InterWell, the geophysical solution from Beicip-Franlab, The leading-edge software with comprehensive workflows, to conduct end-to-end geophysical studies, from defining your Rocks physics model, running QC and seismic data conditioning, seismic inversion, to subsurface characterization, and depth conversion.

InterWell 2024 includes the following features:

Database enhancement

Rename data.

Arrange data in customizable subfolders.

Save & open sessions.

Lithology displays.

Display preferences

Gather conditioning

F-K filter processor.

Depth gathers automatic conversion.

Optional topography while stacking.

Machine Learning

Unsupervised and semi-supervised Self-Organizing Maps.

Principal component analysis on Maps.

Supports depth domain.

Extraction capabilities

Statistics on wells for 2D property mapping.

Machine learning trained by both wells and attributes.

The Self-Organizing Maps is a powerful unsupervised clustering method that transforms a complex, high-dimensional input space (seismic attributes) into a two-dimensional discrete output space (seismic facies), while preserving relationships in the data-structure between neurons (topology).

The SOM has been implemented because the results do not depend on the frequency of appearance of classes in the data, and this is appropriate to indicate atypical, rare or anomalous samples. To automatically highlight the neurons corresponding to a prior observation, a semi-supervised version has also been implemented for fracture or matrix characterization applications.

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