Introducing a new texture attribute based on the anisotropy index,, case study: Salt dome

Articles in Press

Authors

Shahrood University of Technology

Abstract

Accurate detection of subsurface structures such as salt domes is crucial in hydrocarbon exploration. Traditional seismic attributes like coherence, curvature, and chaos offer valuable insights but often fall short in clearly delineating complex geological boundaries. To overcome these limitations, this study explores a texture-based approach focused on analyzing the spatial characteristics of seismic data.

A novel attribute, termed the Gradient Tensor Anisotropy Index (GTAI), is introduced based on the statistical analysis of eigenvalues derived from the local gradient structure tensor. The method distinguishes between anisotropic regions with dominant layering (e.g., sedimentary strata) and isotropic areas lacking directional trends (e.g., salt domes).

The proposed attribute was tested on a 2D seismic dataset from a salt dome in the Strait of Hormuz and compared with conventional entropy and chaos attributes. Results show that GTAI outperforms existing methods in boundary detection accuracy, demonstrating better alignment with expert interpretation, especially when using optimally sized windows.

GTAI is less sensitive to noise, independent of dip estimation, and computationally efficient due to its structure-oriented design. These features make it a promising tool for automatic seismic interpretation, particularly in identifying complex structures like salt domes.

Keywords


Articles in Press, Accepted Manuscript
Available Online from 03 November 2025

Files

Share

How to cite

Statistics