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IPTC-18306-MS
3D and 4D Seismic Data Integration for Geomodel Infilling: A Deep Offshore Turbiditic Field Case Study.
V. Silva, T. Cadoret, L.Bergamo, and R.Brahmantio, TOTAL E&P France
Copyright 2015, International Petroleum Technology Conference This paper was prepared for presentation at the International Petroleum Technology Conference held in Doha, Qatar, 7-9 December 2015. This paper was selected for presentation by an IPTC Programme Committee following review of information contained in an abstract submitted by the author(s). Contents of the paper, as presented, have not been reviewed by the International Petroleum Technology Conference and are subject to correction by the author(s). The material, as presented, does not necessarily reflect any position of the International Petroleum Technology Conference, its officers, or members. Papers presented at IPTC are subject to publication review by Sponsor Society Committees of IPTC. Electronic reproduction, distribution, or storage of any part of this paper for commercial purposes without the written consent of the International Petroleum Technology Conference is prohibited. Permission to reproduce in print is restricted to an abstract of not more than 300 words; illustrations may not be copied. The abstract must contain conspicuous acknowledgment of where and by whom the paper was presented. Write Librarian, IPTC, P.O. Box 833836, Richardson, TX 75083-3836, U.S.A., fax +1-972-952-9435
Abstract
When seismic data is of good quality and that it can be related to useful geological properties it can become a
useful driver to distribute spatial heterogeneity within the geomodel. This paper describes a workflow to
incorporate efficiently seismic data during the geomodel infilling process. We propose to combine the seismic
facies probability attribute (obtained after 3D pre-stack inversion) with 4D attributes. This is done by increasing
the seismic facies probability where 4D information highlights the presence of permeable reservoir facies.
Afterward the obtained attribute is combined with well information using Total in-house workflow to generate
the final facies proportion cubes. Finally, Associated Facies (AF) simulation is performed using SIS (Sequence
Indicator Simulation) algorithms. Comparison is performed between the AF obtained using 3D seismic data
only and AF obtained using combined 3D and 4D seismic data.
The integration of 4D information early in the geomodeling workflow (i.e. in facies modelling stage) improves
the efficiency of the dynamic back-loop by allowing an early combination of Static and dynamic information.
Thanks to this, history matching of dynamic reservoir simulation is facilitated.
Introduction
While defining a geological model, different pieces of information must be integrated to obtain a reliable spatial
organization of geological facies and petrophysical properties. In the field case presented below, a new reservoir
model is designed to improve the representation of geological facies heterogeneities for a turbiditic deep
offshore field.
Total in-house Seismic Reservoir Characterization tool (CARESS) enables conversion of inverted seismic
attributes (such as acoustic impedance and poisson’s ratio) into attributes describing the probability of
occurrence of selected geological facies. It must be pointed out that these attributes have the same resolution as
seismic and can possibly be influenced by pore fluid content.
In the field considered for this study 4D seismic data has proven to be a key piece of information to understand
the dynamic behaviour of the reservoirs. The main 4D attribute used in this study is the fractional P-wave
velocity changes between two different seismic monitors (DV/V). If no subsidence effect occurs in the reservoir
interval, it is assumed that strong DV/V response corresponds to some production or injection related effect
which can only occur in the presence of permeable sand.
IPTC-18306-MS 2
Until now, 4D seismic data was integrated in geomodel workflow following facies simulation to assign
deterministically reservoir facies in zones where strong 4D response is visible.
In this work we propose to combine the seismic facies probability attributes and 4D attribute (DV/V) earlier on
in the infilling process to better constrain the facies property infilling in the model.
Seismic data QC and seismic quality map definition
Before the use of the seismic data to constraint the geomodel infilling, the quality of the different seismic data
were assessed to estimate the relative confidence we can have on it. The computations are performed at
reservoir interval and the final product of this analysis is the seismic quality map.
The seismic stacks used for seismic inversion derives from the Broadband survey. Computation of several
attributes was performed for these stacks as RMS amplitudes, signal to noise analysis, standard AVO QC maps
between near and far stacks after common bandwidth filtering. The stretch between near and far stacks was
performed on raw data, without common bandwidth filtering.
Seismic inversion products are the input for the Caress study, so its qualities have a direct impact on the
potential seismic constraint. Over the reservoir interval the residuals amplitude are as expected weak and
without lateral or vertical organization. In order to analyze in more detail its distribution the residuals are
normalized with respect to the amplitude of the input sub-stacks. This is performed by dividing the RMS of the
residuals calculated in the interval of interest by the RMS amplitudes of the reference seismic.
The Caress quality assessment is performed at well scale by comparing the facies found at well with the caress
prediction, section view by analyzing the continuity of the events and at base map view by analysing the
Geological coherence.
Jointly with the Caress cubes, DV/V is another source of seismic constraint for model infilling. The assessment
of its quality is performed by analyzing the residual time shift between base and monitor survey below reservoir
after warping operation using such attribute. We then look for zones showing higher time shift which would be
an indication of less reliable DV/V.
4 different attributes have been selected to analyze the seismic quality. Figure 1 presents their spatial variation
within a layer defined around the reservoir interval. To highlight zones of relatively poorer AVO behaviour the
correlation and stretch of the seismic signal between Near and Far traces have been measured. Such attributes
allows getting some hint about lateral variation in the quality of NMO correction. The correlation map exhibits
higher correlation values between sub-stacks within the channels. The stretch attribute shows globally
reasonable values except in some small localized zones. Signal to Noise ratio is another obvious criteria to
understand the seismic quality. It has been computed using the near stack. It indicates that the seismic is noisier
in the central panel area because of a highly faulted zone. It highlights also areas of poor seismic signal in the
west flank of the survey where a salt diaper induces very steep seismic reflectors. A last seismic QC taken into
account to define a quality indicator is a normalized RMS inversion residual map computed for the near sub-
stack. It allows to assess, at least partially, if the pre-stack inversion process has been successful to find an
impedance solution explaining the seismic response. This map shows higher residuals, and therefore lower
impedance reliability, in the faulted zone within the sand channels. We interpret these areas as being less
reliable in term of inversion products and therefore less able to have an important weight in the reservoir model
infilling.
In order to define a qualitative indicator reflecting the seismic quality over our interval of interest a map is
defined using some of attributes described in the previous paragraph.
For each single attribute, a quality map was defined, as can be seen in Figure 1. To obtain a single attributes
quality map a superposition of each maps is achieved to delineate zones where low reliability seismic can be
defined.
Figure 2 displays the final seismic quality map. In overall the seismic quality is high to medium, except in the
salt zone and in a small zone to the west, possibly affected by shallower faulted zone. This quality map is
afterward integrated to weight the seismic information put in the Geomodel.
IPTC-18306-MS 3
3D and 4D Seismic attributes time alignment
Prior to the combination of 3D and 4D seismic attributes, a time alignment had to be performed between dataset
to compensate for time shifts introduced by 4D effects and different seismic acquisitions and processing.
While the Caress has been computed using a broadband seismic survey acquired while the field was in
production, the 4D attribute DV/V is obtained from 3D high resolution survey referenced to the baseline time. In
order to be used together the Caress and 4D DV/V attributes have therefore to be put in the same time and
geographical referential as they have been acquired and migrated differently. In order to do so the time shift has
been computed by measuring the amount of shift necessary to maximize the correlation between the Full stack
volume coming from both dataset.
3D and 4D attributes combination and geomodel infilling
The dataset for seismic constraint definition is composed of four CARESS lithoseismic probability cubes (non
reservoir, laminated sand, massive soft sand and massive hard sand) related to each lithology occurrence. Three
4D seismic monitors (M1, M2 and M3) are also available derived from different vintages of high resolution
seismic surveys. Figure 3 illustrates a schematic workflow for 3D and 4D seismic data combination.
Most probable facies cube was computed using as input the facies probability cubes by assigning in the output
cube the facies with highest probability value. Moreover, cumulative 4D attribute is calculated by adding to M3
the response of M1 and M2 above one percent cut-off of DV/V in zones where M3 does not presents a response
above the cut-off. This step was performed to account for possible attenuation/compensation in 4D response in
M3 monitor.
Afterward, a cross validation of the most probable facies and cumulative DV/V is performed by analyzing the
zones where the 4D signal presents a clear response (DV/V above 1%) and the CARESS facies probabilities
does not correspond to a reservoir facies. This allows the definition of a Facies Analysis Cross-Validation
attribute (FAC) highlighting the incoherent zones which require some modification of the facies probabilities.
Such update is performed by increasing the initial reservoir facies probability as shown in Figure 4. This step
was performed at seismic scale and afterword upscalled into the grid to be used during the model infilling
workflow.
Final facies proportion cubes for the model were then built using an in-house workflow (Figure 5) allowing to
combine two proportion cubes per facies: a quantitative cube (or reference cube) providing the target facies
proportions (mainly guided by facies proportions at wells), and a qualitative cube guiding spatial distribution of
the facies (derived from lithoseismic probability cubes providing 3D trends per facies). A seismic quality map
derived from 3D seismic attributes QC has also been used to vary spatially the weight given to the seismic
constraint introduced as qualitative cube.
One final proportion cube is defined for each facies (5 cubes, one per AF). These cubes were then used to
distribute the facies in the model using Sequence Indicator Simulation (SIS).
AF facies were modelled stochastically (Figure 5) in the reservoir grid using the following inputs:
Well AF upscaled (1D) at wells
Facies proportion cubes
Local Varying Azimuth (LVA) property computed in channelized Architectural Elements (AE4, AE5
& AE6)
Vertical and Horizontal Variography
The result of facies modelling was used as basis for Petrophysical modelling in the reservoir grid. The
petrophysical simulations were performed using the Sequential Gaussian Simulation (SGS) algorithm. First of
all, the Effective Porosity (e) was simulated. Given the good relationship of e with Net Effective Porosity
net, Net To Gross (NTG) and Permeability (K), these parameters were co-simulated with e.
IPTC-18306-MS 4
Two model infilling using seismic constraint were performed : one using only Caress lithoseismic probability
cubes and a second one using combined Caress lithoseismic probability cubes and 4D DV/V attribute.
Results Discussion and Conclusions
Assessment of the quality of the input seismic data is a key step for an optimum integration of the seismic data
in the geomodel infilling workflow. Even though the analysis based on various seismic attributes remains
qualitative, this assessment has allowed defining a 2D seismic confidence map which was later integrated in the
compromise workflow to balance the seismic weight in the output facies proportion cubes.
The spatial distribution of the geological facies within the reservoir grid obtained with both 3D only or
integrated 3D and 4D attributes exhibits a good coherency with the geologic context. Nonetheless, the
combination of 3D attributes (CARESS) and 4D attributes (DV/V) has increased the sand content of the
geomodel in comparison to the model infilling using the CARESS attribute alone. Statistics in AF for both
models show that reservoir facies proportion within the main channel area is higher when 4D seismic data is
integrated in the infilling workflow. More importantly, this integration is improving the reservoir facies
continuity as illustrated in Figure 6.
QC was also performed on the NTG per AE. It was observed a maximum NTG error (in comparison to well
input) of 3%,. This difference was considered as acceptable having to take into account the multiple constraints
used by the simulation (e.g. Seismic, Variograms with local variation, well constraint).
3D petrophysical properties coherence were also validated by a seismic back-loop study aiming to check the
compatibility between actual inverted seismic and synthetic elastic properties (IP, PR). These synthetic
attributes are obtained thanks to a petroelastic model using as input the geological model petrophysical
properties. This exercise has allowed demonstrating that modelled P-impedance and Poisson’s Ratio are
globally less than 6% different from the inverted values. This has been considered has a sufficient level of
coherency to validate the model infilling from this point of view.
To conclude it is important to stress the benefit of this integration of 4D information early on in the geomodel
infilling workflow. Indeed, it makes the dynamic modelling more reliable by allowing an early combination of
static and dynamic information. This has improved the dynamic loop by reducing the time needed to history
match the reservoir model with production data.
Acknowledgments
The authors would like to thank TOTAL for permission to publish this paper. The authors would like also to
thank Hildebrando Vicente-Pedro for assistance in the Facies modelling workflow.
References
Sengupta S., Cadoret T., Pivot F., (2014). Semi-Automatic Facies Up-scaling Techinique for Litho-Seismic
Classification – Application to a field located in Western Offshore Africa. IPTC Paper 17444 presented at
International Petroleum Technology Conference in Doha 2014.
Hubans C., Cauquil E.C., Brechet E. (2014). 4D (time lapse) seismic: an emerging tool for underwater
monitoring. OTC paper 25225 presented at Offshore Technology Conference held in Houston 2014.
IPTC-18306-MS 5
Fig. 1: Seismic QC attributes and confidence contours. Top left - correlation between near and far sub-stack, top right - stretch between near and far sub-stack. Bottom left – mean relative inversion residual for near sub-stack,
bottom right – mean signal to noise ratio for near sub-stack.
Seismic Confidence
Low
Medium
High
MeanSignal/Noise
Near Substack
Mean Relative
Inversion Residual
Near Substack
Correlation
Near/Far
Near/Far
Stretch
IPTC-18306-MS 6
Fig. 2: Seismic Quality Map highlighting zones with low, medium and high seismic confidence.
Fig. 3: Schematic workflow for 3D and 4D seismic data combination.
Confidence
Low
Medium
High
Time Alignment to Baseline reference
Compromise workflow
Seismic Quality Map
UPDATED CARESS
CARESS (Facies Probabilities)
4D DV/V (M1, M2, M3)
3D + 4D seismic data Combination
IPTC-18306-MS 7
Fig. 4: Caress lithoseismic probability update using 4D data. Red ellipse highlights a zone where 4D anomaly is visible but no reservoir facies exists.
Fig. 5: Compromise and Facies modeling workflow. Reference proportions from well data and auxiliary proportions from seismic data. Seismic quality map used to weight the seismic information (alpha parameter).
Context / applicability of the method (2)
Objective of the proposed method: given proportion targets (the
reference cube), add to it the shapes, the spatial organization contained
in the auxiliary cube or, in other words, modify the global proportions of
the auxiliary cube in order to honor those of the reference cube
The workflow uses the second option:
10 - Références, date, lieu
Ref. cube Aux. cube
Step 1: proportions of the auxiliary
cube are modified to honor the
proportions of the reference cubeRef. cube
unchanged
Aux. Cube
modified
Step 2: Combination. In Case of VPC
or global proportions, only the
auxiliary cube is used (a=0, b=1)
Ref. cube
unchanged
Aux. Cube
modifieda x +b x
With a + b =1To keep the proportions of the reference cube
x
x
Confidence
Low
Medium
High
Context / applicability of the method (2)
Objective of the proposed method: given proportion targets (the
reference cube), add to it the shapes, the spatial organization contained
in the auxiliary cube or, in other words, modify the global proportions of
the auxiliary cube in order to honor those of the reference cube
The workflow uses the second option:
10 - Références, date, lieu
Ref. cube Aux. cube
Step 1: proportions of the auxiliary
cube are modified to honor the
proportions of the reference cubeRef. cube
unchanged
Aux. Cube
modified
Step 2: Combination. In Case of VPC
or global proportions, only the
auxiliary cube is used (a=0, b=1)
Ref. cube
unchanged
Aux. Cube
modifieda x +b x
With a + b =1To keep the proportions of the reference cube
IPTC-18306-MS 8
Fig. 6: Comparison between AF property generated using only 3D as seismic constraint and AF generated using combined 3D and 4D seismic.
AF
CARESS No 4D
AF
CARESS + 4D
AE6
AF No 4D
23.2%
16.2%17.7%
15.8%
27.1%
AE6
AF_4D30.3%
17%17.6%
12.9%
22.2%
Statistics AF without 4D
Statistics AF with 4D
Paper No. 18306
3D and 4D Seismic Data Integration for
Geomodel Infilling: A Deep Offshore Turbiditic
Field Case Study
V.A. DA SILVA*, T. CADORET, L. BERGAMO, R. BRAHMANTIO
6
1
OUTLINE Slide 2
IPTC 18306 • 3D and 4D Seismic Data Integration for Geomodel Infilling• Victoriano A. Da Silva
2
3
4
5
3D AND 4D SEISMIC DATA COMBINATION
How to integrate 3D and 4D attributes in the geomodel infilling workflow?
SEISMIC DATA QC AND CONFIDENCE MAP DEFINITION
Assessing the spatial variability of the seismic quality
CONTEXT
Motivations to perform the study
GEOMODEL INFILLING
Impact of the 4D integration in the outcome?
CONCLUSIONS
Key messages
SEISMIC BACKLOOP
Validating the petrophysical infilling
CONTEXT Slide 3
IPTC 18306 • 3D and 4D Seismic Data Integration for Geomodel Infilling• Victoriano A. Da Silva
• This study was performed in a deep offshore turbiditic field
• Study motivated by the need of an updated model integrating new data
• 4D attribute (dVp/Vp) has proven to be useful as an additional lithological indicator
• This presentation will show a workflow to integrate efficiently the seismic information in the geomodel infilling workflow
• Seismic has also been used to quality control the geomodel infilling
6
1
OUTLINE Slide 4
IPTC 18306 • 3D and 4D Seismic Data Integration for Geomodel Infilling• Victoriano A. Da Silva
2
3
4
5
3D AND 4D SEISMIC DATA COMBINATION
How to integrate 3D and 4D attributes in the geomodel infilling workflow?
SEISMIC DATA QC AND CONFIDENCE MAP DEFINITION
Assessing the spatial variability of the seismic quality
CONTEXT
Motivations to perform the study
GEOMODEL INFILLING
Impact of the 4D integration in the outcome?
CONCLUSIONS
Key messages
SEISMIC BACKLOOP
Validating the petrophysical infilling
SEISMIC DATA QC AND CONFIDENCE MAP DEFINITION Slide 5
IPTC 18306 • 3D and 4D Seismic Data Integration for Geomodel Infilling• Victoriano A. Da Silva
Seismic Quality Map
Seismic Attributes QC
Boundary compilation
Bad
Good
Bad
Good
Bad
Good
Bad
Good
6
1
OUTLINE Slide 6
IPTC 18306 • 3D and 4D Seismic Data Integration for Geomodel Infilling• Victoriano A. Da Silva
2
3
4
5
3D AND 4D SEISMIC DATA COMBINATION
How to integrate 3D and 4D attributes in the geomodel infilling workflow?
SEISMIC DATA QC AND CONFIDENCE MAP DEFINITION
Assessing the spatial variability of the seismic quality
CONTEXT
Motivations to perform the study
GEOMODEL INFILLING
Impact of the 4D integration in the outcome?
CONCLUSIONS
Key messages
SEISMIC BACKLOOP
Validating the petrophysical infilling
3D AND 4D SEISMIC DATA COMBINATION Slide 7
IPTC 18306 • 3D and 4D Seismic Data Integration for Geomodel Infilling• Victoriano A. Da Silva
Initial Most Probable
Facies 4D attribute Cumulative DV/V
Zones to be updated
Abs(DV/V)>1% & MPF=0
-3%
+3%
+1%
-1%
Most Probable
Facies Post Update
Check the Consistency
Update the inconsistent zones
LithoSeismic Facies
3D AND 4D SEISMIC DATA COMBINATION: Spatial Continuity QC Slide 8
IPTC 18306 • 3D and 4D Seismic Data Integration for Geomodel Infilling• Victoriano A. Da Silva
Most Probable Facies
before 4D Update: Most Representative in Layer
4D Signed Absolute
Maximum in Layer Most Probable Facies
after 4D Update: Most Representative in Layer
Attributes Combination
LithoSeismic Facies
3D AND 4D SEISMIC DATA COMBINATION: QC at well Slide 9
IPTC 18306 • 3D and 4D Seismic Data Integration for Geomodel Infilling• Victoriano A. Da Silva
GR AF Sand Probability
before update
Sand Probability
After update 4D DV/V B00M2
Cut off used for facies update Increased Water Sand probability
Associated
Facies (AF)
WOC
LithoSeismic Facies
6
1
OUTLINE Slide 10
IPTC 18306 • 3D and 4D Seismic Data Integration for Geomodel Infilling• Victoriano A. Da Silva
2
3
4
5
3D AND 4D SEISMIC DATA COMBINATION
How to integrate 3D and 4D attributes in the geomodel infilling workflow?
SEISMIC DATA QC AND CONFIDENCE MAP DEFINITION
Assessing the spatial variability of the seismic quality
CONTEXT
Motivations to perform the study
GEOMODEL INFILLING
Impact of the 4D integration in the outcome?
CONCLUSIONS
Key messages
SEISMIC BACKLOOP
Validating the petrophysical infilling
FACIES MODELLING WORKFLOW Slide 11
IPTC 18306 • 3D and 4D Seismic Data Integration for Geomodel Infilling• Victoriano A. Da Silva
From seismic
Litho-Cubes + 4D
Architectural Elements
AF/AE on wells
Cubes Aux
Cubes Ref
AF Target Proportions
Proportion cube from
CARESS, one cube per AF
« spatial
organisation »
Constant per AE, one
cube per GAF « target proportion »
Cubes PCProportion cube
with spatial
organisation
respecting the
target proportion,
one cube per AF
C
O
M
P
RO
M
I
S
E
Proportion of AF per AE (CARESS)
x
Confidence
Low
Medium
High
Context / applicability of the method (2)
Objective of the proposed method: given proportion targets (the
reference cube), add to it the shapes, the spatial organization contained
in the auxiliary cube or, in other words, modify the global proportions of
the auxiliary cube in order to honor those of the reference cube
The workflow uses the second option:
10 - Références, date, lieu
Ref. cube Aux. cube
Step 1: proportions of the auxiliary
cube are modified to honor the
proportions of the reference cubeRef. cube
unchanged
Aux. Cube
modified
Step 2: Combination. In Case of VPC
or global proportions, only the
auxiliary cube is used (a=0, b=1)
Ref. cube
unchanged
Aux. Cube
modifieda x +b x
With a + b =1To keep the proportions of the reference cube
x
+
Context / applicability of the method (2)
Objective of the proposed method: given proportion targets (the
reference cube), add to it the shapes, the spatial organization contained
in the auxiliary cube or, in other words, modify the global proportions of
the auxiliary cube in order to honor those of the reference cube
The workflow uses the second option:
10 - Références, date, lieu
Ref. cube Aux. cube
Step 1: proportions of the auxiliary
cube are modified to honor the
proportions of the reference cubeRef. cube
unchanged
Aux. Cube
modified
Step 2: Combination. In Case of VPC
or global proportions, only the
auxiliary cube is used (a=0, b=1)
Ref. cube
unchanged
Aux. Cube
modifieda x +b x
With a + b =1To keep the proportions of the reference cube
Context / applicability of the method (2)
Objective of the proposed method: given proportion targets (the
reference cube), add to it the shapes, the spatial organization contained
in the auxiliary cube or, in other words, modify the global proportions of
the auxiliary cube in order to honor those of the reference cube
The workflow uses the second option:
10 - Références, date, lieu
Ref. cube Aux. cube
Step 1: proportions of the auxiliary
cube are modified to honor the
proportions of the reference cubeRef. cube
unchanged
Aux. Cube
modified
Step 2: Combination. In Case of VPC
or global proportions, only the
auxiliary cube is used (a=0, b=1)
Ref. cube
unchanged
Aux. Cube
modifieda x +b x
With a + b =1To keep the proportions of the reference cube
x
x
Confidence
Low
Medium
High
Context / applicability of the method (2)
Objective of the proposed method: given proportion targets (the
reference cube), add to it the shapes, the spatial organization contained
in the auxiliary cube or, in other words, modify the global proportions of
the auxiliary cube in order to honor those of the reference cube
The workflow uses the second option:
10 - Références, date, lieu
Ref. cube Aux. cube
Step 1: proportions of the auxiliary
cube are modified to honor the
proportions of the reference cubeRef. cube
unchanged
Aux. Cube
modified
Step 2: Combination. In Case of VPC
or global proportions, only the
auxiliary cube is used (a=0, b=1)
Ref. cube
unchanged
Aux. Cube
modifieda x +b x
With a + b =1To keep the proportions of the reference cube
SISMODELLING
Final
Facies Proportion
Cubes
Geomodelling Results Slide 12
IPTC 18306 • 3D and 4D Seismic Data Integration for Geomodel Infilling• Victoriano A. Da Silva
AF
Lithocubes No 4D
AF
Lithocubes + 4D
23.2%
16.2% 17.7%
15.8%
27.1%
30.3%
17% 17.6%
12.9%
22.2%
Statistics AF without 4D In AE6
Statistics AF with 4D In AE6
Observation:
Sand proportion more in line with wells results
AF2 AF3 AF4 AF5 AF6
AF2 AF3 AF4 AF5 AF6
6
1
OUTLINE Slide 13
IPTC 18306 • 3D and 4D Seismic Data Integration for Geomodel Infilling• Victoriano A. Da Silva
2
3
4
5
3D AND 4D SEISMIC DATA COMBINATION
How to integrate 3D and 4D attributes in the geomodel infilling workflow?
SEISMIC DATA QC AND CONFIDENCE MAP DEFINITION
Assessing the spatial variability of the seismic quality
CONTEXT
Motivations to perform the study
GEOMODEL INFILLING
Impact of the 4D integration in the outcome?
CONCLUSIONS
Key messages
SEISMIC BACKLOOP
Validating the petrophysical infilling
SEISMIC BACKLOOP (SBL) WORKFLOW Slide 14
IPTC 18306 • 3D and 4D Seismic Data Integration for Geomodel Infilling• Victoriano A. Da Silva
3D Geomodel 3D Inverted cubes
Update Petrophysics
Comparison is done in
the Geomodel “space”
SEISMIC BACKLOOP AT WHOLE GRID Slide 15
IPTC 18306 • 3D and 4D Seismic Data Integration for Geomodel Infilling• Victoriano A. Da Silva
Initial mismatch analysis on the whole 3D grid
Strong Mismatch
Moderate Mismatch
Small Mismatch
Rock Physics Model Display
• Evaluate the impact of petrophysical properties (VCL, PHI, SW) on the Elastic IP-PR) attributes by color code to obtain the Summary X-plot
IP
PR
Non-Reservoirs
Vcl
0
0.6
No
n-R
eserv
oir
s
Reserv
oir
s +DIP -DIP
-DPR
+DPR DIP = RPM - INVERSION DPR= RPM - INVERSION
SUMMARY X-PLOT AND STATISTICAL ANALYSIS OF ANOMALY BODY Slide 16
IPTC 18306 • 3D and 4D Seismic Data Integration for Geomodel Infilling• Victoriano A. Da Silva
I
II
IV I
II
IV
+DIP -DIP
IP Overestimation Possible interpretations:
1. Overestimation
of SW
III
2. Underestimation of PHI
-DPR
+DPR
3. Combination of
options 1 and 2
0.5 0 PHIE
But…
1. Bodies located below WOC
(options 1 and 3 are unlikely
to happen )
2. Most likely a porosity effect
DIP = RPM - INVERSION DPR= RPM - INVERSION
0,0%2,0%4,0%6,0%8,0%
10,0%12,0%
IP Percentage Difference
SLAP_Initial
SLAP_Final
Anomaly
Threshold
High Stakes FACIES
Properties Update
• SLAP_Inial: Initial infilling
• SLAP_Final: porosity increased by 3pu
6
1
OUTLINE Slide 17
IPTC 18306 • 3D and 4D Seismic Data Integration for Geomodel Infilling• Victoriano A. Da Silva
2
3
4
5
3D AND 4D SEISMIC DATA COMBINATION
How to integrate 3D and 4D attributes in the geomodel infilling workflow?
SEISMIC DATA QC AND CONFIDENCE MAP DEFINITION
Assessing the spatial variability of the seismic quality
CONTEXT
Motivations to perform the study
GEOMODEL INFILLING
Impact of the 4D integration in the outcome?
CONCLUSIONS
Key messages
SEISMIC BACKLOOP
Validating the petrophysical infilling
CONCLUSIONS Slide 18
IPTC 18306 • 3D and 4D Seismic Data Integration for Geomodel Infilling• Victoriano A. Da Silva
• Seismic constraint allows to distribute realistic lateral heterogeneities and increases the reservoir facies continuity
• Seismic quality map permit weighting spatially the seismic constraint during model infilling
• The integration of 4D information has reduced the time needed to history match the reservoir model with production data
• Seismic Backloop shows that model in-filling allow to globally honor the inverted 3D seismic
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Slide 19