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8102019 Ipa11-G-033 Reservoir Quality and Porosity Prediction in Carbonate Case Study Singa Field South Sumatra Basin
httpslidepdfcomreaderfullipa11-g-033-reservoir-quality-and-porosity-prediction-in-carbonate-case-study 18
IPA11-G-033
PROCEEDING INDONESIAN PETROLEUM ASSOCIATION
Thirty Five Annual Convention amp Exhibition May 2011
RESERVOIR QUALITY AND POROSITY PREDICTION IN CARBONATE
USING SEISMIC INVERSION AND ATTRIBUTES
CASE STUDY SINGA FIELD SOUTH SUMATRA BASIN
Y Yanto
T Iswachyono
M Arief MMZ
J J Wood
ABSTRACT
Singa field has proven gas from carbonates of the
Lower Miocene Baturaja Formation The field is
over 9 km long and 25 km wide and is located in
Lematang Block the central part of the Lematang
Deep between the southern trend of Pendopo
anticlinorium and Muara Enim anticlinorium One
exploration well and one delineation well have
already been drilled and the plan is to drill 2
horizontal development wells The field has a
maximum gas reservoir thickness of 282 feet and
contains an average of 30 CO2 and 110 ppm H2S
Significant porosity (gt 15) has been observed inthe upper part of the Baturaja Formation (BRF) 282
feet thick in the S1 well and 125 feet thick in the S2
well Dominant porosity in thin sections is mouldic
and micro vuggy with some fractures The lower
BRF is carbonate mudstone to wackstone with
minor porosity (~8) interpreted as a platform
carbonate The upper BRF is limestone with
skeletal wackstone and packstone containing algal-
foram-mollusc and a coral-algal-foram-mollusc
intraclast floatstone interpreted as lagoonal and
back reef facies
There are two concerns regarding this deep
carbonate field reservoir quality and porosity
distribution Because of the high CO2 and H2S
content within the gas target the reservoir has to be
large enough to be developed economically Seismic
inversion and attributes techniques are applied to
characterize the reservoir and to quantify reservoir
distribution The objective is to predict reservoir
quality and porosity distribution in order to generate
an updated geological model for reservoir modelling
and to optimize new well locations
PT Medco EampP Indonesia
Cross-plotting acoustic impedance (AI) vs porosity
from well logs shows that the gas and brine values
are populated in separate trends with a good
relationship (minimal scatter) This suggests that
porosity can be estimated from AI by a transform
equation Integrated with the AI method seismic
amplitude-envelope (AE) attribute is used to aid
facies interpretation and to identify the carbonate
depositional setting Integration of AI and AE is
useful for predicting reservoir quality and porosity
distribution in this field As a result of using updated
reservoir modelling based on the seismic inversion
and seismic attribute results the field development
plan can be revised to include the drilling of two
development wells
INTRODUCTION
The Singa field is covered by 13 x 45 km 3D
seismic survey of good quality Seismic shows the
carbonate build-up which is illustrated by ldquoon-laprdquo
to the reservoir carbonate The field is a north-south
trending structure with steeply-dipping flanks
containing the hydrocarbon-bearing carbonate
limestone reservoir The field has proven gas from
carbonates of the Baturaja Formation (BRF)
The reservoir in the Singa field is a large reefal
buildup of the BRF The reef forms a large 4-way
dip closure at the top of the BRF The reef is
developed over an earlier-formed high in the centre
of the basin The vertical relief has a maximum
thickness of 900 feet Regionally the carbonate
limestone is calcareous shale which forms a basin-
wide mappable seismic reflector However where
deposition took place over a basement high the
shallower water and high-energy conditions allowed
the growth of corals and calcareous algae forming aseries of coral reefs in the Singa area The carbonate
reservoir appears to be a reefal build-up with
8102019 Ipa11-G-033 Reservoir Quality and Porosity Prediction in Carbonate Case Study Singa Field South Sumatra Basin
httpslidepdfcomreaderfullipa11-g-033-reservoir-quality-and-porosity-prediction-in-carbonate-case-study 28
porosity development in the upper part of the
carbonate
REGIONAL GEOLOGY
Singa field is located in Lematang Block South
Sumatra Basin approximately 30 km west of the
city of Prabumulih (Figure 1) Based on its present
day relative position to the subduction zone it is
categorized as a back-arc basin filled by Tertiary
sediments The South Sumatra Basin can be divided
into three different sub-basins namely the Jambi
Depression Central Palembang Deep and Lematang
Deep Singa field is located within Lematang Deep
(Figure 2)
Structural systems for the South Sumatra Basin
resulted from at least three tectonic styles ie thePre-Tertiary basement inheritance structure the
Eocene-Oligocene rifting mechanism and the most
recently the PliocenendashPleistocene compressional
regime (Figure 2) Lematang Deep is bounded by
the Lematang Fault to the north Beyond the fault is
the Limau Anticlinorium The Musi Platform is the
boundary to the west while the Kuang Platform is
the boundary to the east The Southern boundary for
the Lematang Deep is marked by the Garba
Mountain Lematang Deep itself consists of a series
of horsts and grabens as a product of Eocene-
Oligocene tectonics
Stratigraphy of the South Sumatra Basin began in
the Eocene epoch marked by the deposition of
volcanic rich material pre-rift sediments (Kamal and
Argakoesoemah 2005) (Figure 3) When the rifting
took place syn-rift sediments of the Lemat Fm
were deposited The Lemat Fm is proximal facies
alluvial fan and fan delta facies for the coarser grain
and lacustrine and marine shale for the finer grain
Subsequently the Lower and Upper Talangakar Fm
was deposited This Talangakar group is fluvio-
deltaic facies sediment In Miocene time the rate ofsubsidence decreased and contemporaneously a
global sea level rise took place known as the
Miocene transgression This transgression allowed
most of the paleo-high (horst) to become submerged
below sea level Where the environment was
suitable a carbonate factory formed and Baturaja
Fm was deposited Elsewhere the Telisa Fm was
deposited Singa field reservoir is a carbonate build-
up that formed during this process The relationship
between Telisa Fm and BRF in some places is
interfingering and as the transgression reached its
maximum the accommodation space for carbonate
increased beyond the carbonate factory productivity
As a result most of the carbonate factory failed to
keep up and no significant carbonate build-up
occurred post the Miocene Transgression maxima
In this phase only the Telisa Fm marine shale was
deposited Regression followed the transgression
and the uplift of Barisan Mountain range in the
south west of South Sumatra Basin provided a new
sediment provenance from which the Palembang
Group is the product This group consists of the
Lower Palembang Formation with transitional
sediment facies The Middle Palembang Fm has a
distinctive coal-bearing section and the Upper
Palembang is marked by its volcanic material
content During the Plio-Pleistocene tectonics some
of the formation was uplifted and eroded notably in
the Limau anticlinorium A series of Quaternary
volcanic activities in South Sumatra produced
volcanic material that was deposited over areas in
the South Sumatra Basin
Singa field is interpreted as an isolated carbonate
platform Palaeo-wind direction directly influences
the distribution of high energy wave agitated
carbonate facies within carbonate platforms The
windward side of the carbonate platform usually has
a steeper slope than compared with the leeward side
Carbonate texture in the windward margin is less
muddy The texture can range from packestone to
boundstone providing good initial porosity whilst
the leeward side usually consists of mudstone to
wackestone facies with fair to poor initial porosityThe windward side of the Singa field is interpreted
as the west side while the leeward is the east side of
Singa field
METHODOLOGY
For this study we used two wells and post-stack time
migrated 3D seismic which has relative preserved
amplitudes with low vertical seismic resolution and
15 Hz dominant frequency at the level of the BRF
This is due to the deep carbonate target at 12000 ft
subsurface An average velocity in the BRF of11155 ftsec yields a vertical seismic resolution of
approximately 186 feet equivalent to 26
milliseconds TWT in seismic data
The accuracy of the horizon interpretation of the
carbonate is crucial for seismic inversion analysis
Picking the top BRF and internal reflection
character of the carbonate in conventional
reflectivity data is difficult because of the chaotic
and dimming seismic amplitude effects related to
the low impedance of high porosity facies changes
and gas-bearing in carbonates To overcome this
problem a high frequency enhancement technique
(Young and Wild 2004) relative impedance
8102019 Ipa11-G-033 Reservoir Quality and Porosity Prediction in Carbonate Case Study Singa Field South Sumatra Basin
httpslidepdfcomreaderfullipa11-g-033-reservoir-quality-and-porosity-prediction-in-carbonate-case-study 38
8102019 Ipa11-G-033 Reservoir Quality and Porosity Prediction in Carbonate Case Study Singa Field South Sumatra Basin
httpslidepdfcomreaderfullipa11-g-033-reservoir-quality-and-porosity-prediction-in-carbonate-case-study 48
gasporous reservoir with associated low AI values
orange to green corresponds to medium porous
reservoir while brown to black corresponds to tight
reservoir with associated high AI values
We must use an integrated analysis between the
facies analysis (AE) and porosity maps to interpret
reservoir quality in the carbonate reservoir for
minimizing risk in porosity prediction from AI
Figure 8 shows reservoir quality map in upper zone
of carbonate reservoir An understanding of this
analysis is very helpful to support the development
team in its reservoir modelling so that the best areas
for new well locations can be defined
CONCLUSIONS
Reservoir quality and porosity prediction in
carbonates is very difficult In our study an
integration of AI and AE proved useful for
predicting reservoir quality and porosity distribution
in the Singa field Understanding the porosity
distribution as defined by reservoir quality analysis
can support the development team in its reservoir
modelling and optimize new well locations
We successfully drilled one horizontal well (S3)
based on our reservoir modelling Post-drill analysisshows that the well has high porosity carbonate and
produces 30 mmcfpd gases The next plan is to drill
a horizontal well
ACKNOWLEDGMENTS
We would like to thank the management of PT
Medco EampP Indonesia and DITJEN MIGAS for
their permission to publish this paper We also
express our gratitude to our colleagues in the
Exploration Division for their suggestions and
valuable comments during the preparation of this
paper
REFERENCES
Ginger D and Fielding K 2005 The Petroleum
Systems and Future Potential of the South Sumatra
Basin IPA August 2005
Kamal A Argakoesoemah RMI Solichin 2005
A Proposed Basin Scale Lithostratigraphy for SouthSumatra Basin Indonesian Association of
Geologists Stratigraphy of Sumatra Workshop 14 p
Lancester A and Whitcombe D 2000 Fast-track
lsquoColoredrsquo Inversion Presented at SEG 2000
Meeting Expanded Abstracts
Yanto Y and Febriwan T 2008 AVO-Inversion
for Reservoir Characterization of Baturaja
Carbonate Gunung Kembang Field South Sumatra
Basin IPA May 2008
Young P and Wild A 2004 Cosmetic
Enhancement of Seismic Data by Loop
Reconvolution PETEX Conference
8102019 Ipa11-G-033 Reservoir Quality and Porosity Prediction in Carbonate Case Study Singa Field South Sumatra Basin
httpslidepdfcomreaderfullipa11-g-033-reservoir-quality-and-porosity-prediction-in-carbonate-case-study 58
Figure 1 - The Singa field is located approximately 30 km west of the city of Prabumulih
Figure 2 - Structural trend of South Sumatra Basin (after Ginger and Fielding IPA 2005)
8102019 Ipa11-G-033 Reservoir Quality and Porosity Prediction in Carbonate Case Study Singa Field South Sumatra Basin
httpslidepdfcomreaderfullipa11-g-033-reservoir-quality-and-porosity-prediction-in-carbonate-case-study 68
Figure 3 - Generalized stratigraphic column of South Sumatra Basin (after Kamal et al 2005)
Figure 4 - Cross-plot analysis of AI and GR using data from wells S1 and S2 with colour-key water
saturation as hydrocarbon cut-off at 65 Red corresponds to gas and green to brine carbonate
with cut-off AI at 12000 msgrcc
8102019 Ipa11-G-033 Reservoir Quality and Porosity Prediction in Carbonate Case Study Singa Field South Sumatra Basin
httpslidepdfcomreaderfullipa11-g-033-reservoir-quality-and-porosity-prediction-in-carbonate-case-study 78
Figure 5 - Crossplot AI versus Porosity in carbonate reservoir with colour key water saturation The red line
is hi-porosity (gas) trend and the green line is low-porosity (brine) trend with cut-off Porosity at
~8
Figure 6 - Compares section of Seismic AE attribute AI inversion and porosity through wells S1 and S2
The upper panel shows the seismic The second panel shows the AE attribute The third panel
shows absolute AI after inversion The lower panel shows porosity section
8102019 Ipa11-G-033 Reservoir Quality and Porosity Prediction in Carbonate Case Study Singa Field South Sumatra Basin
httpslidepdfcomreaderfullipa11-g-033-reservoir-quality-and-porosity-prediction-in-carbonate-case-study 88
Figure 7 - Horizon slices of AE and Porosity and indicates significant porosity changes in upper carbonate
controlled by facies changes from AE The upper panel shows AE attribute and the second panel
shows Porosity distribution map in several horizon slices from top BRF
Figure 8 - Reservoir quality map in upper zone of carbonate reservoir It is derived from facies analysis
from AE and porosity distribution map
8102019 Ipa11-G-033 Reservoir Quality and Porosity Prediction in Carbonate Case Study Singa Field South Sumatra Basin
httpslidepdfcomreaderfullipa11-g-033-reservoir-quality-and-porosity-prediction-in-carbonate-case-study 28
porosity development in the upper part of the
carbonate
REGIONAL GEOLOGY
Singa field is located in Lematang Block South
Sumatra Basin approximately 30 km west of the
city of Prabumulih (Figure 1) Based on its present
day relative position to the subduction zone it is
categorized as a back-arc basin filled by Tertiary
sediments The South Sumatra Basin can be divided
into three different sub-basins namely the Jambi
Depression Central Palembang Deep and Lematang
Deep Singa field is located within Lematang Deep
(Figure 2)
Structural systems for the South Sumatra Basin
resulted from at least three tectonic styles ie thePre-Tertiary basement inheritance structure the
Eocene-Oligocene rifting mechanism and the most
recently the PliocenendashPleistocene compressional
regime (Figure 2) Lematang Deep is bounded by
the Lematang Fault to the north Beyond the fault is
the Limau Anticlinorium The Musi Platform is the
boundary to the west while the Kuang Platform is
the boundary to the east The Southern boundary for
the Lematang Deep is marked by the Garba
Mountain Lematang Deep itself consists of a series
of horsts and grabens as a product of Eocene-
Oligocene tectonics
Stratigraphy of the South Sumatra Basin began in
the Eocene epoch marked by the deposition of
volcanic rich material pre-rift sediments (Kamal and
Argakoesoemah 2005) (Figure 3) When the rifting
took place syn-rift sediments of the Lemat Fm
were deposited The Lemat Fm is proximal facies
alluvial fan and fan delta facies for the coarser grain
and lacustrine and marine shale for the finer grain
Subsequently the Lower and Upper Talangakar Fm
was deposited This Talangakar group is fluvio-
deltaic facies sediment In Miocene time the rate ofsubsidence decreased and contemporaneously a
global sea level rise took place known as the
Miocene transgression This transgression allowed
most of the paleo-high (horst) to become submerged
below sea level Where the environment was
suitable a carbonate factory formed and Baturaja
Fm was deposited Elsewhere the Telisa Fm was
deposited Singa field reservoir is a carbonate build-
up that formed during this process The relationship
between Telisa Fm and BRF in some places is
interfingering and as the transgression reached its
maximum the accommodation space for carbonate
increased beyond the carbonate factory productivity
As a result most of the carbonate factory failed to
keep up and no significant carbonate build-up
occurred post the Miocene Transgression maxima
In this phase only the Telisa Fm marine shale was
deposited Regression followed the transgression
and the uplift of Barisan Mountain range in the
south west of South Sumatra Basin provided a new
sediment provenance from which the Palembang
Group is the product This group consists of the
Lower Palembang Formation with transitional
sediment facies The Middle Palembang Fm has a
distinctive coal-bearing section and the Upper
Palembang is marked by its volcanic material
content During the Plio-Pleistocene tectonics some
of the formation was uplifted and eroded notably in
the Limau anticlinorium A series of Quaternary
volcanic activities in South Sumatra produced
volcanic material that was deposited over areas in
the South Sumatra Basin
Singa field is interpreted as an isolated carbonate
platform Palaeo-wind direction directly influences
the distribution of high energy wave agitated
carbonate facies within carbonate platforms The
windward side of the carbonate platform usually has
a steeper slope than compared with the leeward side
Carbonate texture in the windward margin is less
muddy The texture can range from packestone to
boundstone providing good initial porosity whilst
the leeward side usually consists of mudstone to
wackestone facies with fair to poor initial porosityThe windward side of the Singa field is interpreted
as the west side while the leeward is the east side of
Singa field
METHODOLOGY
For this study we used two wells and post-stack time
migrated 3D seismic which has relative preserved
amplitudes with low vertical seismic resolution and
15 Hz dominant frequency at the level of the BRF
This is due to the deep carbonate target at 12000 ft
subsurface An average velocity in the BRF of11155 ftsec yields a vertical seismic resolution of
approximately 186 feet equivalent to 26
milliseconds TWT in seismic data
The accuracy of the horizon interpretation of the
carbonate is crucial for seismic inversion analysis
Picking the top BRF and internal reflection
character of the carbonate in conventional
reflectivity data is difficult because of the chaotic
and dimming seismic amplitude effects related to
the low impedance of high porosity facies changes
and gas-bearing in carbonates To overcome this
problem a high frequency enhancement technique
(Young and Wild 2004) relative impedance
8102019 Ipa11-G-033 Reservoir Quality and Porosity Prediction in Carbonate Case Study Singa Field South Sumatra Basin
httpslidepdfcomreaderfullipa11-g-033-reservoir-quality-and-porosity-prediction-in-carbonate-case-study 38
8102019 Ipa11-G-033 Reservoir Quality and Porosity Prediction in Carbonate Case Study Singa Field South Sumatra Basin
httpslidepdfcomreaderfullipa11-g-033-reservoir-quality-and-porosity-prediction-in-carbonate-case-study 48
gasporous reservoir with associated low AI values
orange to green corresponds to medium porous
reservoir while brown to black corresponds to tight
reservoir with associated high AI values
We must use an integrated analysis between the
facies analysis (AE) and porosity maps to interpret
reservoir quality in the carbonate reservoir for
minimizing risk in porosity prediction from AI
Figure 8 shows reservoir quality map in upper zone
of carbonate reservoir An understanding of this
analysis is very helpful to support the development
team in its reservoir modelling so that the best areas
for new well locations can be defined
CONCLUSIONS
Reservoir quality and porosity prediction in
carbonates is very difficult In our study an
integration of AI and AE proved useful for
predicting reservoir quality and porosity distribution
in the Singa field Understanding the porosity
distribution as defined by reservoir quality analysis
can support the development team in its reservoir
modelling and optimize new well locations
We successfully drilled one horizontal well (S3)
based on our reservoir modelling Post-drill analysisshows that the well has high porosity carbonate and
produces 30 mmcfpd gases The next plan is to drill
a horizontal well
ACKNOWLEDGMENTS
We would like to thank the management of PT
Medco EampP Indonesia and DITJEN MIGAS for
their permission to publish this paper We also
express our gratitude to our colleagues in the
Exploration Division for their suggestions and
valuable comments during the preparation of this
paper
REFERENCES
Ginger D and Fielding K 2005 The Petroleum
Systems and Future Potential of the South Sumatra
Basin IPA August 2005
Kamal A Argakoesoemah RMI Solichin 2005
A Proposed Basin Scale Lithostratigraphy for SouthSumatra Basin Indonesian Association of
Geologists Stratigraphy of Sumatra Workshop 14 p
Lancester A and Whitcombe D 2000 Fast-track
lsquoColoredrsquo Inversion Presented at SEG 2000
Meeting Expanded Abstracts
Yanto Y and Febriwan T 2008 AVO-Inversion
for Reservoir Characterization of Baturaja
Carbonate Gunung Kembang Field South Sumatra
Basin IPA May 2008
Young P and Wild A 2004 Cosmetic
Enhancement of Seismic Data by Loop
Reconvolution PETEX Conference
8102019 Ipa11-G-033 Reservoir Quality and Porosity Prediction in Carbonate Case Study Singa Field South Sumatra Basin
httpslidepdfcomreaderfullipa11-g-033-reservoir-quality-and-porosity-prediction-in-carbonate-case-study 58
Figure 1 - The Singa field is located approximately 30 km west of the city of Prabumulih
Figure 2 - Structural trend of South Sumatra Basin (after Ginger and Fielding IPA 2005)
8102019 Ipa11-G-033 Reservoir Quality and Porosity Prediction in Carbonate Case Study Singa Field South Sumatra Basin
httpslidepdfcomreaderfullipa11-g-033-reservoir-quality-and-porosity-prediction-in-carbonate-case-study 68
Figure 3 - Generalized stratigraphic column of South Sumatra Basin (after Kamal et al 2005)
Figure 4 - Cross-plot analysis of AI and GR using data from wells S1 and S2 with colour-key water
saturation as hydrocarbon cut-off at 65 Red corresponds to gas and green to brine carbonate
with cut-off AI at 12000 msgrcc
8102019 Ipa11-G-033 Reservoir Quality and Porosity Prediction in Carbonate Case Study Singa Field South Sumatra Basin
httpslidepdfcomreaderfullipa11-g-033-reservoir-quality-and-porosity-prediction-in-carbonate-case-study 78
Figure 5 - Crossplot AI versus Porosity in carbonate reservoir with colour key water saturation The red line
is hi-porosity (gas) trend and the green line is low-porosity (brine) trend with cut-off Porosity at
~8
Figure 6 - Compares section of Seismic AE attribute AI inversion and porosity through wells S1 and S2
The upper panel shows the seismic The second panel shows the AE attribute The third panel
shows absolute AI after inversion The lower panel shows porosity section
8102019 Ipa11-G-033 Reservoir Quality and Porosity Prediction in Carbonate Case Study Singa Field South Sumatra Basin
httpslidepdfcomreaderfullipa11-g-033-reservoir-quality-and-porosity-prediction-in-carbonate-case-study 88
Figure 7 - Horizon slices of AE and Porosity and indicates significant porosity changes in upper carbonate
controlled by facies changes from AE The upper panel shows AE attribute and the second panel
shows Porosity distribution map in several horizon slices from top BRF
Figure 8 - Reservoir quality map in upper zone of carbonate reservoir It is derived from facies analysis
from AE and porosity distribution map
8102019 Ipa11-G-033 Reservoir Quality and Porosity Prediction in Carbonate Case Study Singa Field South Sumatra Basin
httpslidepdfcomreaderfullipa11-g-033-reservoir-quality-and-porosity-prediction-in-carbonate-case-study 38
8102019 Ipa11-G-033 Reservoir Quality and Porosity Prediction in Carbonate Case Study Singa Field South Sumatra Basin
httpslidepdfcomreaderfullipa11-g-033-reservoir-quality-and-porosity-prediction-in-carbonate-case-study 48
gasporous reservoir with associated low AI values
orange to green corresponds to medium porous
reservoir while brown to black corresponds to tight
reservoir with associated high AI values
We must use an integrated analysis between the
facies analysis (AE) and porosity maps to interpret
reservoir quality in the carbonate reservoir for
minimizing risk in porosity prediction from AI
Figure 8 shows reservoir quality map in upper zone
of carbonate reservoir An understanding of this
analysis is very helpful to support the development
team in its reservoir modelling so that the best areas
for new well locations can be defined
CONCLUSIONS
Reservoir quality and porosity prediction in
carbonates is very difficult In our study an
integration of AI and AE proved useful for
predicting reservoir quality and porosity distribution
in the Singa field Understanding the porosity
distribution as defined by reservoir quality analysis
can support the development team in its reservoir
modelling and optimize new well locations
We successfully drilled one horizontal well (S3)
based on our reservoir modelling Post-drill analysisshows that the well has high porosity carbonate and
produces 30 mmcfpd gases The next plan is to drill
a horizontal well
ACKNOWLEDGMENTS
We would like to thank the management of PT
Medco EampP Indonesia and DITJEN MIGAS for
their permission to publish this paper We also
express our gratitude to our colleagues in the
Exploration Division for their suggestions and
valuable comments during the preparation of this
paper
REFERENCES
Ginger D and Fielding K 2005 The Petroleum
Systems and Future Potential of the South Sumatra
Basin IPA August 2005
Kamal A Argakoesoemah RMI Solichin 2005
A Proposed Basin Scale Lithostratigraphy for SouthSumatra Basin Indonesian Association of
Geologists Stratigraphy of Sumatra Workshop 14 p
Lancester A and Whitcombe D 2000 Fast-track
lsquoColoredrsquo Inversion Presented at SEG 2000
Meeting Expanded Abstracts
Yanto Y and Febriwan T 2008 AVO-Inversion
for Reservoir Characterization of Baturaja
Carbonate Gunung Kembang Field South Sumatra
Basin IPA May 2008
Young P and Wild A 2004 Cosmetic
Enhancement of Seismic Data by Loop
Reconvolution PETEX Conference
8102019 Ipa11-G-033 Reservoir Quality and Porosity Prediction in Carbonate Case Study Singa Field South Sumatra Basin
httpslidepdfcomreaderfullipa11-g-033-reservoir-quality-and-porosity-prediction-in-carbonate-case-study 58
Figure 1 - The Singa field is located approximately 30 km west of the city of Prabumulih
Figure 2 - Structural trend of South Sumatra Basin (after Ginger and Fielding IPA 2005)
8102019 Ipa11-G-033 Reservoir Quality and Porosity Prediction in Carbonate Case Study Singa Field South Sumatra Basin
httpslidepdfcomreaderfullipa11-g-033-reservoir-quality-and-porosity-prediction-in-carbonate-case-study 68
Figure 3 - Generalized stratigraphic column of South Sumatra Basin (after Kamal et al 2005)
Figure 4 - Cross-plot analysis of AI and GR using data from wells S1 and S2 with colour-key water
saturation as hydrocarbon cut-off at 65 Red corresponds to gas and green to brine carbonate
with cut-off AI at 12000 msgrcc
8102019 Ipa11-G-033 Reservoir Quality and Porosity Prediction in Carbonate Case Study Singa Field South Sumatra Basin
httpslidepdfcomreaderfullipa11-g-033-reservoir-quality-and-porosity-prediction-in-carbonate-case-study 78
Figure 5 - Crossplot AI versus Porosity in carbonate reservoir with colour key water saturation The red line
is hi-porosity (gas) trend and the green line is low-porosity (brine) trend with cut-off Porosity at
~8
Figure 6 - Compares section of Seismic AE attribute AI inversion and porosity through wells S1 and S2
The upper panel shows the seismic The second panel shows the AE attribute The third panel
shows absolute AI after inversion The lower panel shows porosity section
8102019 Ipa11-G-033 Reservoir Quality and Porosity Prediction in Carbonate Case Study Singa Field South Sumatra Basin
httpslidepdfcomreaderfullipa11-g-033-reservoir-quality-and-porosity-prediction-in-carbonate-case-study 88
Figure 7 - Horizon slices of AE and Porosity and indicates significant porosity changes in upper carbonate
controlled by facies changes from AE The upper panel shows AE attribute and the second panel
shows Porosity distribution map in several horizon slices from top BRF
Figure 8 - Reservoir quality map in upper zone of carbonate reservoir It is derived from facies analysis
from AE and porosity distribution map
8102019 Ipa11-G-033 Reservoir Quality and Porosity Prediction in Carbonate Case Study Singa Field South Sumatra Basin
httpslidepdfcomreaderfullipa11-g-033-reservoir-quality-and-porosity-prediction-in-carbonate-case-study 48
gasporous reservoir with associated low AI values
orange to green corresponds to medium porous
reservoir while brown to black corresponds to tight
reservoir with associated high AI values
We must use an integrated analysis between the
facies analysis (AE) and porosity maps to interpret
reservoir quality in the carbonate reservoir for
minimizing risk in porosity prediction from AI
Figure 8 shows reservoir quality map in upper zone
of carbonate reservoir An understanding of this
analysis is very helpful to support the development
team in its reservoir modelling so that the best areas
for new well locations can be defined
CONCLUSIONS
Reservoir quality and porosity prediction in
carbonates is very difficult In our study an
integration of AI and AE proved useful for
predicting reservoir quality and porosity distribution
in the Singa field Understanding the porosity
distribution as defined by reservoir quality analysis
can support the development team in its reservoir
modelling and optimize new well locations
We successfully drilled one horizontal well (S3)
based on our reservoir modelling Post-drill analysisshows that the well has high porosity carbonate and
produces 30 mmcfpd gases The next plan is to drill
a horizontal well
ACKNOWLEDGMENTS
We would like to thank the management of PT
Medco EampP Indonesia and DITJEN MIGAS for
their permission to publish this paper We also
express our gratitude to our colleagues in the
Exploration Division for their suggestions and
valuable comments during the preparation of this
paper
REFERENCES
Ginger D and Fielding K 2005 The Petroleum
Systems and Future Potential of the South Sumatra
Basin IPA August 2005
Kamal A Argakoesoemah RMI Solichin 2005
A Proposed Basin Scale Lithostratigraphy for SouthSumatra Basin Indonesian Association of
Geologists Stratigraphy of Sumatra Workshop 14 p
Lancester A and Whitcombe D 2000 Fast-track
lsquoColoredrsquo Inversion Presented at SEG 2000
Meeting Expanded Abstracts
Yanto Y and Febriwan T 2008 AVO-Inversion
for Reservoir Characterization of Baturaja
Carbonate Gunung Kembang Field South Sumatra
Basin IPA May 2008
Young P and Wild A 2004 Cosmetic
Enhancement of Seismic Data by Loop
Reconvolution PETEX Conference
8102019 Ipa11-G-033 Reservoir Quality and Porosity Prediction in Carbonate Case Study Singa Field South Sumatra Basin
httpslidepdfcomreaderfullipa11-g-033-reservoir-quality-and-porosity-prediction-in-carbonate-case-study 58
Figure 1 - The Singa field is located approximately 30 km west of the city of Prabumulih
Figure 2 - Structural trend of South Sumatra Basin (after Ginger and Fielding IPA 2005)
8102019 Ipa11-G-033 Reservoir Quality and Porosity Prediction in Carbonate Case Study Singa Field South Sumatra Basin
httpslidepdfcomreaderfullipa11-g-033-reservoir-quality-and-porosity-prediction-in-carbonate-case-study 68
Figure 3 - Generalized stratigraphic column of South Sumatra Basin (after Kamal et al 2005)
Figure 4 - Cross-plot analysis of AI and GR using data from wells S1 and S2 with colour-key water
saturation as hydrocarbon cut-off at 65 Red corresponds to gas and green to brine carbonate
with cut-off AI at 12000 msgrcc
8102019 Ipa11-G-033 Reservoir Quality and Porosity Prediction in Carbonate Case Study Singa Field South Sumatra Basin
httpslidepdfcomreaderfullipa11-g-033-reservoir-quality-and-porosity-prediction-in-carbonate-case-study 78
Figure 5 - Crossplot AI versus Porosity in carbonate reservoir with colour key water saturation The red line
is hi-porosity (gas) trend and the green line is low-porosity (brine) trend with cut-off Porosity at
~8
Figure 6 - Compares section of Seismic AE attribute AI inversion and porosity through wells S1 and S2
The upper panel shows the seismic The second panel shows the AE attribute The third panel
shows absolute AI after inversion The lower panel shows porosity section
8102019 Ipa11-G-033 Reservoir Quality and Porosity Prediction in Carbonate Case Study Singa Field South Sumatra Basin
httpslidepdfcomreaderfullipa11-g-033-reservoir-quality-and-porosity-prediction-in-carbonate-case-study 88
Figure 7 - Horizon slices of AE and Porosity and indicates significant porosity changes in upper carbonate
controlled by facies changes from AE The upper panel shows AE attribute and the second panel
shows Porosity distribution map in several horizon slices from top BRF
Figure 8 - Reservoir quality map in upper zone of carbonate reservoir It is derived from facies analysis
from AE and porosity distribution map
8102019 Ipa11-G-033 Reservoir Quality and Porosity Prediction in Carbonate Case Study Singa Field South Sumatra Basin
httpslidepdfcomreaderfullipa11-g-033-reservoir-quality-and-porosity-prediction-in-carbonate-case-study 58
Figure 1 - The Singa field is located approximately 30 km west of the city of Prabumulih
Figure 2 - Structural trend of South Sumatra Basin (after Ginger and Fielding IPA 2005)
8102019 Ipa11-G-033 Reservoir Quality and Porosity Prediction in Carbonate Case Study Singa Field South Sumatra Basin
httpslidepdfcomreaderfullipa11-g-033-reservoir-quality-and-porosity-prediction-in-carbonate-case-study 68
Figure 3 - Generalized stratigraphic column of South Sumatra Basin (after Kamal et al 2005)
Figure 4 - Cross-plot analysis of AI and GR using data from wells S1 and S2 with colour-key water
saturation as hydrocarbon cut-off at 65 Red corresponds to gas and green to brine carbonate
with cut-off AI at 12000 msgrcc
8102019 Ipa11-G-033 Reservoir Quality and Porosity Prediction in Carbonate Case Study Singa Field South Sumatra Basin
httpslidepdfcomreaderfullipa11-g-033-reservoir-quality-and-porosity-prediction-in-carbonate-case-study 78
Figure 5 - Crossplot AI versus Porosity in carbonate reservoir with colour key water saturation The red line
is hi-porosity (gas) trend and the green line is low-porosity (brine) trend with cut-off Porosity at
~8
Figure 6 - Compares section of Seismic AE attribute AI inversion and porosity through wells S1 and S2
The upper panel shows the seismic The second panel shows the AE attribute The third panel
shows absolute AI after inversion The lower panel shows porosity section
8102019 Ipa11-G-033 Reservoir Quality and Porosity Prediction in Carbonate Case Study Singa Field South Sumatra Basin
httpslidepdfcomreaderfullipa11-g-033-reservoir-quality-and-porosity-prediction-in-carbonate-case-study 88
Figure 7 - Horizon slices of AE and Porosity and indicates significant porosity changes in upper carbonate
controlled by facies changes from AE The upper panel shows AE attribute and the second panel
shows Porosity distribution map in several horizon slices from top BRF
Figure 8 - Reservoir quality map in upper zone of carbonate reservoir It is derived from facies analysis
from AE and porosity distribution map
8102019 Ipa11-G-033 Reservoir Quality and Porosity Prediction in Carbonate Case Study Singa Field South Sumatra Basin
httpslidepdfcomreaderfullipa11-g-033-reservoir-quality-and-porosity-prediction-in-carbonate-case-study 68
Figure 3 - Generalized stratigraphic column of South Sumatra Basin (after Kamal et al 2005)
Figure 4 - Cross-plot analysis of AI and GR using data from wells S1 and S2 with colour-key water
saturation as hydrocarbon cut-off at 65 Red corresponds to gas and green to brine carbonate
with cut-off AI at 12000 msgrcc
8102019 Ipa11-G-033 Reservoir Quality and Porosity Prediction in Carbonate Case Study Singa Field South Sumatra Basin
httpslidepdfcomreaderfullipa11-g-033-reservoir-quality-and-porosity-prediction-in-carbonate-case-study 78
Figure 5 - Crossplot AI versus Porosity in carbonate reservoir with colour key water saturation The red line
is hi-porosity (gas) trend and the green line is low-porosity (brine) trend with cut-off Porosity at
~8
Figure 6 - Compares section of Seismic AE attribute AI inversion and porosity through wells S1 and S2
The upper panel shows the seismic The second panel shows the AE attribute The third panel
shows absolute AI after inversion The lower panel shows porosity section
8102019 Ipa11-G-033 Reservoir Quality and Porosity Prediction in Carbonate Case Study Singa Field South Sumatra Basin
httpslidepdfcomreaderfullipa11-g-033-reservoir-quality-and-porosity-prediction-in-carbonate-case-study 88
Figure 7 - Horizon slices of AE and Porosity and indicates significant porosity changes in upper carbonate
controlled by facies changes from AE The upper panel shows AE attribute and the second panel
shows Porosity distribution map in several horizon slices from top BRF
Figure 8 - Reservoir quality map in upper zone of carbonate reservoir It is derived from facies analysis
from AE and porosity distribution map
8102019 Ipa11-G-033 Reservoir Quality and Porosity Prediction in Carbonate Case Study Singa Field South Sumatra Basin
httpslidepdfcomreaderfullipa11-g-033-reservoir-quality-and-porosity-prediction-in-carbonate-case-study 78
Figure 5 - Crossplot AI versus Porosity in carbonate reservoir with colour key water saturation The red line
is hi-porosity (gas) trend and the green line is low-porosity (brine) trend with cut-off Porosity at
~8
Figure 6 - Compares section of Seismic AE attribute AI inversion and porosity through wells S1 and S2
The upper panel shows the seismic The second panel shows the AE attribute The third panel
shows absolute AI after inversion The lower panel shows porosity section
8102019 Ipa11-G-033 Reservoir Quality and Porosity Prediction in Carbonate Case Study Singa Field South Sumatra Basin
httpslidepdfcomreaderfullipa11-g-033-reservoir-quality-and-porosity-prediction-in-carbonate-case-study 88
Figure 7 - Horizon slices of AE and Porosity and indicates significant porosity changes in upper carbonate
controlled by facies changes from AE The upper panel shows AE attribute and the second panel
shows Porosity distribution map in several horizon slices from top BRF
Figure 8 - Reservoir quality map in upper zone of carbonate reservoir It is derived from facies analysis
from AE and porosity distribution map
8102019 Ipa11-G-033 Reservoir Quality and Porosity Prediction in Carbonate Case Study Singa Field South Sumatra Basin
httpslidepdfcomreaderfullipa11-g-033-reservoir-quality-and-porosity-prediction-in-carbonate-case-study 88
Figure 7 - Horizon slices of AE and Porosity and indicates significant porosity changes in upper carbonate
controlled by facies changes from AE The upper panel shows AE attribute and the second panel
shows Porosity distribution map in several horizon slices from top BRF
Figure 8 - Reservoir quality map in upper zone of carbonate reservoir It is derived from facies analysis
from AE and porosity distribution map