Diffraction imaging enhancement using spectral decomposition for faults, fracture zones, and collapse feature detection in a Middle East carbonate field

Diffraction imaging is demonstrated in this case study to improve horizontal resolution over conventional reflection imaging. Edge enhancement, using spectral decomposition on diffraction imaged data, further enhances the capabilities of detecting faults, fracture zones, and collapse features improving the spatial resolution and edge detection for higher resolution seismic interpretation. Spectral decomposition also provides an effective tool for separating low-frequency reflection data noise from diffraction imaged data, improving the interpretability of the diffraction imaged data. This case study also demonstrates that edge enhancement using spectral decomposition improves the ability of spatially correlating the edges of collapse features, detected with diffraction imaged data, to drilling mud losses in carbonates. Detecting overburden collapse features with diffraction imaging could provide economic benefits, avoiding encounters with high perm zones, preventing mud loss expenses and increased drilling time, from days to weeks, and controlling the well.