hi ，i'm zhaoyang, you did excellent work.

i have a problem, when i try to run PGI_joint_no_petrophysical_means_information.ipynb, it gives

module'SimPEG.regularization'has no attribute ''MakeSimplePetroRegularization'

my simpeg version is 0.13.0. How can I solve this problem？

appreciate.

I want to reproduce the results of the simPEG joint inversion technique with potential field data sets (gravity and magnetic) of my study area. But I do not know how to create geology surface feature files (*.ts *.vtp, and *.vtu files extensions in the Geology surface folder) for my study area. Please tell me which software should I use for creating geology surface files.

Any help would be appreciated

• I tried to run the variable name in command line for seeing the data but output show some strings like below

• How can i save variable data from the SimPEG data store

Hi,

I am Fian and I am interested in your work. I have cloned the GIT into my system, and when I tried to run it, it gives

'jupyter' is not recognized as an internal or external command,
operable program or batch file.

I have tried several things:

1. Copied the jupyter into the pgijoint-env folder,
2. Adding the Python Home Path to my System's Environment Variables,
3. Reinstalled Jupyter (which it says that it is already in my system).

I have ran out of ideas, can you offer me any other solution?

1. I tried to recreate the ocTree mesh data file used in the Joint PGI of Gravity and Magnetic without petrophysical information code. However, I was unable to create the precise ocTree mesh file. Please specify the exact parameters for reproducing the Octree mesh data file.
   I have attached the code for creating an ocTree mesh file and cross-sections and XY plots of the ocTree mesh.
   ####### create octree mesh file

Import Modules

import numpy as np
from scipy.interpolate import LinearNDInterpolator
import matplotlib as mpl
import matplotlib.pyplot as plt

from discretize import TreeMesh
from discretize.utils import mkvc, refine_tree_xyz
from SimPEG.utils import plot2Ddata, model_builder, surface2ind_topo
from SimPEG import maps
from SimPEG.potential_fields import gravity

######### load topogaphy data #########################

data1 = np.genfromtxt('TOPO_AOI_KIMBERLITE_CANADA_15JUL21.dat')

x_topo1=data1[:, 0]
x_topo2= np.transpose(x_topo1)
y_topo1=data1[:, 1]
y_topo2= np.transpose(y_topo1)
z_topo1=data1[:, 2]
z_topo2= np.transpose(z_topo1)

x_topo, y_topo, z_topo = mkvc(x_topo2), mkvc(y_topo2), mkvc(z_topo2)
xyz_topo = np.c_[x_topo, y_topo, z_topo ]

#Defining an OcTree Mesh

dx = 25 # minimum cell width (base mesh cell width) in x
dy = 25 # minimum cell width (base mesh cell width) in y
dz = 25 # minimum cell width (base mesh cell width) in z

x_length = 800.0 # domain width in x
y_length = 800.0 # domain width in y
z_length = 800.0 # domain width in z

Compute number of base mesh cells required in x and y

nbcx = 2 ** int(np.round(np.log(x_length / dx) / np.log(2.0)))
nbcy = 2 ** int(np.round(np.log(y_length / dy) / np.log(2.0)))
nbcz = 2 ** int(np.round(np.log(z_length / dz) / np.log(2.0)))

Define the base mesh

hx = [(dx, nbcx)]
hy = [(dy, nbcy)]
hz = [(dz, nbcz)]

#mesh = TreeMesh([hx, hy, hz])
mesh = TreeMesh([hx, hy, hz], x0="CCN")

xc = 400 + 556900
yc = 400 + 7133200
zc = 440.9

x0_new = np.r_[mesh.x0[0] + xc, mesh.x0[1] + yc, mesh.x0[2] + zc]

mesh.x0 = x0_new

Refine based on surface topography

mesh = refine_tree_xyz(
mesh, xyz_topo, octree_levels=[2, 2], method="surface", finalize=False
)

Refine box based on region of interest

xp, yp, zp = np.meshgrid([557000.0, 557600.0], [7133300.0, 7133900.0], [50.0, 400.0])
xyz = np.c_[mkvc(xp), mkvc(yp), mkvc(zp)]
mesh = refine_tree_xyz(mesh, xyz, octree_levels=[2, 2], method="box", finalize=False)

mesh.finalize()

mesh.writeUBC('mesh_file1.ubc')

2. I was unable to construct correct output quasi-geological model or density/susceptibility contrast on cross-sections and XY plots, and 2D density probability plot using the Joint PGI of Gravity and Magnetic without petrophysical information code with the ocTree mesh file that I created using the preceding script (remaining input files and settings are the same). Please find the attached figures.
   
   

3. I noticed no quasi-geological model or density/susceptibility contrast on cross-sections and XY plots, and the points on the density probability plot are scattered, I am not sure why.

PGI multi-physics inversion utilising a dynamic Gaussian mixture model (GMM) technique was implemented on extremely small scale area (600 m 600 m) potential field data sets in this work (Astic et al., 2020). Is it possible to apply this strategy to reasonably big areas (regional scale)? If so, what assumptions should I think about?