Abstract
Formation water is one of the problem in oil fields, in terms of
production as well as environmental. When it reaches the surface or
shallow groundwater system, then it will interact with main water supply
in the area. In this paper we discuss a robust principal component
analysis method to characterise both water bodies and how its
interactions. This multivariable approach will reduce the number of
variable in to fewer set for easier analysis and interpretation.
We re-use with permission a nice dataset from Po Plain area Italy, as a
”toy” dataset in the analysis. Here we also use some geothermal water
data in the analysis to show the contrast. We use R, an open source
statistical package to run the model. We also compare the PCA model from
two packages: Pcamethods and FactomineR to test the consistency.
Aside to the trace elements like Sr, Br, and I, we can also
differentiate formation water from shallow groundwater using alkalinity
(Alk) major elements Ca, Mg, Na, K, Cl, SO, H, O, C, and trace elements
Sr, Br, I, Fe. PCA technique can amplify the contrast of concentration
of major elements to show the differentiation. In the biplot we can see
that formation water samples from oil fields are fall in the region of
Cl and SO4, while geothermal water show stronger control
of HCO3. The shallow groundwater however, fall randomly
in the area of Ca and Mg due to the natural water-rock interaction
processes.
The PCA model presented in this paper, can be used as an example to
finger print water system based on the hydrochemistry. The biplot can
also help environmental division to do a fast and robust water quality
classification in the field.
Key words: formation mater, meteoric water, R statistical package, PCA