[Python] How to figure out or estimate the level of noise in a given data distribution

I have been given a data distribution which was synthetically generated by geostatistical methods such as variogram analysis.

Without having the source of the technique which generated the data, is there any way to find out or at least estimate the level of noise in the data? (a parameter to quantify how noisy the data is or the amount of noise in the data)

I have provided a sample of my data here.



import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

noisy_data = [[0.0467251, 0.0529133, 0.0775945, 0.0640082, 0.0439774, 0.0915829,
0.0547699, 0.0826791, 0.0883616, 0.0977739],
[0.0875183, 0.0790368, 0.101146 , 0.0777582, 0.104289 , 0.0775479,
0.156569 , 0.0999909, 0.0905242, 0.161871 ],
[0.1427 , 0.1211 , 0.15661 , 0.113337 , 0.135986 , 0.1384 ,
0.181515 , 0.159102 , 0.200004 , 0.187535 ],
[0.163381 , 0.186425 , 0.174798 , 0.14191 , 0.1514 , 0.166044 ,
0.199063 , 0.146319 , 0.173303 , 0.144067 ],
[0.182485 , 0.16901 , 0.11 , 0.127162 , 0.0858656, 0.1564 ,
0.161187 , 0.0588985, 0.110706 , 0.0560944],
[0.103804 , 0.109948 , 0.0707144, 0.0493536, 0.0471329, 0.0708205,
0.048201 , 0.0487304, 0.069967 , 0.0947939],
[0.0382397, 0.0918 , 0.101197 , 0.102453 , 0.135943 , 0.0867575,
0.123071 , 0.0970329, 0.099906 , 0.101536 ],
[0.113361 , 0.167597 , 0.141526 , 0.0792396, 0.118 , 0.065764 ,
0.0915817, 0.1183 , 0.149376 , 0.118608 ],
[0.10647 , 0.1566 , 0.1303 , 0.139754 , 0.174465 , 0.148458 ,
0.187625 , 0.132805 , 0.171687 , 0.158161 ],
[0.15319 , 0.174204 , 0.161628 , 0.127377 , 0.173368 , 0.145292 ,
0.208068 , 0.168076 , 0.14961 , 0.124334 ]]

plt.imshow(noisy_data, cmap ="jet")
plt.colorbar()


I know that without an underlying model, it's very difficult to distinguish between noise and the signal

but given the nature of the subsurface rock property data which has to be of close values if located close to each other for every range of the data (same range without having outliers or data points that are suddenly too low or too large), in other words, if are located close to each other,

I was wondering is there is any way to describe or quantify the noise.

Continue reading...