I am trying to resolve the following problem
There is a set of samples that are regularly spaced in location or you may say it has a 2D grid distributed.
After a while a second measurement is performed exactly on the same grid nodes to find the changes of the measured property in each sample location.
I am expecting some differences but the changes between two sets shows some exaggeration and a little bit far from reality. I think the second data set is not showing the same range as the first data set for some reason. I wanted to compare the first sample set with the second and see the differences in each point or location. I can't exactly explain source of that exaggeration but I want to minimize this phenomena. My question is if I can bring the second data set in the same range of the first data set . Is this a bias issue?? and what would you suggest me to do? Do I need to normalize both data sets and then compare them. In this case which method do you recommend for normalization. For me the most important thing is comparison between the two sets and find the relative increase and decrease between the samples of the two sets.
Also I would appreciate if you recommend me any references or papers regarding a similar case.
Your advises would be highly appreciated.
Reza Nazarian
Schlumberger Information Solutions
SONILS Oil Services Centre, Porto de Luanda, Angola
( Via UK: +44 (0)207 576 6306
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