Emad Ghalenoei's repositories
3D_Voronoi_Plane_Trans-D_Inversion
This is a Python code based on MPI module that parametrizes the subsurface structures using 3D Voronoi and Plane (VP) partitioning. You can find the full description in my research paper published in Geophysical Journal International (GJI). Citation instruction can be found at https://academic.oup.com/gji/advance-article-abstract/doi/10.1093/gji/ggac083/6536917.
Alpha_Shape
This python script applies joint gravity and magnetic inversion using Linear Interpolation and Alpha Shape. This method is fully represented in our research paper published at Inverse Problem Journal. Paper Title: Joint gravity and magnetic inversion with trans-dimensional alpha shapes and autoregressive noise models
Nearest_Interpolation_Alpha_Shape
This python script applies joint gravity and magnetic inversion using Nearest Interpolation and Alpha Shape. This method is fully represented in our research paper published at Inverse Problem Journal. The link of paper will be added soon.
Gravity_Forward_Model_2D_Python
This Python code performs 2D gravity forward model to generate simulated noisy data from a 2D model
rjMcMC_NestedVoronoi_GJI
This MATLAB code performs the rjMcMC algorithm to invert gravity and magnetic data to image the subsurface models. more info can be found in my journal paper.
Matrix_Wavelet_Compression
This python code takes a huge matrix (e.g. 3D gravity kernel) as an input and then performs wavelet compression to improve the efficiency of matrix multiplication. Note that the multiplication of two matrices in the wavelet domain is equal to the multiplication in the real domain. This wavelet compression was introduced by Li and Oldenburg, 2003 Fast inversion of large-scale magnetic data using wavelet transforms and a logarithmic barrier method. Geophysical Journal International.
Nested_Voronoi
This python script applies joint gravity and magnetic inversion using Nested Voronoi with 3 parent nodes. This method is fully represented in our research paper published at Inverse Problem Journal. The link of paper will be added soon.
Trans-D-Gravity-Inversion-cpp
This c++ code performs the rjMcMC algorithm to invert gravity and magnetic data to image the subsurface models.
correlated_noise_from_covariance
This code generates correlated noise to given data from a covariance matrix. the covariance matrix can have any form but here I assume a complex sinusoidal form. Enjoy and Cite!
Generate_Gravity_Data_cpp
Generate simulated gravity data in C++
Inversion-Gravity-Magnetic-using-KNN-Julia
This Julia code performs the rjMcMC algorithm to invert gravity and magnetic data to image the subsurface models.
Python_bot_Insta
follow and unfollow Instagram users