[HTML][HTML] The minerals industry in the era of digital transition: An energy-efficient and environmentally conscious approach

GT Nwaila, HE Frimmel, SE Zhang, JE Bourdeau… - Resources Policy, 2022 - Elsevier
The concept of the 4th industrial revolution is becoming a strategic determinant of
sustainability, success and competitiveness in the modern mining sector. The importance of …

Building realistic structure models to train convolutional neural networks for seismic structural interpretation

X Wu, Z Geng, Y Shi, N Pham, S Fomel, G Caumon - Geophysics, 2020 - library.seg.org
Seismic structural interpretation involves highlighting and extracting faults and horizons that
are apparent as geometric features in a seismic image. Although seismic image processing …

3-D Structural geological models: Concepts, methods, and uncertainties

F Wellmann, G Caumon - Advances in geophysics, 2018 - Elsevier
The Earth below ground is the subject of interest for many geophysical as well as geological
investigations. Even though most practitioners would agree that all available information …

Deep relative geologic time: a deep learning method for simultaneously interpreting 3‐D seismic horizons and faults

Z Bi, X Wu, Z Geng, H Li - Journal of Geophysical Research …, 2021 - Wiley Online Library
Extracting horizons and detecting faults in a seismic image are basic steps for structural
interpretation and important for many seismic processing schemes. A common ground of the …

[BOK][B] Handbook of poststack seismic attributes

AE Barnes - 2016 - library.seg.org
The Handbook of Poststack Seismic Attributes is a general reference for poststack seismic
attributes intended for reflection seismologists in petroleum exploration. The goal of the book …

Semiautomated seismic horizon interpretation using the encoder-decoder convolutional neural network

H Wu, B Zhang, T Lin, D Cao, Y Lou - Geophysics, 2019 - pubs.geoscienceworld.org
The seismic horizon is a critical input for the structure and stratigraphy modeling of
reservoirs. It is extremely hard to automatically obtain an accurate horizon interpretation for …

Multitask learning for local seismic image processing: fault detection, structure-oriented smoothing with edge-preserving, and seismic normal estimation by using a …

X Wu, L Liang, Y Shi, Z Geng… - Geophysical Journal …, 2019 - academic.oup.com
Fault detection in a seismic image is a key step of structural interpretation. Structure-oriented
smoothing with edge-preserving removes noise while enhancing seismic structures and …

Predictive painting of 3D seismic volumes

S Fomel - Geophysics, 2010 - library.seg.org
Predictive painting is a numerical algorithm that spreads information in 3D volumes
according to the local structure of seismic events. The algorithm consists of two steps. First …

Deep learning for relative geologic time and seismic horizons

Z Geng, X Wu, Y Shi, S Fomel - Geophysics, 2020 - library.seg.org
Constructing a relative geologic time (RGT) image from a seismic image is crucial for
seismic structural and stratigraphic interpretation. In conventional methods, automatic RGT …

Horizon volumes with interpreted constraints

X Wu, D Hale - Geophysics, 2015 - library.seg.org
Horizons are geologically significant surfaces that can be extracted from seismic images.
Color coding of horizons based on amplitude or other attributes can help reveal ancient …