Quantum-Entangled Seismic Imaging for Fault Detection and Reservoir Characterization

Abstract This paper introduces a quantum-inspired edge detection approach for accurately delineating seismic faults and enhancing reservoir characterization in complex geological environments. By leveraging quantum entanglement, we aim to more effectively capture subtle discontinuities and stratigraphic boundaries, offering improved structural interpretation and a deeper understanding of reservoir properties in seismic data. Our method models seismic traces as elements of a quantum system and applies principles of quantum entanglement to correlate neighboring sample points based on amplitude and phase similarities. Each trace is "entangled" with its adjacent traces according to their similarity metrics, revealing abrupt discontinuities that typically indicate faults or other structural boundaries. We then apply an adaptive threshold to isolate these high-entanglement zones. Post-processing steps, including noise suppression and smoothing, refine the fault surfaces and enhance clarity in reservoir-scale features. This workflow is designed to integrate seamlessly with existing seismic interpretation and reservoir modeling processes. Extensive tests on both synthetic seismic models and real field datasets demonstrate that the quantum-inspired method excels in detecting subtle faults. Moreover, the computational overhead remains manageable, as the entanglement calculations are optimized for large-scale 3D seismic volumes. Overall, our findings confirm that quantum-inspired edge detection can significantly enhance structural interpretation and reservoir characterization by reliably pinpointing minor yet geologically critical features.