Page 203 - Principles of Applied Reservoir Simulation 2E

188 Principles of Applied Reservoir Simulation

discontinuity in rate is observed between the end of history and the beginning
of prediction. The rate difference usually arises because the actual well PI,
especially skin effect, is not accurately modeled by the model PL An adjustment
to model PI needs to be made to match final historical rate with initial predicted
rate.
The next step is to prepare a base case prediction. The base case prediction
is a forecast assuming existing operating conditions apply. For example, the base
case for a newly developed field that is undergoing primary depletion should
be a primary depletion case that extends to a user-specified economic limit. By
contrast, if the field was being waterflooded, the waterflood should be the base
case and alternative strategies may include gas injection and WAG (water-
altemating-gas).
The base case prediction establishes a basis from which to compare
changes in field performance resulting from changes in existing operating
conditions. In addition, a sensitivity analysis should be performed to provide
insight into the uncertainty associated with model predictions. A procedure for
conducting a sensitivity analysis is outlined below.

19.3 Sensitivity Analyses

Sensitivity analyses are often needed in both the history matching and
prediction stages [for example, see Crichlow, 1977; Mattax and Dalton, 1990;
Saleri, 1993; and Fanchi, et al, 1996]. Any method that quantifies the uncer-
tainty or risk associated with selecting a particular prediction case may be viewed
as a sensitivity analysis. An example of a sensitivity analysis technique that is
cost-effective in moving a history match forward is conceptual modeling. It can
be used to address very specific questions, such as determining the impact of
fluid contact movement on hydrocarbon recovery. Similarly, window models
that study such issues as the behavior of a horizontal well in a fault block provide
useful information on the sensitivity of a model to changes in input parameters.
Another example of a sensitivity analysis technique is risk analysis.
Murtha [1997] defines risk analysis as "any form of analysis that studies and
hence attempts to quantify risks associated with an investment." Risk in this