Use of SBED as a tool for permeability modelling in ... - Force

Use of SBED as a tool for permeability modelling in heterolithic
tidal reservoirs: a test study from the Njord Field
SBED meeting October 16 th 2006
Mike Young

Outline
• Introduction
- Motivation behind the study
- Use of SBED in Hydro
• Tilje Formation, Njord Field - SBED test study
- Challenge of modelling the Tilje Fm.
- Why SBED?
- Data set used in the study
- Methodology/workflow
- Results
• Summary/comments on the SBED approach

Introduction
• Motivation
- Theoretically SBED is a good concept
- Hydro has supported SBED for some time
- Test out in practice … can the tool be implemented in the BU’s ?
• Good test case: Heterolithic tidal facies of the Tilje Fm., Njord Field
- Difficult to characterize using “conventional” petrophysical/property modelling
- SBED/TBED designed to model tidal heterogeneity
• Internal use in Hydro
- Limited to a research activity
- Low priority activity
- At present, it is difficult and time consuming (expensive) to get results !
- Uncertainty in SBED is a key issue that is poorly addressed

Challenge of modelling the Tilje Fm., Njord
Thin intercalations of mudstone and
sandstone layers will have a strong influence
on the flow properties!

Why use SBED?
Core plug data: Tilje 3A Formation
Question:
Can we derive petrophysical properties from
these data (core plugs) that are representative at
the grid-cell scale of a reservoir model ?
Problems:
Kv and Kh are NOT well characterized by core
plugs or wireline data.
Permeability data measured from core plugs that
have a sample volume below the REV will be
unrepresentative.
Therefore we see extreme variability of plug
permeabilities (Kv, Kh) even inside small vertical
intervals.
Answer:
No! But using SBED to model the heterogeneity
at a more suitable volume (REV) and using flowbased
upscaling to determine properties could
be a more realistic solution…
Thin intercalations of mudstone and
sandstone layers will have a strong influence
on the flow properties!

Data set
6407/7-4 Tilje 3A
• Cored well 6407/7-4 (Njord East Flank)
- Used as a test case
- Thick Tilje 3A
- Good petrophysical data set
• Core plug & mini-perm. data
• Wireline and synthetic poro-perm data
Tilje 3A
50 m
• Tidal heterolithics (Tilje 3A)
- Vertically aggraded tidal flat deposits
- Composed of tidal bundles
- Wavy, flaser and lenticular beds

Core plug poro. – perm. data (Tilje 3A, Njord)
Large scatter in Kv and Kh !
Correlation = 0,67

SBED Methodology/Workflow used
• Generate bedding-scale sub-models/SBED templates
• Petrophysical data analysis (core plugs/mini-perm. data)
• Populate sub-models with petrophysical values
• Calibrate SBED petrophysical input values
• Moving window upscaling to generate the SBED output results

Generate SBED sub-models
6407/7- 4 Tilje 3A
• Split up core into intervals modelled with
specific SBED templates
- Different sub-models needed to capture variations in
the sand:shale ratio (NTG)
- Intervals of approx. 5% sand:shale (SBED NTG)
- i.e. 10%, 15%, 20% ….. 100% sand
• Key parameters
- Sand to shale ratio (NTG in SBED)
- Geometry, thickness variation and frequency of the
mud layers
• Mean & STD for porosity and permeability
- Values needed for each lithotype in each submodel
50 m
Model size 30x30x30 cm
26 different SBED models needed to capture variation in
sand:shale (NTG) and sedimentary architecture

Sand:shale ratio key in these tidal facies
Key modelling parameter - it will have a strong influence on vertical and horizontal permeability.
Predictable relationship between sand:shale ratio and geometry/continuity of the bedforms.
Flaser – Lenticular bedding transition
SBED submodels
95% sand
50% sand
Ca. 50m
10% sand
After Reineck & Wunderlich (1968)

Petrophysical input data
• Porosity and permeability for each of
the lithological components of the
model (i.e. ebb sand, flood sand, mud)
• Mean and STD values
2
• Variogram value
• Poro-perm correlation (e.g. 0,67)
1

Petrophysical data analysis
• We need to find permeability/porosity values for each lithotype (sand 1 & 2, mud…)
• Not an easy task …
- There is typically a biased data base sampling at the wrong volume (core plugs)
- Mini-permeameter data are better, but rarely taken as standard …
- Especially difficult to get permeability values for the mud layers
• Key steps: Filter out “biased plugs” that contain multiple lithotypes
Asses porosity and permeability distributions for the entire dataset and for subsets:
e.g. specific intervals of NTG, depth intervals …
Use these results as a starting point !
Mini-perm
Plug data
Few data points below 50%
sand:shale ratio (essentially SBED submodel divisions)

Porosity (sand)
Shapes of the distributions
sketched to highlight their nature
95-100
Mean = 0,23
STD = 0,03
0-65
Mean = 0,14
STD = 0,04
70-80
Mean = 0,18
STD = 0,04
85-90
Mean = 0,20
STD = 0,03
• Porosity distribution for the entire data set (sand layers)
- Need to make sense of this and break it down into subsets
• Porosity distribution for specific intervals of NTG (sand:shale ratios)
- Divisions based on visual inspection of the core and determination of intervals with “similar” sand type
- Based on splitting up the data set into various different intervals of NTG
- Based on this data it is possible to determine mean and STD values
- May not be simple Gaussian distributions !

Permeability (sand)
• Distributions for the NTG intervals
- Core plug data and mini-perm
- Complex distributions, commonly with at least
two sand types in each of the NTG intervals !
• Permeability distribution for the entire
data set
Shapes of the distributions
sketched to highlight their nature
• Core plug data are biased, so mini-perm
data are better at capturing values for
individual sand layers
- However, mini-perm data show bias towards
the higher perm. layers !
Shapes of the distributions
sketched to highlight their nature

Effect of varying input data (petrophysics)
• Results from upscaling of all realisations of SBED submodels for the Tilje 3A, 6407/7-4
• 5 different model versions - same geometric input, but different petrophysical input
- i.e. the variation is related almost exclusively to the petrophysics
• Key observation: The petrophysical input data have a significant impact on the results!
Variation in
Kh between
the different
models
Variation in
Kv between
the different
models

Calibration of the SBED model input
• An important step is to calibrate the petrophysical values in the models
- Key question: Have we captured the true variation in petrophysical values ?
- Answer: Almost certainly not at the first attempt !
• Need to generate ”pseudo” core plugs from the SBED models
- Extract volumes from the models that are the same as the actual core plugs
- These need to be upscaled (flow based, fixed boundary) and compared to the actual
core plug data
- Compare the porosity-permeability cross-plot
- Compare the porosity and permeability frequency distributions
Vertical plug
10 cm
10 cm
2.5 cm
Horizontal plug
2.5 cm
90% Sand model populated with permeability

• Input petrophysics should be adjusted until an acceptable match is obtained
between pseudo and real core plugs
• It is likely that several iterations of this process will be needed !
0 - 65
95 - 100
Frequency %
25,00
20,00
15,00
10,00
Core plugs
Pseudo plugs (SBED model)
Kh
Frequency %
45,00
40,00
35,00
30,00
25,00
20,00
15,00
Core plugs
Pseudo plugs (SBED model)
5,00
10,00
5,00
0,00
0,01 0,03 0,05 0,07 0,09 0,11 0,13 0,15 0,17 0,19 0,21 0,23 0,25 0,27 0,29
Porosity Bins
0,00
0,01 0,03 0,05 0,07 0,09 0,11 0,13 0,15 0,17 0,19 0,21 0,23 0,25 0,27 0,29
Porosity Bins
70-80
85-90
30
25
Core plugs
Pseudo plugs (SBED model)
35
30
Core plugs
Pseudo plugs (SBED model)
Frequency %
20
15
10
Frequency %
25
20
15
10
5
5
0
0,01 0,03 0,05 0,07 0,09 0,11 0,13 0,15 0,17 0,19 0,21 0,23 0,25 0,27 0,29
Porosity Bins
0
0,01 0,03 0,05 0,07 0,09 0,11 0,13 0,15 0,17 0,19 0,21 0,23 0,25 0,27 0,29
Porosity Bins
SBED pseudo plugs and the actual plugs have the same sample
volume. We could expect a similar scatter in both data sets !

Results
• Several different options here …
• Chosen to build a “stacked model” for the
cored interval – i.e. a direct representation of
the core
• Moving window upscaling enables upscaled
results at a log scale (e.g. every 12.5 cm) for
Kh, Kv, Porosity
• Upscaling method is dynamic (flow-based)
method with fixed boundary conditions
• Why log scale ?
- Consistent with wireline data (same scale)
- Can be used together with wireline data to predict
properties (esp. Kh, Kv) in non-cored wells
• The software “Facimage” was used to
generate ”electrofacies” and predict
permeability in non-cored wells/intervals
SBED results used as “training” data

Using clustering and nearest neighbour index (NNI) the “electrofacies” and SBED-permeability (defined for cored
intervals) can be propagated to non-cored well intervals. Using the input from SBED this is a more geologically
based and accurate method for predicting permeability and defining “flow facies” that will be taken into RMS.

Summary
• In tidal heterolithic facies (e.g. Tilje Fm.) it is difficult to determine
representative permeability values using conventional core plugs
• SBED method was used to generate log-scale permeability based on
process based modeling of small-scale geology (bedding scale)
• Moving window upscalling enabled Kh and Kv values to be generated at
the log scale (ca. 12,5 cm), consistent with other wireline data
• Kh and Kv logs from SBED can be used as “training” data for
permeability and facies prediction in non-cored wells
- E.g. Using the NNI method in Paradigm Facimage
• SBED/Facimage can provide a more realistic (Kh and Kv) and consistent
data input to the geo-model (RMS)
- All input data with a similar sample volume
- Bedding scale, but not necessarily representative at the grid block !
- Additional modelling and upscaling step may be necessary

Comments on the use of SBED
• Calibrating the input data is an important/critical step
- Otherwise it is difficult to determine whether the results can be trusted
- Potentially a large range in uncertainty
- SBED could be equally as uncertain as conventional plug-based methods
- Manual and very time consuming, but critical step in the workflow !!
• SBED projects are labour intensive and thus expensive
- Possibly hundreds of man hours for a relatively small project !
- Especially with the manual calibration technique
• SBED is a specialist tool and still somewhat immature
- Not recommended for wider use in Hydro BU’s yet !