GEOFISIKA ( 18 Files )

SEMINAR NASIONAL JURUSAN FISIKA FMIPA UM 2016

Brent Sandstone Reservoir Porosity Mapping using Acoustic
Impedance Inversion and Geostatistical Method Sequential
Gaussian Simulation in FS Field
MUHAMMAD FAHMI1), ABDUL HARIS2,*), TAKESHI KOZAWA2)
1) Post

Graduate Master of Reservoir Geophysics Program, Department of Physics, Mathematics
and Science Faculty, University of Indonesia, Depok, West Java
E-mail: muh.fahmi14@gmail.com

Department of Physics, Mathematics and Science Faculty, University of Indonesia, Depok, West
Java
E-mail: aharis@sci.ui.ac.id
2) JGI,

Inc.

E-mail: takeshi.kozawa@jgi.co.id
*) CORRESPONDING AUTHOR

TEL: 085691896671
ABSTRACT: FS Field which is geologically located in northern part of North Sea Basin had a
complex structure. It can lead to uncertainty in mapping of Brent group sandstone reservoir.
Brent group sandstone reservoir consist of 5 main formation, Tarbert, Ness, Etive, Rannoch and
Broom which is known as deltaic reservoir. This study conducted to evaluate porosity distribution
map of Brent reservoir based on acoustic impedance inversion result and geostatistical method
sequential gaussian simulation using 3D seismic PSTM, 4 wells complete with well log, geological
marker and well report data. The results show the porosity map distribution of Brent reservoir
using acoustic impedance inversion results had a comprehensive distribution than using
geostatistical method sequential gaussian simulation.
Keyword

: Acoustic Impedance
Distribution Maps.

Inversion,

Sequential

Gaussian

Simulation,

Porosity

INTRODUCTION
FS Field which is geologically located in northern part of North Sea Basin had
many oil and gas field in rifting system of North Sea Basin. Regional geology of FS field
had a complex geological structure which is consist of many major fault north-south
trend causing formation of graben structure in FS field.
Seismic interpretation process is expected to be accurately find out subsurface
condition in order to oil and gas field development. Inversion seismic using acoustic
impedance parameter is one of geophysical method that can show rock density layer
formation, (Lindseth, 1982). Acoustic impedance value is influenced by wave velocity
value in rocks that have certain trends towards other influence parameter such as
porosity.
Reservoir modelling aims is to mapping rock porosity of Brent sandstone reservoir
in FS field using approach results acoustic impedance inversion result and
geostatistical method sequential gaussian simulation (SGS). It is expected to minimize
error that occurred in Brent sandstone reservoir mapping process.

RESEARCH METHODOLOGY
This research is based on a combination of several studies, including seismic,
geological, petrophysical and geostatistical studies. The reservoir model is based on 3D
seismic data and well log data which is able to explain the porosity distribution and
geometry of geological structure model in FS field.

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Research area located in FS field, North Sea Basin (Figure 1.)

Figure 1. Research area in FS field location map, North Sea Basin
is shown by the red box (Fraser et al.,2002)

Here is the data used in this research :
1. Seismic Data
Table 1. 3D Seismic Data Specification
No.

1.
2.
3.
4.
5.
6.

Specification Seismic Data
Total Inline
2845
Total Xline
2145
Bin Size
25 x 25 m
Record Length
6000 msec
Sampling Interval
4 msec
Coordinate System
Zone 31 N UTM

2. Well Data
In this research had 4 well consist of well S-1, R-1, D-2 and A-3. Well log
data availability shown in Table.2.
Table 2. Well Data Avalaibality
No.
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.

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Data

Gamma Ray Log
Resistivity Log
Density Log
Neutron Porosity Log
Sonic Log
Caliper Log
Well Report
Composite Log
Checkshot
Geological Marker
Remarks

S-1
V
V

R-1
D-2
A-3
V

V
V
V
V
V
V
V
V
V
V
V
V
V
V
V
V
V
V
V
V

V
V
V
V
V
V
V
Not available
Available

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SEMINAR NASIONAL JURUSAN FISIKA FMIPA UM 2016
Flowchart in this research shown in Figure 2. :

Figure 2. Brent reservoir porosity distribution mapping flowchart.

1. Well Correlation
In this stages, for well R-1, D-2 and A-3 that had well log and geological
marker data will used for well correlation analysis. This is focused

correlation on depositional environment process, time depositional, lithology
and thickness of every main formation of Brent reservoir.
2. Seismic Well Tie
In this stages, seismic data in time domain will tie with well data in depth
domain. Wavelet and checkshot data used for this seismic well tie analysis.
There are 3 wavelet that tested in this stages, ricker wavelet with specify
dominant frequency, statistical wavelet extract from seismic data near well
data and use well wavelet. The best correlation wavelet in this research is
using statistical wavelet extract from seismic data near well R-1. Window
correlation of seismic well tie analysis focusing on main formation of Brent
reservoir and got the best well seismic tie correlation value is 0,8.
3. Well Logging Analysis
Well log data analysis conducted to determine zona interest of Brent
sandstone reservoir. Gamma ray log can help to determined for sand or shale
lithology, in this research using sand base line 35 API and shale base line is
90 API. Crossover between density and neutron porosity log can help to
determined specified zona interest of Brent sandstone reservoir that include
any hydrocarbon. Resistivity log can help to determined for hydrocarbon
content, oil, gas or water, low resistivity more likely include water zone.
4. Petrophysics Evaluation

After well log analysis, petrophysical evaluation is needed to calculate and
evaluate property of Brent sandstone reservoir such as Vshale content, water
saturation, total porosity and effective porosity.

5. Seismic Interpretation

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The result of seismic well tie analysis is important for seismic interpretation
process. In this stage, picking horizon and fault in FS field using 3D seismic
data. There are 3 main horizon consist of top brent, mid brent, base brent
and 4 major fault north-south trending that picked in this process.
6. Structural Modeling
Horizon and fault picking result used in structural modeling process. The
result of this stages is horizon model, fault model, time structure map and
structural model.
7. Seismic Inversion

Seismic inversion analysis is this research using acoustic impedance model
based method. Input of this process is horizon model, wavelet and well log
data from previous stage. This inversion process using iteration 20 times
with constrained value from model inversion is 25 % and gate window from
1500 4500 msec. From acoustic impedance value can convert to porosity
value using relation between acoustic impendace and porosity with trend
formula. Porosity value is inversely from acoustic impedance value.
8. Sequential Gaussian Simulation
Input of this process is porosity property from petrophysical evaluation in
previous stage. The porosity value from every well data scaled up and
distributed with sequential gaussian simulation method. Porosity mapped
distribution is output of this process.
9. Porosity Distribution Maps
Porosity distribution maps obtained from two methods, approach of acoustic
impedance inversion result and sequential gaussian simulation method. This
two porosity distribution maps analyzed and evaluated to got minimum error
for porosity property modeling maps.
RESULT AND DISCUSSION
Acoustic Impedance Maps
On the horizon top Brent, mid Brent and base Brent extraction of acoustic
impedance (AI) result using model based with window gate 50 msec above horizon and
50 msec below horizon. From the petrophysical evaluation result top Brent had a low to
medium AI sand with range AI value is from 6.500 9.000 (gr/cc)*(m/s) and from AI
maps distribution with varying thickness variation (Figure 3.).

Figure 3. Brent reservoir AI maps for horizon top Brent, mid Brent and base Brent.

From south to west area in FS field had a thick sandstone reservoir and become
thinning to the north and east of research area in FS field. This difference of sandstone

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thickness caused of many major fault north-south trending. Regarding this AI maps,
Brent reservoir in FS field had a channel deltaic feature.
Porosity Maps from AI Maps
Acoustic impedance and porosity had a inverse relationship. Regarding AI value
result and relationship formula between AI and porosity, porosity maps obtained from
AI value that convert to porosity value using relationship formula :
Effective Porosity = -2,831 x 10-5 x AI + 0,367431

(1)

Porosity maps (Figure 4.) from AI maps on horizon top Brent, mid Brent and base
Brent had a similar feature condition like AI maps. It is because porosity maps obtained
from AI maps. The southern to western area of FS field had low AI value, so that the
porosity value in porosity maps from AI maps had a high value and for northern part to
eastern part area of FS field had a high AI value and porosity value in porosity maps
from AI maps had a low value. The distribution of AI and porosity value is one of the
consideration for development oil and gas field.

Figure 4. Brent reservoir Effective Porosity maps from AI maps for horizon top Brent,
mid Brent and base Brent.

Comparison Porosity Maps from AI maps and SGS maps
Porosity distribution maps in this research obtained from two method, from acoustic
impedance inversion result and from geostatistical methods sequential gaussian
simulation (SGS). Porosity distribution maps from AI maps has a similar feature with
AI maps, because in this process, porosity maps is a result of conversion from AI value
from inversion result to porosity value using relationship formula between AI and
porosity. Whereas, porosity maps from geostatistical method SGS obtained from
petrophysical evaluation results, scaled up log and then distribute with SGS
distribution methods. Porosity maps from AI maps (Figure 4.) in this research had a
better result on distribution all of area than porosity maps from SGS maps (Figure 5.).
It is because porosity maps from AI maps use 3D seismic data when running inversion
process and for SGS just using 3 well that didn t cover all of area. It caused porosity
distribution from SGS maps had minimum error in near well area range but had a
maximum error in far well area range.

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. Figure 5. Brent reservoir Effective Porosity maps from SGS maps for horizon top

Brent, mid Brent and base Brent.

CONCLUSION
1.
FS Field complex structure consist of 4 mayor faults north-south trend and formed
graben structure
2. Brent sandstone reservoir had acoustic impedance value between 6.500
8.500
(gr/cc)*(m/s)).
3. Porosity maps which is constrained by acoustic impedance result had more
comprehensive distribution compared to porosity maps from geostatistical methods
sequential gaussian simulation.
4. Porosity maps distribution from geostatistical methods sequential gaussian
simulation need more well data to get better porosity distribution.
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