An improved C3 coherence algorithm using structural dip derived through the FFT time-shift property
ABSTRACT Fault identification is a key objective in oil and gas geophysical exploration, with the coherence cube technique being among the most widely used methods for fault identification. This paper extended the classical C3 coherence algorithm by incorporating structural dip information using the time-shifting properties of FFT. This modification eliminated the need for traditional interpolation methods and effectively addressed the C3 algorithm’s insensitivity to dip at a very low computational cost. To achieve this, we first smoothed and diffused the seismic data using directional derivatives to minimize the impact of noise on dip estimation and coherence calculation. Next, we estimated the dip angle using instantaneous phase. Subsequently, we incorporated the dip information into the coherence algorithm enhanced using complex seismic traces, resulting in a dip-considered coherence method. Application to 2D synthetic data demonstrated that the method effectively eliminates low-value artifacts caused by linear and curved dipping strata, clearly revealing faults. Coherence results from 3D field data also showed significant noise suppression and effective elimination of coherence artifacts and stratigraphic anomalies, highlighted small faults previously obscured by artifacts. Compared to the classical C3 coherence algorithm, the proposed method offered higher resolution, improved noise resistance, and eliminated dip artifacts at a very low computational cost, thereby enhanced discontinuity detection and ensuring accurate fault identification.
Authors
- Jianguo Song (ORCID: https://orcid.org/0000-0003-0302-7201)
- Zicheng Wang (ORCID: https://orcid.org/0000-0001-8351-0329)
- Yufei Su (ORCID: https://orcid.org/0009-0003-4304-1101)
- Jiwei Zhang
Institutions
- China University of Petroleum, East China (CN)
- China National Petroleum Corporation (China) (CN)
Publication Details
- Journal
- Geophysics
- Published
- 2025-10-27
- DOI
- https://doi.org/10.1190/geo-2025-0095
- Citations
- 1
- Primary Topic
- Advanced Fiber Optic Sensors
- Type
- article
- Field-Weighted Citation Impact
- 0.73