Geoplatai 2025.3 New ResUnet-24A Fault Identification Model
Geoplat AI-Based Integrated Geoscience Solution
Fault interpretation is one of the most challenging tasks in general structural interpretation workflows. Technologies developed in Geoplatai ,Geoplat v2025.03 can significantly reduce the time and resources required to build geological models. Machine learning based on deep neural networks enables calculation of fault probability distributions, surface extraction, and elimination of interpretation uncertainties. Horizon interpretation is a core process for understanding structural features in geological sections and performing reliable dynamic seismic analysis. Geoplat v2025.03 introduces a novel approach to solving the problem of automated horizon tracking. You can trace individual formations or entire strata while preserving complex fault structures and regional geological features. Low-quality seismic datasets often pose challenges for constructing structural frameworks and predicting pay zone attributes. The machine learning algorithms developed in Geoplat v2025.03 deliver a powerful workflow for interactive and intelligent data conditioning of stacked seismic data. It provides immediate results, substantially reducing time spent defining functions and workflows.
