# Computer Vision In Geo-science

## Naive 3D seismic fault segmentation workflow in Python

This post is mostly to share back with the community what I’ve learned in my playground session with [Kerry-3D Seismic data](https://wiki.seg.org/wiki/Kerry-3D).

Kerry-3D is collection of Data provided by the New Zealand Crown Minerals is a prestack migrated final volume. The volume is 1 GBytes. All data are time migrated.

Please refer to the

NOTEBOOK - https://github.com/equinor/segyio-notebooks/blob/master/notebooks/pylops/01\_seismic\_inversion.ipynb

This notebook aims at presenting a simple example of relative seismic inversion. This notebook uses both the [Kerry3D data](https://wiki.seg.org/wiki/Kerry-3D) and the [Volve data](https://www.equinor.com/no/how-and-why/digitalisation-in-our-dna/volve-field-data-village-download.html) as input data to our inversion and we will leverage the open-source [segyio](https://pypi.org/project/segyio/) along with [pylops](https://pypi.org/project/pylops/) libraries to accomplish our task as follows:

* Data is read from SEG-Y file using [segyio](https://pypi.org/project/segyio/) (note that for the Volve data we will have to deal with irregular geometry)
    
* Relative seismic inversion is applied by means of pylops.avo.poststack.PoststackInversion
    
* Inverted data is saved back to SEG-Y file using segyio
    

Pictorial representation of the workflow -

![](https://mycarta.files.wordpress.com/2019/03/workflow.png?w=768 align="left")

## Want to get access of free loads of 3D Seismic Datasets

Please access ["The SEG Wiki"](https://wiki.seg.org/wiki/Main_Page) The SEG Wiki's main mission is to supply scientific materials to the geoscience community.

Well! A sample (An example 3D plot of a subset of Kerry-3D) data and inline and xline displays are below -

![](https://wiki.seg.org/images/6/6e/Kerry3d.png align="left")

![](https://wiki.seg.org/images/8/8b/Kerry_sidebyside.png align="left")

## Working with Seismic Data (3D data)

Ability to work with Seismic Data has been a sore spot for some time. How to go about converting Seismic data (generally SEGY files with .SGY extensions) to numpy arrays/Tensors, Seismic image processing, and particularly morphological image processing, to the task of fault segmentation, et al? So, think about -

* how to read seismic volumes as NumPy arrays?
    
* how to manipulate the similarity to create a discontinuity/fault volume?
    
* how to write the fault volume to SEG-Y file using re-using the headers from the input file?
    
* how to basic Segy editing, such as how to perform manipulations of traces length, both resampling and cutting, etc?
    
* how to transfer binary and trace headers in pandas dataframes and visualize headers and data with matplotlib?
    
* how to perform Seismic inversion, such as how to download and read a SEG-Y file, perform colored inversion to a portion of the data and saved the inversion result in a brand new SEG-Y?
    

\*\* Enters [segyio](https://pypi.org/project/segyio/), a fast, open-source library, developed precisely to work with SEGY files. The aforementioned whole load of questions get answered by python libraries - [segyio](https://pypi.org/project/segyio/) along with [pylops](https://pypi.org/project/pylops/) and NumPy. \*\*

## Reference

[![Seismic Data Inversion](https://serc.carleton.edu/download/images/27316/seismic_reflection.gif align="left")](https://youtu.be/7DnudEsb6hU)

(["Click on the Image Link"](https://youtu.be/7DnudEsb6hU) for the YouTube Video on Seismic Data Inversion)

Thank you for joining! Stay connected with the latest updates and insights by visiting my website [**www.DeepHiveMind.com**](http://www.deephivemind.com/). Don't forget to follow me on social media for more tech tips and discussions. Let's continue exploring the exciting world of technology together! #TechTalks #StayConnected

* LinkedIn:[**https://www.linkedin.com/in/harshvardhan-ai/**](https://www.linkedin.com/in/harshvardhan-ai/)
    
* GitHub: [**https://github.com/DeepHiveMind**](https://github.com/DeepHiveMind)