supported by …
OBN | TGS
Ocean Bottom Node (OBN) data, and sparse OBN, is ideally suited for Dynamic Matching Full Waveform Inversion (DM FWI). The processing toolkit for OBN includes 3D curvelet, sparse …
A review of OBN processing: challenges and solutions
Aug 9, 2021 · The main challenge of processing of OBN data is its unique acquisition geometry. Here we will demonstrate processing technologies that have been applied to a recently …
OBN System
Mobile seismic system for marine surveys and monitoring in transit shallow water based on 4C OBN KATRAN (depth range up to 200m).
MANTA 4C Ocean Bottom Acquisition System - Environmental XPRT
Ocean bottom node (OBN) acquisition is adaptable to more challenging imaging objectives providing full azimuth 4C sampling. PXGEO provides a range of ocean bottom nodes suitable …
(PDF) Seismic Imaging with Ocean-Bottom Nodes (Obn): New …
The Atlantis Seatrial 3D-4C OBN survey was acquired by SeaBird Exploration in 2009 over the Atlantis field at Gulf of Mexico. A total of 41 nodes were used at 17 locations on receiver lines …
ONGC has conducted its first full azimuth 4C-3D dense grid OBN seismic data acquisition in the two important oil fields; D1 and Neelam-Heera during 2018-19 using double sided parallel …
(PDF) Elastic Seismic Imaging Enhancement of Sparse 4C Ocean …
Jan 1, 2023 · To address these issues in the context of 4C elastic imaging, we propose a deep learning-based method using a multi-scale convolutional neural network (Ms-CNN) to improve …