May 6, 2019 · Seismic facies classification refers to the interpretation of facies type from the seismic reflector information. The key elements used to determine seismic facies and depositional setting are bedform internal and external configuration/geometry, lateral continuity, amplitude, frequency, and interval velocity.

Feb 4, 2022 · Seismic facies analysis is the description and interpretation of seismic reflection parameters, such as configuration, continuity, amplitude, and frequency, within the stratigraphic framework of a depositional sequence.

Jan 1, 2022 · Seismic facies analysis is perhaps the most useful aspect of seismic stratigraphy, which emphasizes the integration of seismic data with geology. On a broader scale, it allows distinguishing sedimentary environments and interpreting lithologies based on seismic reflection geometry characteristics.

Seismic facies analysis is the description and interpretation of seismic reflection parameters, such as configuration, continuity, amplitude, and frequency, within the stratigraphic framework of a depositional sequence.

Seismic facies analysis aims to interpret the variations of seismic response parameters. The so-called seismic facies can be defined as groups of seismic traces; members of the...

Reconstructing HR seismic images from LR ones and performing accurate automated seismic interpretation are crucial for assessing subsequent oil and gas reservoirs. In this letter, we propose a multitask seismic facies interpretation network based on super-resolution (SR) learning, named SR semantic segmentation network (SRSS-Net).

Apr 1, 2017 · Seismic facies analysis provides an effective way to delineate the heterogeneity and compartments within a reservoir. Traditional method is using the single waveform to classify the seismic facies, which does not consider the stratigraphy continuity, and the …

Seismic facies analysis involves the systematic description and mapping of seismic facies units within a stratigraphic framework, using seismic attributes and visualization techniques such as color-coded facies maps and 3D volume rendering

Oct 7, 2024 · We propose three strategies of field seismic data curation, knowledge-guided synthesization, and GAN-based generation to construct a massive-scale, feature-rich and high-realism benchmark dataset of seismic facies and evaluate its effectiveness in training a deep learning model for automatic seismic facies classification.

seismic facies. Because almost all geologic structures show at least one of these facies in seismic reflection data, classifying them accu-rately would allow us to map a wide range of structures. MACHINE LEARNING To classify seismic facies, we apply a typical machine-learning workflow (e.g., Abu-Mostafa et al., 2012). The basic idea of this