Ali A. Mohiedain

Euler deconvolution is a powerful tool in geophysics, particularly in the interpretation of magnetic and gravity data. By providing estimates of source location and depth, it helps map subsurface structures efficiently. One of the common challenges, however, lies in properly choosing the structural index (SI), as an incorrect SI can lead to significant errors in interpretation.

In practical applications, a balance between automatic and manual selection of the structural index is often necessary. Automatic techniques can offer a starting point, but domain knowledge and experience in interpreting the geological context often allow for more accurate results. Have you found specific datasets where this balance works best, or is there a particular approach you prefer for optimizing SI selection in complex geological scenarios?

Additionally, advancements in algorithms, such as 3D Euler deconvolution, have allowed for more refined interpretations, particularly in areas with intricate subsurface features. It's interesting to consider how these improvements might further enhance our ability to model complex geological structures.

I’d love to hear from others about their experiences with Euler deconvolution in various contexts, especially in terms of overcoming challenges in complex terrains or datasets.