# Multiscale Fusion for Seismic Geometric Attribute Enhancement

## TL;DR

This paper introduces a multiscale fusion method that enhances seismic geometric attributes like dip and curvature, improving their resolution and noise robustness for better seismic data interpretation.

## Contribution

The paper presents a novel multiscale fusion technique using Gaussian pyramids to enhance seismic attributes, outperforming existing methods in noise reduction and resolution.

## Key findings

- Improved noise robustness of seismic attributes.
- Enhanced resolution of dip and curvature attributes.
- Potential to improve other seismic attributes like coherence and GLCM.

## Abstract

In this abstract, we propose a multiscale fusion technique to enhance seismic geometric attributes, such as dip and curvature, which are very sensitive to noise present in seismic data. For a give seismic section, first, we construct a Gaussian pyramid that allows us to generate the seismic attribute at different resolutions (scales). Then, all attributes at the different scales are fused together to form the proposed multiscale enhanced attribute. Applications to the 3D seismic dataset over the Great South Basin in New Zealand demonstrate that the proposed method is capable of improving both the resolution and noise robustness of the first-order dip and the second-order curvature attributes, compared to existing methods and algorithm. Such improvement indicates the great potential of our multiscale fusion technique for enhancing the quality of more multitrace seismic attributes, such as coherence, flexure, and GLCM.