Because of their effectiveness in identifying geologic features, seismic attributes are usually
used as input to machine learning (ML) models for facies classification. Typically, too many …

Faults with throws that fall below vertical seismic resolution are challenging to identify in
reflection seismic datasets. Nevertheless, such small-scale faults may still affect the seismic …

Deep‐water massive sandstones (DWMS) are characterized by large volumes of sand
accumulations which are considered as potential reservoir intervals in deep‐marine …

Featured Application Precise fault detection and extraction have a prime role in
understanding the structural framework in the subsurface for multiple reasons, the major …

Over the past few years, the use of machine learning has gained considerable momentum in
many industries, including exploration seismic. While supervised machine learning is …

Hybrid event beds represent the combined effect of multiple geological processes, which
result in complex depositional geometries and distinct facies distribution in marine …

Abstract Machine learning algorithms (MLAs) perform better when enough high-quality
training data is provided. However, a lack of training data is frequent in seismic facies …

The Danish subsurface has the potential to store significant amounts of CO2 by having
porous siliciclastic reservoirs at depths below 800 m (where pressure and temperature allow …

Alluvial fan and Fluvial facies sand bodies are important reservoirs for oil and gas resources.
In this study, the sedimentary characteristics and evolutionary patterns of Alluvial fan and …

Sandbody distribution patterns and controls are the most important foundation for petroleum
exploration and development, particularly in a lacustrine basin with rapid changes in the …