The Data Plot
Different well test analysis softwares are available in the market. Most of them have more or less the same well testing tools: the derivative plot, superposition, the data plot (also sometimes called simulation plot, production history plot, etc…) and deconvolution.
In this note, let’s have a look at the Data Plot.
Gauge pressure and rate data are plotted versus time in a Cartesian scale.
The data plot can be used for:
This plot is first used to quickly assess any long-term trend in gauge pressure data. This could give some indication in particular on the evolution of the well productivity index, total compressibility, reservoir pressure over time, interference, etc… In addition, the way the pressure data builds up during a shut-in period could give some qualitative information on the reservoir permeability thickness.
The data plot isn’t the main tool that drives the interpretation, it is more of a verification tool. The interpretation model will simulate the pressure values according to the given rate history. The simulated pressure data should be compared with actual data in the Data Plot.
The PBU tests should be matched. If not, explanations should be found. This could be due to a wrong interpretation model, an incorrect initial pressure value Pi, an incorrect permeability value in the model, the need to add/remove boundaries or the need to add/remove some reservoir regions at different mobilities/storativities.
It could also be that the reservoir/well behaviour changes over time and the pressure data simply cannot be modelled with a simple analytical model with some fixed reservoir and well parameters. This could include a change of phase in the reservoir (changing the total compressibility), a change in fluid density below the gauge, a change in total KH (due to a well intervention), interference with other wells, etc…
Once the PBU tests are matched, any discrepancy between actual and calculated pressure data during periods of production (drawdown periods) should be understood. This could indicate an error in the interpretation model, an error in the rate data or a change in reservoir/well characteristics (change in skin due to clean-up, stimulation, fluid/gas breakout, etc…).
As a quick guide, the figure below suggests the impact of an erroneous skin value on the calculated pressure data.
As seen in the figure above, the skin value does not have any impact on the PBU match. However, it may explain any discrepancy between the calculated and actual pressure data during drawdown (production) periods.
For more information or for a discussion on this topic, please don’t hesitate to contact us.
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