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recovery process where heat has been injected in some form, then we need to
use a simulator that accounts for temperature variation and associated thermody-
namic effects. The set of algorithms is sufficiently complex that high-speed
computers are the only practical means of solving the mathematics associated
with a reservoir simulation study. These topics are discussed in more detail in
later chapters.

10.4 Major Elements of a Reservoir Simulation Study

The essential elements of a simulation study include matching field
history; making predictions, including a forecast based on the existing operating
strategy; and evaluating alternative operating scenarios [Mattax and Dalton,
1990; Thomas, 1982], During the history match, the modeler will verify and
refine the reservoir description. Starting with an initial reservoir description,
the model is used to match and predict reservoir performance. If necessary, the
modeler will modify the reservoir description until an acceptable match is
obtained. The history matching phase of the study is an iterative process that
makes it possible to integrate reservoir geoscience and engineering data.
The history matching process may be considered an inverse problem
because an answer already exists. We know how the reservoir performed; we
want to understand why. Our task is to find the set of reservoir parameters that
minimizes the difference between the model performance and the historical
performance of the field. This is a non-unique problem since there is usually
more than one way to match the available data.
Once a match of historical data is available, the next step is to make a base
case prediction, which is essentially just a continuation of existing operating
practice. The base case prediction gives a baseline for comparison with other
reservoir management strategies.
Model users should be aware of the validity of model predictions. One
way to get an idea of the accuracy of predictions is to measure the success of
forecasts made in the past. Lynch [1996] looked at the evolution of the United
States Department of Energy price forecast over a period of several years for
both oil and gas. The quality of price forecasts is illustrated in Figure 10-3,