interval is defined by stratigraphic surfaces/layering
and faults, represented by a three-dimensional grid.
• The property model, defining how petrophysical
reservoir properties and other relevant properties
are distributed in three dimensions within the reservoir container/grid. It usually also includes a
numerical description of the spatial distribution of
the reservoir fluids, e.g. oil and/or gas saturation
(through water saturation modelling).
To provide high quality input to a model, it is
important to stress that a reservoir model represents a
synthesis of several sub-surface disciplines’ description and understanding of the reservoir. The goal is to
establish a common model that can be used for determining and optimising the commercial value of a
hydrocarbon accumulation. Close communication,
co-operation, and planning between the involved
disciplines are key points for constructing a successful
model that is useful for its intended purposes. As there
are many ways to create a digital model, having a clear
and well defined business objective for the modelling
effort is another important success factor. Disciplines
that typically are involved with modelling are
petrophysics, various disciplines in geology (such as
sedimentology, petrography, diagenesis, stratigraphy,
biostratigraphy, geochemistry and structural geology),
geophysics, production technology, reservoir engineering, statistics and computer sciences. Due to
the major implementation of reservoir models in
the oil industry in the last two decades, being a
“geomodeller” or “reservoir modeller” has become a
discipline by itself.
22.2 Model Planning
Before starting any modelling work there are some fundamental questions that need answers, as model work may be
time consuming and requires significant manpower. One
should also collect all possible data and knowledge of the
reservoir to be modelled, including experience from previous models. Hence, proper model planning is important
before starting the actual model work.
22.2.1 Business Objectives
The process of constructing a new reservoir model
should always start by defining the business
objectives, e.g. why are we making a reservoir
model? What is the purpose of the model? What kind
of questions is the model going to provide answers to?
Business objectives may vary substantially depending
on where an individual field is in its life cycle. Here
are some examples of modelling objectives and the
consequences to the scope of the work:
• Calculating oil or gas in-place volumes. This objective is often the most important in the exploration
and early field development phase. Generally, it
implies the use of more simplistic models with
less focus on the detailed architecture of the reservoir. Usually, several alternative models are made
to capture volume uncertainty (see Sect. 22.5).
• Calculating recoverable volumes and establishing
production profiles. This objective becomes a priority in the field development and production stage.
It generally requires a more detailed and sophisticated description of reservoir architecture and distribution of reservoir properties to be able to
simulate how fluids are flowing through the reservoir during production. A common way to calibrate
the models with production data is so-called history
matching (Sect. 22.4.3).
• Optimising the depletion plan for a field. This objective is tightly linked to the previously described
business objective and therefore has many of the
same requirements. The depletion plan describes
how to optimally drain the reservoir. This includes
not only optimising the recoverable reserves, but
also the economy of the field in question. Some
typical aims of depletion planning could include:
– Evaluating depletion vs. gas and/or water
injection.
– Optimising number of wells.
– Evaluating well geometries, e.g. vertical, slanted
or horizontal wells. Would it be economical or
beneficial to use branched wells?
• Well planning. This objective may demand an even
higher degree of detail in the reservoir model.
22.2.2 Input Data and Databases
There are numerous data sources that can be utilised
for reservoir modelling (Fig. 22.3). Examples of
important data are given in the following sub-sections.
22.2.2.1 Geophysical Data
The dominant geophysical input to reservoir
modelling is seismic data. Other geophysical data
22 Introduction to Reservoir Modelling
561
and faults, represented by a three-dimensional grid.
• The property model, defining how petrophysical
reservoir properties and other relevant properties
are distributed in three dimensions within the reservoir container/grid. It usually also includes a
numerical description of the spatial distribution of
the reservoir fluids, e.g. oil and/or gas saturation
(through water saturation modelling).
To provide high quality input to a model, it is
important to stress that a reservoir model represents a
synthesis of several sub-surface disciplines’ description and understanding of the reservoir. The goal is to
establish a common model that can be used for determining and optimising the commercial value of a
hydrocarbon accumulation. Close communication,
co-operation, and planning between the involved
disciplines are key points for constructing a successful
model that is useful for its intended purposes. As there
are many ways to create a digital model, having a clear
and well defined business objective for the modelling
effort is another important success factor. Disciplines
that typically are involved with modelling are
petrophysics, various disciplines in geology (such as
sedimentology, petrography, diagenesis, stratigraphy,
biostratigraphy, geochemistry and structural geology),
geophysics, production technology, reservoir engineering, statistics and computer sciences. Due to
the major implementation of reservoir models in
the oil industry in the last two decades, being a
“geomodeller” or “reservoir modeller” has become a
discipline by itself.
22.2 Model Planning
Before starting any modelling work there are some fundamental questions that need answers, as model work may be
time consuming and requires significant manpower. One
should also collect all possible data and knowledge of the
reservoir to be modelled, including experience from previous models. Hence, proper model planning is important
before starting the actual model work.
22.2.1 Business Objectives
The process of constructing a new reservoir model
should always start by defining the business
objectives, e.g. why are we making a reservoir
model? What is the purpose of the model? What kind
of questions is the model going to provide answers to?
Business objectives may vary substantially depending
on where an individual field is in its life cycle. Here
are some examples of modelling objectives and the
consequences to the scope of the work:
• Calculating oil or gas in-place volumes. This objective is often the most important in the exploration
and early field development phase. Generally, it
implies the use of more simplistic models with
less focus on the detailed architecture of the reservoir. Usually, several alternative models are made
to capture volume uncertainty (see Sect. 22.5).
• Calculating recoverable volumes and establishing
production profiles. This objective becomes a priority in the field development and production stage.
It generally requires a more detailed and sophisticated description of reservoir architecture and distribution of reservoir properties to be able to
simulate how fluids are flowing through the reservoir during production. A common way to calibrate
the models with production data is so-called history
matching (Sect. 22.4.3).
• Optimising the depletion plan for a field. This objective is tightly linked to the previously described
business objective and therefore has many of the
same requirements. The depletion plan describes
how to optimally drain the reservoir. This includes
not only optimising the recoverable reserves, but
also the economy of the field in question. Some
typical aims of depletion planning could include:
– Evaluating depletion vs. gas and/or water
injection.
– Optimising number of wells.
– Evaluating well geometries, e.g. vertical, slanted
or horizontal wells. Would it be economical or
beneficial to use branched wells?
• Well planning. This objective may demand an even
higher degree of detail in the reservoir model.
22.2.2 Input Data and Databases
There are numerous data sources that can be utilised
for reservoir modelling (Fig. 22.3). Examples of
important data are given in the following sub-sections.
22.2.2.1 Geophysical Data
The dominant geophysical input to reservoir
modelling is seismic data. Other geophysical data
22 Introduction to Reservoir Modelling
561