This repository contains codes to reproduce the results/ images in the manuscript: Deep neural network for detection and location of microseismic events and velocity model inversion of microseismic data recorded by DAS. The codes are written 100% in python and can be run by simply calling the .py files either on the command line or running the Jupyter notebook file provided. The test dataset is huge and can be downloaded here: https://drive.google.com/drive/folders/1IrmZjTaU8F68V9u-0np446raaaSiSNza?usp=sharing
Requirements:
Python version 2.7 and above
Tensorflow version 2.0 and above
Keras version 2.24 and above
Execution:
Download/ clone the repository and unzip it to a preferable location on your computer. Download the test dataset and place them in the same directory with the python files. Navigate to the location of the files and either;
type on the command line "python filename" without the ("")marks or,
open a jupyter notebook on your browser, import the files and run them or copy the code to a new notebook and execute.
optional: save the images to a directory of choice (By default, the images are saved in the same directory as the files. You can change this)
Notes:
Due to the large volumes of data involved, only 50 samples of the velocity models have been included in the test dataset provided here. Full synthetic dataset can be obtained by contacting the author.
Field dataset can be accessed at http://gdr.openei.org/submissions/1207
For more information contact wamriewdan@gmail.com