Accelerating Seismic Dip Estimation With Deep Learning
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2021.3120315
Abstract: The seismic volumetric dip is a crucial seismic geometric attribute, which can provide useful information for assisting subsequent processing and interpretation. Waveform similarity scanning-based dip estimation (WSSB) delivers reliable dip estimation but encounters problems of… read more here.
Keywords: dip estimation; seismic dip; deep learning; dip ... See more keywords
Time-Frequency Spectral Decomposition Based on Dip Guided Window Function for Accurate Dip Estimation
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2022.3171296
Abstract: The dips of underground reflectors indicate their trends and provide a wealth of information about geological structures. It is widely used in seismic data processing and interpretation. The time-frequency spectrum (TFS) can be directly used… read more here.
Keywords: time; dip estimation; window function; dip ... See more keywords
Seismic Volumetric Dip Estimation via Multichannel Deep Learning Model
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2022.3190911
Abstract: Although there are plenty of approaches proposed for addressing seismic volumetric dip estimation, it still suffers from several limitations, for example, the expensive computation cost, the perturbations from sequence stratigraphic anomalies, and the difficulty for… read more here.
Keywords: volumetric dip; seismic volumetric; model; dip estimation ... See more keywords
Seismic Image Dip Estimation by Multiscale Principal Component Analysis
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2022.3229332
Abstract: Dip estimation of geological structures plays an important role in geophysical applications. Principal component analysis (PCA) is a common approach to estimating local dips by decomposing the local gradients of a seismic migration image and… read more here.
Keywords: multiscale; migration; dip estimation; image ... See more keywords