SeisFacies
Multi-attribute seismic classification. Numerous attributes are derived from modern seismic datasets, to provide insight into reservoir properties. Paradigm® SeisFacies®, an extension of the Paradigm Stratimagic® solution, and an integrated component of the Paradigm interpretation and characterization workflow, brings a wealth of technologies and processes to extract as much information as possible from existing seismic attributes. SeisFacies ensures that all available attribute data is put to use towards a comprehensive characterization of a prospect or reservoir. In the exploration stage, the versatile SeisFacies technology can perform 2D and 3D multi-attribute classification to extract geological information from seismic attributes. However, when used in association with electrofacies data, seismic facies information can also deliver calibrated, quantitative 3D representations of rock and fluid properties in heterogeneous environments. The classification results can serve as valuable input into the Paradigm SKUA® Data and Trend Analysis and Reservoir Properties modules, which have all the capabilities needed to leverage the results and deliver highly detailed quantitative property volumes. SeisFacies benefits:
- Extends application and scope of Stratimagic
- Integration with other Epos® -based products delivers an effective solution for facies volume analysis
- Increases geological understanding of seismic data
- Reduces noise and data redundancy for a more effective interpretation
- Principal Component Analysis: PCA is a statistical process used for data reduction. It identifies redundant information and keeps only uncorrelated information that contributes to further classification. PCA analyzes the relationships between a rich set of attributes and extracts the principal elongation directions to reduce the number of input variables.
- Multi-attribute Seismic Classification. Classifies all samples from a set of seismic attributes from 2D lines or 3D volumes, over a user-specified interval. SeisFacies uses Hierarchal
- Clustering, Neural Network or Hybrid classification methods.
- Visualization and validation: Presents classification results using selective sculpting tools, color coding and transparency, through close integration with the Paradigm VoxelGeo® voxel interpretation system.
- Calibration: Applies mathematical operators, such as well property-to-seismic attribute relationships, and other user-defined formulas, to data subsets to produce new volumes and/or maps.
- Fusion: Mixes two attributes to create a single output seismic volume or map containing a combination of the data. An interesting use is to mix structural and stratigraphic attributes.
- Zonation: Reduces the size of seismic sample datasets by using a controlling auxiliary seismic volume to generate seismic layers (zones). &l
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