One if the Watercut Diagnostics plots with  water cut (Y_w) along y-axis and inverse liquid rate  $//<![CDATA[ \begin{array}{l}1/q_L\end{array} //]]>$ along x-axis (see Fig. 1 – Fig. 3).

The absence of correlation between Y_w and liquid rate suggest that either produced water is all good or it may have bad water production from the reservoir with the same formation pressure as oil pay: $//<![CDATA[ \begin{array}{l}P_{\, {\rm bad} \, {\rm water}} = P_{{\rm oil} \, {\rm pay}}\end{array} //]]>$ (see Fig. 1).

In practice, it is very rare occasion that bad water has the same formation pressure as the oil pay: $//<![CDATA[ \begin{array}{l}P_{\, {\rm bad} \, {\rm water}} = P_{{\rm oil} \, {\rm pay}}\end{array} //]]>$ and usually the absence of correlation between Y_w and liquid rate indicates that all produced water is good.

The negative correlation between Y_w and inverse liquid rate $//<![CDATA[ \begin{array}{l}1/q_L\end{array} //]]>$ suggests that produced water contains bad water with lower formation pressure than that of oil pay: $//<![CDATA[ \begin{array}{l}P_{\, {\rm bad} \, {\rm water}} < P_{{\rm oil} \, {\rm pay}}\end{array} //]]>$ (see Fig. 2).

The positive correlation between Y_w and inverse liquid rate $//<![CDATA[ \begin{array}{l}1/q_L\end{array} //]]>$ suggests that produced water contains bad water with higher formation pressure than that of oil pay: $//<![CDATA[ \begin{array}{l}P_{\, {\rm bad} \, {\rm water}} > P_{{\rm oil} \, {\rm pay}}\end{array} //]]>$ (see Fig. 3).

There is no clear regulation on what value of correlation is enough to discriminate between the cases on Fig. 1 – Fig. 3.

This is usually done by an eye pick or artificial intelligence and stands as a part of the complex Watercut Diagnostics.

Some people see that growing Y_w with increasing of liquid rate for low-pressure bad water is counter-intuitive but in reality this is a solid fact which can be easily verified mathematically and/or tested in practise.

The YLIQ analysis is not always applicable as sometimes well produces at constant rate and correlation with watercut can not be assessed.

But even when historical rates were varying the YLIQ analysis does not provide the unique answer on whether produced water contains bad water.

Nevertheless, in many practical cases YLIQ analysis is very helpful as additional argument (and sometimes as the key argument) in assessing if produced water contains bad water.

Cases

Case 1

Case 2

Case 3

See Also

Petroleum Industry / Upstream /  Production / Subsurface Production / Field Study & Modelling /  Production Analysis / Watercut Diagnostics