Automated Seismic Horizon Tracking Using Advance Spectral Decomposition Method

Maryam Mahsal Khan ()
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Maryam Mahsal Khan: Department of Computer Science (CECOS University of IT and Emerging Science, Peshawar, Pakistan)

International Journal of Innovations in Science & Technology, 2024, vol. 6, issue 2, 688-697

Abstract: Introduction/Importance of Study: In three-dimensional seismic interpretation, automatic horizon tracking is a critical productivity tool. However, it often fails in areas where horizons are not smooth and exhibit sharp discontinuities such as large spatial displacement or changes in reflector aliasing, horizon gradients, and signal character. Such failures require manual intervention, which increases the interpretation cycle time.Novelty Statement: In this research study, an automated horizon tracker is proposed that adapts tochangesin reflector shape, strength,and geological variation as it traverses through the seismic data volume.Material and Method: A predefined spatial grid window steers across the horizon surface where its orientation changes with the variation in a pre-computed, high-resolution, dip volume. The method is further improved to incorporate tracking horizons across discontinuities i.e. faults.Result and Discussion: The proposed method is tested on three-dimensional seismic data with varying geological conditions and has demonstrated successful mapping of horizon surfaces and effective matching across major faults.Concluding Remarks: Our automatic procedure, by reducing the need for manual intervention during interpretation, has the potential to significantly improve productivity.

Keywords: Horizon Surface; Spectral Decomposition; Fault Displacement; Cosemblance; Seismic (search for similar items in EconPapers)
Date: 2024
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