Results 301 to 310 of about 22,545,449 (395)

Identifying Complex Fluvial Sandstone Reservoirs Using Core, Well Log, and 3D Seismic Data: Cretaceous Cedar Mountain and Dakota Formations, Southern Uinta Basin, Utah.

, 2011
William H. Hokanson
openalex   +1 more source

Restoring off‐highway vehicle trails in flood‐prone and riparian forests using balsam poplar cuttings

Restoration Ecology, EarlyView.
Abstract Introduction Recreational off‐highway vehicle (OHV) use can cause significant disturbance to natural areas. The use of local balsam poplar (Populus balsamifera L.) cuttings may be a solution to supply native plant material for the restoration of flood‐prone and riparian environments.
Raiany Dias de Andrade Silva, Anne C. S. McIntosh, S. Ellen Macdonald, Kerri Widenmaier   +3 more
wiley   +1 more source

Seismic cross-gradient constrained 3D inversion of transient electromagnetic data

Fei Li, Yulong Song, Zhewei Zhang, Ziyang Liu   +3 more
openalex   +1 more source

Seismic Data Acquisition and Processing

, 2011
openaire   +3 more sources

A physics-driven workflow for gas-sand identification in Pliocene turbidites using pre-stack inversion and seismic attributes, offshore Egypt. [PDF]

Sci Rep
Mahdy A, Helmi A, Helaly AS, Mahmoud AME.   +3 more
europepmc   +1 more source

Seismic and mineralogical evidence for an iron-rich mega-ultralow-velocity zone beneath Hawai'i. [PDF]

Sci Adv
Kim D, Song JH, Dobrosavljevic VV, Lekić V.   +3 more
europepmc   +1 more source

An interactive segmentation-based method for seismic facies annotation and segmentation. [PDF]

Sci Rep
Tian S, Tang Y, Deng F, Luo W, Wang B, Yang S.   +5 more
europepmc   +1 more source

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Seismic Data Reconstruction via Wavelet-based Residual Deep Learning

IEEE Transactions on Geoscience and Remote Sensing, 2022
Seismic data reconstruction is one of the essential steps in seismic data processing. Recently, the deep learning (DL) models have attracted huge attention in seismic exploration, which have been applied to seismic data reconstruction, especially the ...
Naihao Liu, Lukun Wu, Jiale Wang, Hao Wu, Jinghuai Gao, Dehua Wang   +5 more
semanticscholar   +1 more source

Multiscale Spatial Attention Network for Seismic Data Denoising

IEEE Transactions on Geoscience and Remote Sensing, 2022
Seismic background noise often damages the desired signals, thereby resulting in some artifacts in the seismic imaging that follows. Since about 2016, some supervised-deep-learning methods have shown impressive performance in seismic data denoising, but ...
Xintong Dong, Jun Lin, Shaoping Lu, Hongzhou Wang, Yue Li   +4 more
semanticscholar   +1 more source

Consecutively Missing Seismic Data Interpolation Based on Coordinate Attention Unet

IEEE Geoscience and Remote Sensing Letters, 2022
Missing traces interpolation is a basic step in the seismic data processing workflow. Recently, many seismic data interpolation methods based on different neural networks have been proposed.
Xinze Li, Bangyu Wu, Xu Zhu, Hui Yang
semanticscholar   +1 more source