Selective Trace Mix: A New Processing Tool to Enhance Seismic Imaging of Complex Subsurface Structures.

Area of Science:

• Geophysics
• Seismic Imaging

Background:

• Trace mixing in seismic data enhances signal-to-noise ratio but struggles with complex subsurface structures.
• Conventional filters often introduce artifacts, obscuring important geological features like faults and folds.

Purpose of the Study:

• Introduce a novel, data-dependent selective trace mix filter.
• Improve seismic data interpretability by enhancing reflections and preserving structural clarity.

Main Methods:

• Developed a selective trace mix filter employing sequential evaluation, referencing, exclusion, weighting, and normalization.
• The filter is temporally and spatially variable, adapting to data characteristics.

Main Results:

• The selective trace mix filter demonstrated enhanced amplitude consistency and spatial coherence.
• Preserved complex structures and improved fault and horizon clarity on synthetic and real seismic data.

Conclusions:

• Selective trace mix significantly outperforms conventional filters in maintaining horizon integrity and fault definition.
• This novel filter is effective for seismic imaging in areas with complex geology.