3. Static model development |
Section 1 Introduction to static reservoir
modeling
Section 2
For decision making and improving the estimation of
reserves; a computer model of a reservoir is constructed
Section 3
which we call as “The Reservoir Model”.
Section 4
Section 5
4. Building the model
Real Model Computer Model ……How ??
CLICK HERE FOR MORE INFO
6. Introduction to static reservoir modeling
Geocellular modeling
It is a way to describe the subsurface in 3D space
(mathematically), which is constrained by a structural
and stratigraphic framework.
In a layman’s language, it is the process of generating
the model/prototype of the subsurface. This model will
resemble the real reservoir model.
The physical properties of the reservoir are stored at the
grid points or at the centers of gravity (3D voxels).
So the first thing is to define the GRID
7. Introduction to static reservoir modeling
Grid
The simulation grid is the definition of how we divide, or
discretize, space in order to solve the differential
equations numerically.
Common grid co-ordinate system includes
Cartesian
Cylindrical
Corner Point
Curvilinear
8. Grid Simulation |
Selection of proper GRID
It is necessary that the grid that is defined should have desired level of accuracy in
the solution of the flow equations; properly represents the reservoir geology;
locations of wells, boundaries, faults, etc. and has the lowest computer memory
and time requirements to solve the problem.
Common rules of constructing GRID
In case of cylindrical grid system, the grid spacing is at logarithmic scale
difference.
The grid spacing should be such that the adjacent block size should not
increase by the factor more that 3.
Even the pressure drop between the blocks should not decrease by 30-20 %.
Reservoir flow units should be separated by grid block boundaries.
Vertical discretization should be fine enough for accurate accounting of gas
percolation and migration and/or gravity over-ride or under-ride
9. Grid Simulation | using CMG simulator (version 2007.1)
GRID type (Cartesian,
corner or cylindrical)
# of grid blocks in x, y and z
direction respectively
Here, 10 is width of
the block and 3 is
the # of blocks in
each direction
10. Grid Simulation | using CMG simulator (version 2007.1)
Date @ which
simulation starts
A block with
width 10m each
in x, y & z
direction
12. Static model development |
Section 1 Structural modeling
Section 2 .
Section 3
Section 4
Section 5
13. Structural Modeling |Using Petrel 2009 Seismic Simulator
Identifying structural top
Structural top identification means recognizing the geometric
structure of hydrocarbon trap.
The workflow(in petrel) for the same would be :
Load SEG-Y format data.
Interpret it manually.
Full range of tools allows us to take a traditional line-by-line
approach combined with the latest algorithms and tools
including amplitude & waveform based tracking for best
interpretation, allowing us to achieve rapid results
14. Structural Modeling |Using Petrel 2009 Seismic Simulator
Interpreting set of faults
Since the presence of fault/set of faults directly makes a huge
difference to the field development plan and production
characteristics…we need to carefully investigate it’s presence.
Fault can be interpreted in the same way (as we seen the
workflow in case of structural top).
But consider only Sealing faults !!!
BUT STILL …
THERE CAN BE NUMEROUS FAULTS
SO, MANUAL INTERPRETATION BECOMES TEDIOUS !
15. Structural Modeling |Using Petrel 2009 Seismic Simulator
So many faults
Can we do it
automatically
???..
16. Structural Modeling |Using Petrel 2009 Seismic Simulator
The Petrel Automated Structural All u need is ANT
Interpretation module uses an TRACKING module
advanced computing algorithm "Ant
Tracking" to overcome the tedious task.
Benefits :
Increases structural accuracy
and detail & thus provides
unbiased, repeatable & highly
detailed mapping of
discontinuities.
Significantly reduces tedious
manual interpretation time.
17. Structural Modeling |Using Petrel 2009 Seismic Simulator
The Ant Tracking workflow consists of four independent steps:
Enhance the spatial discontinuities in your seismic data using
any edge detection algorithm (i.e. variance, chaos, edge
Step 1 detection) and optionally, pre-condition your seismic data by
reducing noise.
Generate the Ant Track Cube and extract the fault patches.
Step 2
Validate and edit the fault patches.
Step 3
Create final fault interpretation model.
Step 4
18. Static model development |
Section 1
Stratigraphic modeling
Section 2
.
Section 3
Section 4
Section 5
19. Stratigraphic Modeling |Analytical approach
Analytically the best technique to establish the correlation between the
geological units is by using the sequence stratigraphic method.
As per this technique the deposition of sedimentary bodies is governed by the
combined effects of changes in sea-level, sedimentation, subsidence and tectonics.
On this basis, we can identify sequences of different hierarchical order within a
geological unit that are separated by
sequence boundaries which represent
Unconformities or maximum flooding
surfaces.
22. Stratigraphic Modeling |Petrel v2009 Simulator
In Petrel we can display and organize your logs in a flexible 2D visualization
environment.
23. Stratigraphic Modeling |Petrel v2009 Simulator
A flexible 2D canvas allows simultaneous display of logs, seismic, 3D grid, and
simulation results.
24. Stratigraphic Modeling | Petrel v2009 Simulator
The workflow for correlation can be
given as follows :
[1] Import well log las-file data :
By importing well trajectories, well
deviations and logs(las file) you can
pick/select any horizon top and analysis
it.
[2] Create cross sections :
Under “window” option select “new
well section window”. Then you can
select the #of wells (to display their
cross section)
Then after you can carry out other
secondary operations (colorfill,
thickness etc.)
25. Stratigraphic Modeling | Petrel v2009 Simulator
[3] Revise formation top picks &
compare:
Pick horizon tops in the well panel and
see the effects directly in 3D, or vice
versa.
Now you can compare the required
section of the well log to other sections
by using “ghost curve” option in the right
hand side bar of petrel.
Using ghost curve you can clip out a small
section of your seismic and drag it over to
other parts to correlate across
faults.
(refer to next slide)
26. Stratigraphic Modeling | Petrel v2009 Simulator
Now after selecting the portion, you can
drag it to the other portion of the log to
figure out the similarity between them.
(see the yellow curves in box)
This operation is called ghosting.
[4] Evaluate real-time updated picks in
2D and 3D interpretation windows :
You can view the real time updated picks
by turning ON (simply click on it) the well
section fence.
27. Static model development |
Section 1 Lithological modeling
Section 2
.
Section 3
Section 4
Section 5
28. Lithological Modeling |
As a rule, facies Modeling can be performed using appropriate deterministic or
stochastic functions which allow us to generate 2 or 3 dimensional spatial
distributions of significant characteristics, such as porosity and permeability, directly
from well data.
The idea behind this procedure is that the petrophysical characteristics of the
reservoir can be considered intimately linked to the lithological facies.
In practical terms, the lithological model of a reservoir is constructed by
integrating an ideal representation of the reservoir (sedimentological model), a
classification stage (definition of facies) and a spatial distribution stage (three-
dimensional model).
29. Lithological Modeling |
.
Classification of
facies
Sedimentological
Model
3D distribution
of facies
Lithological Modeling
31. Static model development |
Section 1 Petrophysical modeling
Section 2
.
Section 3
Section 4
Section 5
32. Petrophysical Modeling |using Petrel v2004
.The values between the cells are
interpolated by various techniques. Two • Select the Moving average as the
of the important techniques are: .
Method; leave all other settings as
• Deterministic Model default.
• Stochastic Model • Click on OK; display the model in 3D
window and it would appear like :
Deterministic Model
It uses moving average method, based on
inverse distance weighting.
• Open the petrophysical process option
from the menu.(this will open a dialog
box)
• From the dialog box, select Use Existing
Property and select the Porosity property
as the property to be modeled from the
drop down menu.
33. Petrophysical Modeling |using Petrel v2004
. Stochastic Model .
Stochastic method : user
This method uses Sequential Gaussian
defined variogram and range.
Simulation method. To create stochastic
Modeling follow the given steps:
• Open the Petrophysical Modeling
process. Go to the Use Existing
property and select Porosity from the
drop-down list.
• Activate the required zone by clicking
on the zone tab.
• Select Sequential Gaussian Simulation
as the method to use.
• In variogram tab, select the Variogram
type. In it select the Major
Range, Minor Range, Vertical Range and
Azimuth. Then after click on OK and
create the property model.
34. References |
Journal article, organization as author :
ESSCA Group, L'ESSCA, la Grande Ecole directement Petrel 2009 Seismic to Simulation Software,
2009.
Petrel-A Schlumberger product group, Release notes; Petrel™ Workflow Tools 2004, November
2004. .
Encyclopaedia on the Internet :
Portale Treccani. L'enciclopedia Italiana; Oil Field Characteristics and Relevant Studies [Internet]
, Italy Inc.; 2008, Available from : http://www.treccani.it/enciclopedia/oil-field-characteristics-
and-relevant-studies_(altro)/
Part of an Internet website :
West Virginia University, Department of Geology and Geography [Homepage on Internet], West
Virginia : The University; c2008, Available from : http://www.geo.wvu.edu/~wilson/casi/
Editor's Notes
Vertical discretization should be fine enough for accurate accounting of gas percolation and migration and/or gravity over-ride or under-ride. It is usually a trial-and-error process to find the appropriate grid block sizes. and they may be dependent on operating conditions of wells in the simulation.
The 1st step in the workflow involves the reduction of noise in your seismic data and the creation of anedge-enhancing attribute (i.e. variance, chaos, dip deviation), highlighting special discontinuities.During the 2nd step, the Ant Track cube is created. The Ant Tracking algorithm follows an analogy ofants finding the shortest path between their nest and their food source by communicating usingpheromones, a chemical substance that attracts other ants. The shortest path will be marked with morepheromones than the longest path and so the next ant is more likely to choose the shortest route, and soon.The idea is to distribute a large number of these electronic "ants" in a seismic volume; and let each antmove along what appears to be a fault surface while emitting "pheromone." Ants deployed along a faultshould be able to trace the fault surface for some distance before being terminated. Surfaces meetingexpectations will be strongly marked by "pheromone." Surfaces unlikely to be faults will be unmarked orweakly marked. The Ant Tracking algorithm creates a new fault attribute highlighting the correspondingfault-surface features having orientations within some pre-determined settings. The algorithm thenautomatically extracts the result as a set of fault-patches, a highly detailed mapping of discontinuities.Manual interaction is provided in the 3rd step. The extracted fault patches must be evaluated, editedand filtered in order to obtain the final interpretation.This is done using an innovative approach applyingan interactive stereo-net and histogram filter tool.In the final step, the fault patches are used for further seismic interpretation or as input to the faultmodeling directly.
Let us see how can we do correlation with the help of petrel. Using flexible 2D visualization module available in petrel we can simultaneously view the log files of different adjacent wells side by side
SEDIMENTOLOGICAL MODEL: Also known as depositional model. It describes the type of depositional environment of the sediments (fluvial, deltaic, marine, etc.)CLASSIFICATION OF FACIES: Facies can be classified by setting the cut-off values in the log. i.e. simple sands-clays classification may be realizedby identifying a cut-off value in the gamma ray log. Once they are classified, they are compared with the available core data. In these way the accuracy of the characterization is maximized.3-DDISTRIBUTION OF FACIES: The 3-dimensional distribution of facies is usually obtained by applying stochastic algorithms.These algorithm when applied will help you to create the realistic model(fig. given on next slide).Thesemodel has a large #of cells (of order of millions), later on upon simplification and by reducing the #of cells these it would behave as the input for the dynamic model to simulate the production behavior of the reservoir.
Moving avg: a set of data is divided into several subsets and their mean avg value is computed. Then after again the mean avg value of new subset (preceding) is found out and so on. This is usually done to filter out noise, remove fluctuations to make it smooth.
