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Chapter
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3.E.7
Diagnostic
After extraction, data problems overlooked in the initial quality control may become apparent,
requiring further data editing, and a new extraction.
Looking at the derivative response will generally be the starting point of this process.
Individual features in the derivative signature will be considered, validated or rejected, and
potentially associated to a well, reservoir or boundary model. These possible assumptions
must then be compared to what is already known from other sources.
Depending on the diagnostic, the loglog and semilog plots can be complemented by other
specialized plots to identify specific flow regimes by straight line analysis. However this
approach has been made largely redundant by the introduction of the modern approach. The
engineer will have the choice of the pressure function, the time function and the type of
superposition that will be applied to the time function; raw function, tandem superposition for
simple buildups, or multirate superposition.
Depending on the prior knowledge and the complexity of the response, the problem may be
very quickly restricted to one or two alternatives, or the range of possibilities may remain
large. For exploration wells, the uncertainty in the explanation may stand, and alternative
explanations may be presented in the ‘final’ report. Further tests and increased knowledge of
the reservoir could allow, later, narrowing down the range of possibilities, months or years
after the initial interpretation.
3.E.8
Model generation
The engineer, after diagnosing the behavior, will then select one or several candidate models.
The process below will be duplicated for each considered model.
The objective is to use the modelling capability of the software to match in part or in totality
the pressure response. This will consist of selecting one or several models, which may be
analytical or numerical. Then, entering a first estimate of the model parameters, running the
model and comparing the simulated results with the real data, on all relevant plots.
AI based Model advisers may be used to speed up the process by detecting if a derivative
response can be explained by a certain combination of well, reservoir and boundary models,
and produce a first estimate of the model parameters with no user interaction.
Today’s software products offer a wide choice of analytical models. Typically the user will
select a wellbore, a well, a reservoir and a boundary model. Unfortunately, our ability to solve
problems mathematically is limited, and all combinations of well, reservoir and boundary
models may not be available. This is sometimes frustrating to the engineer, as in this case
only portions of the response can be matched at any one time.
There are many ways to estimate parameters: (1) from the results of specialized plots that
may have been created in the analysis; (2) from straight lines drawn on the loglog plot
(wellbore storage, IARF, fractures, closed systems, etc.); (3) from interactive features picking
the corresponding part of the derivative signature; (4) by manual input.