“net reservoir”. The reservoir flag is an indication
of which intervals (based on petrophysical criteria)
may be regarded as reservoir, or non-reservoir,
intervals.
• Input to fluid and saturation models – such as saturation logs, saturation height functions, fluid
contacts, and fluid properties.
All logs are associated with a variable degree of
uncertainty. Permeability logs are regarded as more
uncertain than porosity logs, and horizontal wells have
usually less accurate measurements than vertical wells
(Chap. 16).
22.2.2.3 Geological Data
Geological data and analysis embraces a wide variety
of input to reservoir models, both quantitative and
qualitative. It is vital to understand the genesis and
depositional signature of the subsurface interval of
interest, in order to delineate the overall architecture
of the reservoir. For example, the geological data input
could be:
• Reservoir zonation and sedimentological description, including identification of flow units
(modelling facies, see Sect. 22.3.3.4) and barriers.
Sedimentological core descriptions are a very
important input here.
• Various stratigraphic models, including sequence
stratigraphic models and lithostratigraphic models
(Chaps. 7 and 8). This also includes palogeographic
maps which may be quite important for understanding trends and architectural topology within reservoir units in the model construction.
• Evaluation of compaction and diagenesis, including impact on reservoir property distribution (see
Chaps. 4 and 21).
22.2.2.4 Reservoir Technical Data
Reservoir technical data includes data that are related
to dynamic understanding of the reservoir. Typical
reservoir technical data are:
• Pressure data, both those observed prior to production and the pressure development during
production.
• Various fluid data and PVT data, such as
viscosities, fluid densities, B o , B g (shrinkage factors
for oil and gas), etc.
• Well test data and production history in general.
These data are usually applied during calibration of
reservoir model, known as history matching
(Sect. 22.4.3).
22.2.2.5 Databases and Data Management
All data input to reservoir modelling need to be easily
accessible. A database is an organised collection of
data, and includes digital data as well as paper reports.
The purpose of a database is to provide efficient
retrieval for the task to be performed – in this case
reservoir modelling.
A major challenge is that data need to be thoroughly
quality checked prior to modelling as even apparently
small errors in parameters such as well data may be
magnified when propagated into the models, which in
turn can lead to erroneous models and hence wrong
decisions with large financial consequences.
The subsurface database may be vast. Seismic data
alone requires enormous amounts of data storage. A
common problem is that different software products
have their own databases, and transferring data
between different databases and applications can be
demanding. As software tools are upgraded, data
import and export formats may change, and new data
types may be required.
Working with the database prior to the actual
modelling is an important and time consuming task,
and sometimes the database preparations and quality
control may take more resources than the actual
modelling. It is important to acknowledge this early in
the model planning, to avoid delays and errors in the
actual modelling.
22.2.3 The Conceptual Model
The conceptual model can be defined as a synthesis of
our understanding of the reservoir targeted for
modelling, based on all available input data from all
the subsurface disciplines (see Sect. 22.2.2). In many
cases, it will also be crucial to include additional
information, such as well data from neighbouring
fields, regional models and understanding, experience
from analogue producing fields, and/or outcrop data.
Typically the conceptual model can be summarised
with a number of drawings and qualitative
descriptions prior to the modelling.
22 Introduction to Reservoir Modelling
563
of which intervals (based on petrophysical criteria)
may be regarded as reservoir, or non-reservoir,
intervals.
• Input to fluid and saturation models – such as saturation logs, saturation height functions, fluid
contacts, and fluid properties.
All logs are associated with a variable degree of
uncertainty. Permeability logs are regarded as more
uncertain than porosity logs, and horizontal wells have
usually less accurate measurements than vertical wells
(Chap. 16).
22.2.2.3 Geological Data
Geological data and analysis embraces a wide variety
of input to reservoir models, both quantitative and
qualitative. It is vital to understand the genesis and
depositional signature of the subsurface interval of
interest, in order to delineate the overall architecture
of the reservoir. For example, the geological data input
could be:
• Reservoir zonation and sedimentological description, including identification of flow units
(modelling facies, see Sect. 22.3.3.4) and barriers.
Sedimentological core descriptions are a very
important input here.
• Various stratigraphic models, including sequence
stratigraphic models and lithostratigraphic models
(Chaps. 7 and 8). This also includes palogeographic
maps which may be quite important for understanding trends and architectural topology within reservoir units in the model construction.
• Evaluation of compaction and diagenesis, including impact on reservoir property distribution (see
Chaps. 4 and 21).
22.2.2.4 Reservoir Technical Data
Reservoir technical data includes data that are related
to dynamic understanding of the reservoir. Typical
reservoir technical data are:
• Pressure data, both those observed prior to production and the pressure development during
production.
• Various fluid data and PVT data, such as
viscosities, fluid densities, B o , B g (shrinkage factors
for oil and gas), etc.
• Well test data and production history in general.
These data are usually applied during calibration of
reservoir model, known as history matching
(Sect. 22.4.3).
22.2.2.5 Databases and Data Management
All data input to reservoir modelling need to be easily
accessible. A database is an organised collection of
data, and includes digital data as well as paper reports.
The purpose of a database is to provide efficient
retrieval for the task to be performed – in this case
reservoir modelling.
A major challenge is that data need to be thoroughly
quality checked prior to modelling as even apparently
small errors in parameters such as well data may be
magnified when propagated into the models, which in
turn can lead to erroneous models and hence wrong
decisions with large financial consequences.
The subsurface database may be vast. Seismic data
alone requires enormous amounts of data storage. A
common problem is that different software products
have their own databases, and transferring data
between different databases and applications can be
demanding. As software tools are upgraded, data
import and export formats may change, and new data
types may be required.
Working with the database prior to the actual
modelling is an important and time consuming task,
and sometimes the database preparations and quality
control may take more resources than the actual
modelling. It is important to acknowledge this early in
the model planning, to avoid delays and errors in the
actual modelling.
22.2.3 The Conceptual Model
The conceptual model can be defined as a synthesis of
our understanding of the reservoir targeted for
modelling, based on all available input data from all
the subsurface disciplines (see Sect. 22.2.2). In many
cases, it will also be crucial to include additional
information, such as well data from neighbouring
fields, regional models and understanding, experience
from analogue producing fields, and/or outcrop data.
Typically the conceptual model can be summarised
with a number of drawings and qualitative
descriptions prior to the modelling.
22 Introduction to Reservoir Modelling
563