DiffraPy: An open-source Python software for seismic diffraction imaging

Zakarewicz, Guilherme; Maciel, Susanne; Biloti, Ricardo

doi:10.1016/j.cageo.2024.105575

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article1

Other1

Preprint1

Relationship

Self Cite0

Independent3

Authors

Journals

Cited by 3 publications

References 115 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Systematic literature review on seismic diffraction imaging

Zakarewicz,

Maciel,

da Cunha

2024

Earth-Science Reviews

View full text Add to dashboard Cite

Systematic literature review on seismic diffraction imaging

Zakarewicz,

Maciel,

da Cunha

2024

Earth-Science Reviews

View full text Add to dashboard Cite

Automated Recognition of Structures in Scanning Electron Microscopy Images Using Specialized Algorithms in MATLAB and Python: An Overview

Marascu,

Mihailescu,

Nita

et al. 2024

2024 16th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)

View full text Add to dashboard Cite

Diffraction separation method using shapeDTW and median-mean filter

Sheng,

Zhao,

Yang

et al. 2024

Preprint

View full text Add to dashboard Cite

The subsurface small-scale geological structures are manifested as diffractions in seismic data. Diffraction imaging provides high-resolution details of discontinuities such as faults, collapse columns, and karst caves. However, this high-resolution information is often obfuscated by strong reflections, necessitating their removal prior to diffraction imaging. Here, we propose a novel diffraction separation method based on shape dynamic time warping (shapeDTW) and median-mean filter. The shapeDTW is an effective time series alignment method that utilizes the distance between temporal points within a neighborhood as the alignment criterion, which can accurately align strong energy events in seismic data. We implement shapeDTW to construct flattened reflection gathers, in which the reflections are aligned and therefore behaves as horizontal events with consistent strong amplitudes, while the diffractions appear as non-horizontal weak events. Leveraging this difference in shape and amplitude, the median-mean filter can effectively extract the reflections from flattened reflection gathers. Diffractions are separated from seismic data by subtracting the extracted reflections. The synthetic data experiment confirms the feasibility of the proposed method in eliminating strong reflected waves while preserving weak diffracted waves related to karst caves in seismic data with low signal-to-noise ratio. The field data application further illustrates its effectiveness in removing strong high-slope reflections, highlighting small-scale fracture-related detailed features.

show abstract

DiffraPy: An open-source Python software for seismic diffraction imaging

Cited by 3 publications

References 115 publications

Systematic literature review on seismic diffraction imaging

Systematic literature review on seismic diffraction imaging

Automated Recognition of Structures in Scanning Electron Microscopy Images Using Specialized Algorithms in MATLAB and Python: An Overview

Diffraction separation method using shapeDTW and median-mean filter

Contact Info

Product

Resources

About