School of Geosciences, Yangtze University, Wuhan, Hubei, China.
School of Computer Science, Yangtze University, Jingzhou, Hubei, China.
PLoS One. 2022 Jul 15;17(7):e0271615. doi: 10.1371/journal.pone.0271615. eCollection 2022.
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.
提出了一种基于方向场一致性的骨架提取故障检测方法,以提高故障检测效率,降低横向非结构因素对故障检测的影响,实现自动故障提取。在指纹图像处理中,当所有方向都平行时,方向场的一致性达到最大值,而当不是所有方向都平行时,方向场的一致性取较小的值。在存在地层不连续的情况下,方向场不再平行,并且相应区域中的方向场一致性低于平行区域中的方向场一致性。这个特性可以用来从地震数据中提取不连续区域。然后,进行二值化和闭运算,以提取断层区域并增加断层连续性。最后,使用基于提取纵向中心点的骨架提取方法来识别断层线。与经典的蚂蚁跟踪方法相比,该方法需要调整的参数更少,从而在一定程度上简化了故障识别过程。此外,该方法有效地抑制了横向不连续性,突出了纵向故障特征,增强了故障连续性。