• Publications
  • Influence
Unsupervised seismic facies analysis using wavelet transform and self-organizing maps
Unsupervised seismic facies analysis provides an effective way to estimate reservoir properties by combining different seismic attributes through pattern recognition algorithms. However, withoutExpand
Integrated seismic texture segmentation and cluster analysis applied to channel delineation and chert reservoir characterization
In recent years, 3D volumetric attributes have gained wide acceptance by seismic interpreters. The early introduction of the single-trace complex trace attribute was quickly followed by seismicExpand
Automatic Seismic Facies Classification with Kohonen Self Organizing Maps - a Tutorial
The most popular seismic attributes fall into broad categories - those that are sensitive to lateral changes in waveform and structure, such as coherence and curvature, and those that are sensitiveExpand
Progress on empirical mode decomposition-based techniques and its impacts on seismic attribute analysis
AbstractSpectral decomposition plays a significant role in seismic data processing and is commonly used to generate seismic attributes that are useful for interpretation and reservoirExpand
Seismic interpretation of self-organizing maps using 2D color displays
Classification without supervision of patterns into groups is formally called clustering. Depending on the application area these patterns are called data lists, observations or vectors. ForExpand
Wavelet Transform Filtering In the 1D And 2D For Ground Roll Suppression
Among the various types of noise found in seismic land acquisition there is the one produced by surface waves. This noise is called ground roll, and it can be defined as a group of events thatExpand
Integrated seismic texture segmentation and clustering analysis to improved delineation of reservoir geometry
TLDR
We show how modern texture analysis based on the gray-level co-occurrence matrix, when coupled with recent developments in self-organizing maps clustering technology, extends such statistical measures to delineate features that geoscientists can see, but not easily describe. Expand
Latent space modeling of seismic data An overview
TLDR
Modeling of seismic data takes two forms: those based on physical or geological (phenomenological) models and those that are data-driven (probabilistic) models. Expand
Characterization of Thin Beds Through Joint Time-frequency Analysis Applied to a Turbidite Reservoir In Campos Basin, Brazil
A new spectral decomposition based method is presented here. We propose to use the ridges of the joint timefrequency analysis, as a new way to detect, in each trace, the maximum instantaneousExpand
...
1
2
3
4
5
...