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the people who commissioned the study. Their views may require using a model
that has more complexity than required from a technical modeling perspective.
Non-reservoir requirements include personnel, simulator availability, and
cost effectiveness. Personnel will be needed to gather and evaluate data, prepare
input data, perform the history match, and then make predictions. Data gathering
may take a few days or several months depending on the quality and extent of
the data base for a particular field. The history matching and prediction phases
do not necessarily have to be done by the same modeler. In some companies,
history matching is done in a collaborative effort between a specialized tech-
nology center and a field office, while most of the prediction work is completed
in the field office. This takes advantage of specialized expertise: technology
centers, including outside consultants, routinely set up and ran models, while
day-to-day changes that impact production operations are handled in the field
office. The division of labor between history matching and prediction makes
sense in some circumstances.
A wide variety of simulators are available for a price. The work horse
simulators - black oil and compositional - can often be leased on an as-needed
basis or are available through computer networks. More specialized simulators
may be obtained from software vendors, or as publicly available research codes
developed at university and government laboratories.
As complexity increases, so also does cost. A good economic argument
to support Ockham's Razor is to remember that the latest technology is not
always the best technology for a project, and its use comes with a cost. Modeling
teams are often tempted to apply the latest technology, even if it is not warranted.
An example is the use of local grid refinement (LGR) to model horizontal wells.
LGR is an innovative grid preparation technique that can improve spatial
resolution, but at a substantial increase in computer cost and simulator sophisti-
cation. It is very common to find LGR used to model horizontal wells. In some
cases, such as feasibility studies, this level of technical detail exceeds the needs
of the study objectives and simply adds cost to the project without adding the
corresponding value. A wise modeling team will match the level of technology
with the objectives of the study. The result will be the selection of the most cost
effective method for achieving study objectives.