## 4 Discussion  
This section provides a critical evaluation of the proposed OOCA method based on the experimental findings. We examine its performance in comparison with conventional seismic attributes, clarify the contributions of its core components, explore its geological and engineering applicability, discuss limitations observed during implementation, and highlight the method's technical innovations and broader implications. (1) Performance Comparison  
Both physical model tests and field data applications consistently show that the OOCA method improves fault and fracture detection over conventional attributes. In controlled modeling scenarios, OOCA achieved a detection accuracy of 92.6%, substantially exceeding that of C3 coherence (74.7%) and instantaneous phase (80.0%). It also demonstrated superior spatial resolution by identifying fractures as narrow as 10 m, compared to the 20-30 m threshold of traditional methods. In field applications, OOCA effectively delineated secondary and branching fractures within complex strike-slip fault systems, addressing the long-standing trade-off between large-scale continuity and small-scale resolution that limits fixed-window and single-frequency techniques. Despite its algorithmic sophistication, OOCA remains computationally efficient. Processing a typical 3D seismic volume required 21 min, comparable to C3 coherence (16 min), but with notably improved structural clarity. This makes it a practical alternative for workflows requiring both speed and resolution. (2) Frequency Integration  
OOCA's use of Gabor-based multi-frequency decomposition is central to its ability to extract structural information at multiple scales. Low-frequency components capture regional structural frameworks, while high-frequency components enhance resolution of fine-scale features such as fractures and small discontinuities. This integration enables the method to overcome the resolution-continuity trade-off commonly seen in single-frequency approaches. The current fusion scheme employs energy-based weighting, which--while computationally efficient--may suppress important signals in low-energy bands, potentially resulting in partial blurring of features in densely fractured zones. Moreover, the method's performance depends on the empirical selection of center frequencies and window parameters, which may limit adaptability across datasets. Future work may benefit from adaptive fusion strategies informed by spectral entropy, coherence metrics, or local structural complexity, enabling more context-aware integration. (3) Geological and Engineering Relevance  
OOCA's directional strategy is conceptually grounded in structural geology, reflecting the tendency for lithological changes to occur perpendicular to major structural trends. This allows the method to emphasize discontinuities that are more likely to be geologically meaningful. It is particularly suited for settings with intersecting faults or distributed fracture systems, where small-scale discontinuities may coincide with operational risks. Field validation shows that OOCA-detected features spatially correlate with lost circulation events observed during drilling. While such correlations do not establish causality, they suggest that the method may aid in the early identification of structurally sensitive intervals. In this capacity, OOCA could serve as a useful complement to conventional pre-drill risk screening tools, especially in reservoirs with structural complexity that affects borehole stability or fluid migration. Limitations and Influencing Factors  
Although OOCA offers clear advantages, several limitations merit consideration. The use of fixed energy-based frequency weighting may underrepresent structurally relevant signals in low-energy bands, particularly in noisy or fracture-rich zones. The method also depends on dip estimation derived from structure tensors, which can degrade under poor seismic quality, potentially leading to misalignment of model traces and reduced coherence reliability.