We present a comprehensive automated solution for 3D seismic fault detection and interpretation that combines deep learning with advanced geometric post-processing. The method integrates a 3D U-Net neural network trained on synthetic data with normalized distance function targets and an integrated post-processing pipeline including planarity filtering, Hessian-based faultness extraction, time-slice fault tracing, and a novel mutual neighbor confirmation clustering algorithm. The core contribution lies in system-level integration of known methods into a fully automated end-to-end workflow with minimal parameterization, where critical parameters are determined automatically. Time-slice tracing with Hessian-based orientation provides azimuth-agnostic detection; the method is most effective for high-angle faults (dip > 45°). Internal validation on proprietary datasets achieved F1-scores of 0.82–0.87. In expert qualitative assessment, the majority of faults required no or minimal manual correction. The result is a production-ready system integrated into commercial software, significantly accelerating structural seismic interpretation.
The increasing reliance on third-party packages from repositories such as Python Package Index (PyPI) and Node Package Manager (NPM) has introduced critical vulnerabilities in software supply chains. Traditional security approaches, including signature-based detection and trust e…
Abstract: 5G is rolled out and next generation 6G networks are also being developed, ultra-low latency (URLL) communication as a standard is critical in supporting the plethora of applications, spanning autonomous vehicles, immersive extended reality experience, etc. However, tra…
Nigeria's oil and gas pipeline network spanning over 5,000 km of trunk lines and more than 3,000 km of flow lines loses an estimated one billion US dollars annually to pipeline failures, environmental incidents, and non-productive time. The dominant monitoring approach in operati…
The rapid growth of online career and learning resources has made it difficult for job seekers and professionals to identify the skills, roles, and learning paths that best match their goals. This paper presents SkillGraph, a multi-agent architecture for AIpowered career recommen…
The digital landscape is undergoing a seismic shift, moving beyond the era of simple data storage into an age where the true value of information lies in its ability to forecast the future. AI-Powered Predictive Analytics for Intelligent Decision Support Systems is designed as a…