To perform better interpretation in
making the right and effective decisions, valuable information is needed. This research
defines and evaluates measurement models to measure information value. The
models will be based on theory and practical experiences showing the value of
information and the foundation. Information can be improved and can provide
better support in decision making. The models should be concise, clear and
broadly applicable, though they should be adapted to energy companies to get
the most out of them.

The value of information will be considered
in terms of a possible gain in value with further information on Shaly Sand
reservoirs interpretation, as well as a loss in value associated with the
absence of information.  It is important
that an operating company collect as much information about the reservoir as
the economics of the project allows.  In
addition to seismic and wireline logs, core data, geological data, regional
data, and information from nearby wells can be extremely valuable in making
economic decisions.  Obtaining this data
requires trained professionals from both the operating company and service
companies, working together to get the best possible interpretation.

Over the years, operating
companies have found that service companies can offer many of the processes
once performed in house at a lower cost and at a highly quality.  For example, a wireline expert from Service
company may have experience with a wide range of reservoirs, as opposed to an
operating company engineer who deals only with a limited number of
reservoirs.  Of course, the operating
company engineer will have much more detailed information about his own
reservoirs, so it is necessary that the two work closely together.

One of
the most controversial problems in formation evaluation is the shale effect in
reservoir rocks. An accurate determination of formation porosity and fluid
saturation in Shaly sand is subjected to many uncertain parameters, all are
induced by the existence of shale in pay formation. Shales are one of the more
important common constituents of rocks in log analysis. Aside from their
effects on porosity and permeability, this importance stems from their
electrical properties, which have a great influence on the determination of
fluid saturations.  Through the years, log interpretation has been
performed in a sequential process of logical operation. The log analyst
determines one parameter and then another until the problem is logically



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