Sedimentological facies models versus digital reservoir models'

1
Sedimentological facies modelsversusdigital
reservoir models.

• How do they relate?

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Digital reservoir models - main components

• Structural/
• framework
• model
• Seismic surfaces
• Faults
• Isochores
• Zone tops

• Property Model
• Facies model
• Petrophysical model
• - Porosity
• - Permeability
• - Saturations
• Fault seal model

3D modelling grid
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Role of geological interpretations andconceptual
models
Critical role through entire modelling
process Zonation Building of modelling
grid Choice of facies modelling
techniques Input parameters to facies
modelling . . .
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Reservoir zonation for 3D modelling
General rule is that zonation should follow time
lines. Lithostratigraphic zonations are often
OK for volumetric calculations. BUT are often
unsuitable for building flow simulation models.
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3D modelling grid - Internal geometries
Several slides about grid geometries
Proportional gridding
Constant no. of cells
Top conformable gridding
Base conformable gridding
Constant cell thickness
Constant cell thickness
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Mixed gridding geometry
Proportional gridding
Intermediate gridding geometry
Intermediate gridding geometry. Some proportional
gridding Some basal truncation. Achieved by
using additional control surfaces
Top conformable gridding
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Multiple zone grids
Modelling grids generally comprise several
geological zones. Different vertical grid
geometries in each zone. Identical lateral
resolutions
Z3 - proportional
Z2 - Top Conform
Z3 - Base Conform
Erosional surface between Z2 and Z3
Conformable surface between Z1 and Z2
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Grid resolution
The grid resolution should be partly dependent
on typical heterogeneity dimensions.
Highly anisotropic grids are typical dx, dy
100 m range (25 m to 500 m) dz 1 m range (25
cm to 10 m) Important to capture geometry of
thin continuous heterogeneities Focus on
barriers and thief zones Typical models are
described by 1- 5 million of grid cells. Small
models are described lt 1 million of grid
cells. Large models are described gt 10 million of
grid cells.
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Building the 3D modelling grid
- sand-rich fan systems
Isochore shale-bounded sand-rich fan.
Shale bounded sand-rich fan system. Thinning
from North to South
A
Q1 - How should the modelling grid be built? Q2 -
What is the shale geometry towards the planned
injector?
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Grid geometries - sand-rich fan
Several slides about grid geometries
Proportional grid
Good shale and sand continuity
Top conformable grid
Shales clinoform down Restricted lateral sand
continuity
Mixed grid - proportional with control surface
Intermediate shale and sand continuity
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Building the 3D modelling grid - channel
reservoirs
Complex incised channel system with thinning on
flanks
Shales observed in discovery well
Q1 - How should the modelling grid be built? Q2 -
What is the shale geometry towards the planned
injector?
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Grid geometries - turbidite channels
Sweep in top of channel
Top conformable grid
No pressure support in base
Good lateral communication
Proportional grid
Good lateral communication
Mixed grid - proportional with control surface
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Approaches for property modelling in 3D grid
1) Direct modelling of petrophysics 2) Build
facies model first and constrain petrophysics to
facies model.
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Direct modelling of petrophysics
1) Interpolation - Distance weighting
techniques - Geostatistical techniques
(kriging) - gt produce smooth models - gt OK for
volumetrics - gt NOT OK for flow simulation - gt
lack of geological realism 2) Geostatistical
simulation - gt produce more heterogeneous models
- gt better for flow simulation but still
lack realistic geometries - gt can be used in
uncertainty analysis - gt can be directly
constained to seismic data AI - poro
scatterplots
Porosity Models
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Facies modelling approaches

• 1) Facies and body definition from seismic
• 2) Manual digitising of facies
• 3) Geostatistical/Stochastic techniques
• 4) Process based mathematical models

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Body definition from seismic
Turbidite channel system. Direct definition of
abandonment phase
Interpreted abandonment phase
Location in channel system
Channel segments
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Manual digitising/painting of facies distribution

• Geologically intuitive
• Realistic models
• Input to simulators for
• quick appraisal studies
• Can only account for a few
• (large-scale) heterogeneities

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Geostatistical/stochastic techniques

• Strengths
• Quick generation of
• heterogeneous reservoir models
• Generates realistic models
• Reproducible
• Framework for data integration
• geology, wells, seismic, production
• Quantify uncertainty

• Weaknesses
• Techniques are not always realistic enough
• Cannot capture all geological rules
• Tools not user friendly enough

Cross-section through sand-rich fan
Lobes
Channels
Interlobe shales
Fan pinch-out
Intralobe shales
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Facies modelling hierarchy
Hierarchical (nested) modelling is common. Should
follow the sedimentological hierarchy.
Distal pinchout of fan
1) Facies associations
Upper fan
Distal mudstones
Mid and lower fan
2) Lobe distribution
Lobes
Interlobe shales
3) Facies distribution
Channels within upper fan
Intralobe shales
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Facies models Stochastic models
Use equations and statistics to describe
geometries Challenge is to find the appropriate
equations and statistics Has been a tendency to
try to make the geology pass in with the
mathematics BUT Basis for an appropriate
stochastic model should be a well defined
conceptual geological model.
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Formulation of a model for linear shorefaces
Model truncated Gaussian function with linear
expectation trend

• Mathematical formulation
• Truncated Gaussian field
• Linear spatial trend in expectation func.
• Variogram of underlying Gaussian field

• Key geometric characteristics
• Systematic ordering of facies belts
• Progrades and aggrades
• Interfingering between belts

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Formulation of parameter input
Progradation and aggradation is described in
terms of a Linear trend in the expectation
function a bx cy dz (also uncertainty
in a, b, c d)
Problem -gt Geologists dont think in terms of as
bs etc

• The parameter input can be reformulated as
  geologically meaningful angles
• Progradation angle - j
• Aggradation angle - q

a0, bsinqsinj csinqcosj dcosj
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Shoreline morphology
A variety of shoreline morphologies can be
generated by using more complex trend functions
Elongate
Lobate
Linear
Mixed waves and rivers
Wave dominated
River dominated

• Similar methods have been applied to turbidite
  reservoirs for modelling
• Distal fan pinchouts
• Lateral channel/levee relationships

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Object-type stochastic models
Turbidite channel

• Object-type stochastic models describe bodies
  with
• a variety of geometries.
• Standard input to object models
• Shape
• Volume fractions
• Spatial distibution
• Dimensions
• Orientation
• Extra input
• Trends
• Body correlations
• Seismic data
• Stochastic models are
• highly constrained by deterministic input

Lobe
Arcuate bar
Body thickness colour coded
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Trend definition - fan geometry
Lateral trend in channel distribution
Net sand parameter
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Trend definition - slope channel
Lateral and vertical sand distribution
trends within channel system
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Body correlations
Barrier distribution in 9 adjacent wells
Barriers green
RHOB (left) and GR (right)logs
Barrier correlation
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Constraining to body correlations
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Barrier geometry in 3D
Barrier is observed in 7 of 9 adjacent wells
Simulated barrier
Correlations set-up
Barrier thickness colour coded
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Petrophysics

• Petrophysical models are typically constrained to
  the facies distribution
• Input parameters
• - Histograms
• - Trends
• - Variograms
• for each facies
• for each parameter
• (poro, permh, permv)
• for each zone.

• Large-scale trends are particularly
• important
• Depositional trends
• Diagenetic trends

Slice through porosity realisation
High porosities red Low porosities blue
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Role of geology/geologist in 3D reservoir
modelling

• Zonation
• Time lines
• Major (continuous heterogneities)
• Building of modelling grid
• Correct internal geometries should be
• conformable with time lines
• Choice of facies modelling
• techniques

• Input parameters to facies modelling
• Dimensions/orientation etc
• Integration with other disciplines
• Geophysics
• Reservoir technology
• QC

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Some important challenges

• Optimal use of seismic data
• Direct body extraction
• Modelling of thin continuous shales
• Often difficult to capture in reservoir
  simulator
• Conceptual models and internal architecture of
  slope channel systems
• Flexible modelling of compensational features