Fault detection by skeleton extraction based on orientation field consistency

PLoS One. 2022 Jul 15;17(7):e0271615. doi: 10.1371/journal.pone.0271615. eCollection 2022.

Abstract

A fault detection method using skeleton extraction based on orientation field consistency is proposed to improve the efficiency of fault detection, reduce the influence of transverse nonstructural factors on fault detection, and realize automatic fault extraction. In fingerprint image processing, the consistency of the orientation field reaches a maximum value when all orientations are parallel and takes a smaller value when not all orientations are parallel. The orientation field ceases to be parallel in the presence of a stratigraphic discontinuity, and the consistency of the orientation field in the corresponding region is lower than that in parallel regions. This characteristic can be exploited to extract discontinuous regions from seismic data. Then, binarization and closing operations are used to extract fault areas and increase fault continuity. Finally, a skeleton extraction method based on extracting the longitudinal center point is used to identify the fault lines. Compared with the classical ant tracking method, the proposed method requires the adjustment of fewer parameters, thus simplifying fault identification process to a certain extent. Moreover, the proposed method effectively suppresses transverse discontinuities, highlights the longitudinal fault characteristics, and strengthens fault continuity.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Image Processing, Computer-Assisted*
  • Skeleton*

Grants and funding

This research was funded by the National Science and Technology Major Projects of China (2016ZX05055). The funders had no role in study design, data collection, and analysis, decision to publish, or preparation of the manuscript.