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ENHANCED
USE OF NUMERICAL METHODS FOR
RESERVOIR DESCRIPTION USING WELL TEST AND
PRODUCTION DATA
Well test and production data analysis
are two primary techniques for dynamic
reservoir description. These two
approaches are traditionally based on
simplified and average analytical
solutions. However, these idealized
solutions cannot be easily used for
complex reservoir characterization
studies. Without having efficient data
integration methods and a robust flow
simulator, conducting numerical studies
become cumbersome. The purpose of this
project is to design new and adapt
existing workflows for efficient data
analysis and dynamic reservoir description
in well testing and production data
analysis.
ENHANCED
TECHNIQUES FOR HISTORY MATCHING AND
FORECASTING
History matching refers to calibrating
numerical or analytical models by observed
data. However, this task can be very
challenging in the presence of complex
geology and/or many unknown data. The
purpose of this project is to introduce
and apply new techniques for building
predictive history-matched models for
reservoir characterization of conventional
and unconventional reservoirs, which can
be used for probabilistic forecast and
uncertainty quantification. The purpose of
this project is to design new and adapt
existing workflows that can enhance the
history matching task in various problems.
This includes the use and applications of
state-of-the-art methods that can
represent the geology and can efficiently
and accurately calibrate the dynamic
models by minimizing the computational
cost.
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