SlideShare ist ein Scribd-Unternehmen logo
1 von 1
Downloaden Sie, um offline zu lesen
GEOPHYSICAL ANALYSIS OF MIO-PLIOCENE MANGAA FORMATION FOR BETTER
EXPLORATION WITHIN THE PARAHAKI 3D SURVEY; TARANAKI BASIN, OFFSHORE
NEW ZEALAND
Jade Bujardand Rui Zhang
University of Louisiana at Lafayette
Query
The Taranaki Basin is the only
known producing basin within and
around New Zealand with
numerous oil and gas fields. Since
the drilling of the first well in 1865,
the Taranaki basin has remain
relatively underexplored. The
Arawa-1 well was drilled in 1992
used 2D seismic lines. Since the
initial drilling, New Zealand has
started an exploration initiative by
publicly releasing all geological and
geophysical information gathered
on and offshore New Zealand. This
includes the Parihaka 3D survey
which directly overlies the Arawa-1
well and original 2D lines. This
poses the question, with the newly
acquired 3D survey and with
geological information gathered
from the Arawa-1 well, can a set of
geophysical tools now be used to
better locate signatures of
hydrocarbon bearing reservoirs
within the Parihaka 3D survey.
Methods
A 3D seismic volume was
investigated using geophysical tools
in order to locate an area of interest
for hydrocarbon exploration.
Interpreter found high amplitude
teardrop events conforming to
structure. An extrapolation from a
near by well was used to identify a
stratigraphic level of interest. A
coherency volume was created to
investigate stratigraphic features in
an interval zone. A teardrop
stratigraphic feature was found in
time slice (Figure 2) and further
investigated. Average energy
volume was created to differentiate
this high amplitude event from the
background amplitudes (Figure 5).
Afterwards an amplitude extraction
was made off of the mapped horizon
(Figure 3). This was overlaid with
structural contours for an idea of
structural conformance. A model
well was created for a fluid
substitution modeling (Figure 6).
After creating a model with 100%
gas , an amplitude versus offset
model was made off of this model
well. Both the modeled gas
synthetic and the original water
saturation synthetic was compared
to each other. Additionally these
offsets were then compared with the
potential reservoir inside and
outside of the amplitude anomaly
(Figure 8;9).
Conclusion
With the use of the coherence volume,
geomorphological features of interest can easily be
pinpoint. These features can be compared with
depositional environments from available well
logging data. Within the Mangaa formation these
features resemble those of potential reservoirs.
Potential reservoirs can be compared to paleo-
depositional maps for further evidence of potential
reservoirs. AVO analysis within the reservoir
resembles that of a class 4 anomaly. The model of the
modeled gas well resemble the same class 4 AVO
anomaly as that of the inside of the potential
reservoir. The anomaly outside of the reservoir
resembles closely to the original 100% water
saturation synthetic. In conclusion, geophysical tools
from the workflow described can be used to pinpoint
potential areas of interest with a high probability of
hydrocarbon signatures.
Discussion
Upon evaluating well logs of the Arawa-1 (Figure 1), a
stratigraphic area of interest was focused around the Mangaa
Formation. The geomorphological area of interest circle in
(Figure 2) resembled the deposition of a turbidite system
and fit with the paleo-depositional map from King and
Thrasher 1996 (Figure 4). The amplitude signature was
brought out even more, and was better distinguished from
background amplitudes within the average energy attribute
(Figure 5). After mapping the amplitude, the anomaly
resembled the same feature as the coherence an additionally
conformed to structure. Additionally this amplitude anomaly
fit the paleo-depositional map from King and Thrasher 1996.
With these structural contours migration pathways can be
inferred from the down-dip faulting (Figure 3). After
creating a fluid replacement model with purely gas and an
additional AVO model of the same well, the signature of a
gas filled reservoir is closely related to the AVO signature
within the amplitude anomaly (Figure 8). The original water
saturation synthetic resembles that of Figure 9.
References
Arco Petroleum NZ Inc., 1992; Arawa-1 Final well report PPL38436, Ministry of Economic Development New Zealand, Unpublished Petroleum Report PR1824.
Higgs, K.E., D. Strogen, A. Griffin, B. Ilg, M. Arnot, 2012, Reservoirs of the Taranaki Basin, New Zealnd. GNS Science Data Series No. 2012/13a
King, P.R., and G.P. Thrasher, 1996, Cretaceous-Cenozoic geology and petroleum systems of the Taranaki Basin, New Zealand, Institute of Geological and Nuclear
Sciences, vol. 13.
Angle Gather Within Reservoir
Angle Gather Outside Reservoir
Figure 1 Awara-1 Logs
Figure 2 is a coherence time slice through the Mangaa Formation at ~ 1.605sec.
Circle in yellow is the area of interest within the Mangaa Formation.
Figure 3 Is an amplitude extraction map within the Mangaa Formation. Overlaid is structural contours of the
same horizon. Notice the conformance of the amplitude with structure and how brighter amplitudes are
higher.
Figure 4 is a Paleo-depositional map of
Mangaa Formation from King and Thrasher
1996
Figure 5 is an Average Energy cross-section through the amplitude anomaly. This is to delineate the
strength of the anomaly from background amplitudes.
Figure 7 is the fluid replacement model for the Arawa-1 well with the assumption of 100% gas. Additional the AVO
synthetic of both the original water saturation and for the model accompanies this. In yellow is the horizon of interest for
AVO comparison.
Figure 8 is compilation of near mid and far offsets
within the reservoir. Dashed in yellow is the
horizon of interest for AVO comparison.
Figure 9 is compilation of near mid and far
offsets outside of the reservoir. Dashed in
yellow is the horizon of interest for AVO
comparison.
Coherence Time Slice Amplitude Extraction with Structure Overlay Paleo-deposition
Average Energy Cross-Section
Awara-1
Fluid Replacement Model Arawa-1 P
T
B
B’
C
C’
A
A’
B B’
C C’

Weitere ähnliche Inhalte

Was ist angesagt?

frison.ppt
frison.pptfrison.ppt
frison.ppt
grssieee
 
Introduction to Groundwater Modelling
Introduction to Groundwater ModellingIntroduction to Groundwater Modelling
Introduction to Groundwater Modelling
C. P. Kumar
 
2012 BISHOP Interpretation and modelling of the Pedirka Basin using magnetics...
2012 BISHOP Interpretation and modelling of the Pedirka Basin using magnetics...2012 BISHOP Interpretation and modelling of the Pedirka Basin using magnetics...
2012 BISHOP Interpretation and modelling of the Pedirka Basin using magnetics...
Christopher Bishop
 
2D Seismic Data Interpretation and Volumetric Analyis of Dhulain Area, Upper ...
2D Seismic Data Interpretation and Volumetric Analyis of Dhulain Area, Upper ...2D Seismic Data Interpretation and Volumetric Analyis of Dhulain Area, Upper ...
2D Seismic Data Interpretation and Volumetric Analyis of Dhulain Area, Upper ...
Fasih Akhtar
 
Karakterisasi Letusan Merapi menggunakan Data SAR (Synthetic Aperture Radar)
Karakterisasi Letusan Merapi menggunakan Data SAR (Synthetic Aperture Radar)Karakterisasi Letusan Merapi menggunakan Data SAR (Synthetic Aperture Radar)
Karakterisasi Letusan Merapi menggunakan Data SAR (Synthetic Aperture Radar)
Achmad Darul
 
3D Facies Modeling
3D Facies Modeling3D Facies Modeling
3D Facies Modeling
Marc Diviu Franco
 

Was ist angesagt? (20)

Tsunami wave extensively_resurfaced_the_shorelines_of_an_early_martian_ocean
Tsunami wave extensively_resurfaced_the_shorelines_of_an_early_martian_oceanTsunami wave extensively_resurfaced_the_shorelines_of_an_early_martian_ocean
Tsunami wave extensively_resurfaced_the_shorelines_of_an_early_martian_ocean
 
frison.ppt
frison.pptfrison.ppt
frison.ppt
 
northsea
northseanorthsea
northsea
 
Hydrological modelling i5
Hydrological modelling i5Hydrological modelling i5
Hydrological modelling i5
 
Work_Sample_Paper
Work_Sample_PaperWork_Sample_Paper
Work_Sample_Paper
 
Introduction to Groundwater Modelling
Introduction to Groundwater ModellingIntroduction to Groundwater Modelling
Introduction to Groundwater Modelling
 
2012 BISHOP Interpretation and modelling of the Pedirka Basin using magnetics...
2012 BISHOP Interpretation and modelling of the Pedirka Basin using magnetics...2012 BISHOP Interpretation and modelling of the Pedirka Basin using magnetics...
2012 BISHOP Interpretation and modelling of the Pedirka Basin using magnetics...
 
2D Seismic Data Interpretation and Volumetric Analyis of Dhulain Area, Upper ...
2D Seismic Data Interpretation and Volumetric Analyis of Dhulain Area, Upper ...2D Seismic Data Interpretation and Volumetric Analyis of Dhulain Area, Upper ...
2D Seismic Data Interpretation and Volumetric Analyis of Dhulain Area, Upper ...
 
Recent north magnetic pole acceleration towards Siberia caused by flux lobe e...
Recent north magnetic pole acceleration towards Siberia caused by flux lobe e...Recent north magnetic pole acceleration towards Siberia caused by flux lobe e...
Recent north magnetic pole acceleration towards Siberia caused by flux lobe e...
 
Poster GSA 2014
Poster GSA 2014Poster GSA 2014
Poster GSA 2014
 
Scale-dependency and Sensitivity of Hydrological Estimations to Land Use and ...
Scale-dependency and Sensitivity of Hydrological Estimations to Land Use and ...Scale-dependency and Sensitivity of Hydrological Estimations to Land Use and ...
Scale-dependency and Sensitivity of Hydrological Estimations to Land Use and ...
 
Karakterisasi Letusan Merapi menggunakan Data SAR (Synthetic Aperture Radar)
Karakterisasi Letusan Merapi menggunakan Data SAR (Synthetic Aperture Radar)Karakterisasi Letusan Merapi menggunakan Data SAR (Synthetic Aperture Radar)
Karakterisasi Letusan Merapi menggunakan Data SAR (Synthetic Aperture Radar)
 
Continental Mapping Projects - FEMA Butler Co. MO
Continental Mapping Projects - FEMA Butler Co. MOContinental Mapping Projects - FEMA Butler Co. MO
Continental Mapping Projects - FEMA Butler Co. MO
 
Morphometric analysis of a vrishabhavathi sub watershed upstream side of gali...
Morphometric analysis of a vrishabhavathi sub watershed upstream side of gali...Morphometric analysis of a vrishabhavathi sub watershed upstream side of gali...
Morphometric analysis of a vrishabhavathi sub watershed upstream side of gali...
 
REMOTE SENSING DATA FOR HYDROLOGICAL MODELING
REMOTE SENSING DATA FOR HYDROLOGICAL MODELINGREMOTE SENSING DATA FOR HYDROLOGICAL MODELING
REMOTE SENSING DATA FOR HYDROLOGICAL MODELING
 
Field and Theoretical Analysis of Accelerated Consolidation Using Vertical Dr...
Field and Theoretical Analysis of Accelerated Consolidation Using Vertical Dr...Field and Theoretical Analysis of Accelerated Consolidation Using Vertical Dr...
Field and Theoretical Analysis of Accelerated Consolidation Using Vertical Dr...
 
3D Facies Modeling
3D Facies Modeling3D Facies Modeling
3D Facies Modeling
 
Hydrological Application of Remote – Sensing and GIS for Handling of Excess R...
Hydrological Application of Remote – Sensing and GIS for Handling of Excess R...Hydrological Application of Remote – Sensing and GIS for Handling of Excess R...
Hydrological Application of Remote – Sensing and GIS for Handling of Excess R...
 
AMIP
AMIPAMIP
AMIP
 
PREFEASIBILITY DESIGN OF A 2×25 MW SINGLE-FLASH GEOTHERMAL POWER PLANT IN ASA...
PREFEASIBILITY DESIGN OF A 2×25 MW SINGLE-FLASH GEOTHERMAL POWER PLANT IN ASA...PREFEASIBILITY DESIGN OF A 2×25 MW SINGLE-FLASH GEOTHERMAL POWER PLANT IN ASA...
PREFEASIBILITY DESIGN OF A 2×25 MW SINGLE-FLASH GEOTHERMAL POWER PLANT IN ASA...
 

Ähnlich wie AAPG2016_Poster

LGMC_Liu_Allen_OS20160218
LGMC_Liu_Allen_OS20160218LGMC_Liu_Allen_OS20160218
LGMC_Liu_Allen_OS20160218
Jie Liu
 
Time-lapse Stress Effects in Seismic Data
Time-lapse Stress Effects in Seismic DataTime-lapse Stress Effects in Seismic Data
Time-lapse Stress Effects in Seismic Data
Ali Osman Öncel
 
Effects of shale volume distribution on the elastic properties of reserviors ...
Effects of shale volume distribution on the elastic properties of reserviors ...Effects of shale volume distribution on the elastic properties of reserviors ...
Effects of shale volume distribution on the elastic properties of reserviors ...
DR. RICHMOND IDEOZU
 
Mercator Ocean newsletter 50
Mercator Ocean newsletter 50Mercator Ocean newsletter 50
Mercator Ocean newsletter 50
Mercator Ocean International
 

Ähnlich wie AAPG2016_Poster (20)

Delineation of Hydrocarbon Bearing Reservoirs from Surface Seismic and Well L...
Delineation of Hydrocarbon Bearing Reservoirs from Surface Seismic and Well L...Delineation of Hydrocarbon Bearing Reservoirs from Surface Seismic and Well L...
Delineation of Hydrocarbon Bearing Reservoirs from Surface Seismic and Well L...
 
Reassessing the Hydrocarbon Potential of Bornu Basin through Electrofacies an...
Reassessing the Hydrocarbon Potential of Bornu Basin through Electrofacies an...Reassessing the Hydrocarbon Potential of Bornu Basin through Electrofacies an...
Reassessing the Hydrocarbon Potential of Bornu Basin through Electrofacies an...
 
LGMC_Liu_Allen_OS20160218
LGMC_Liu_Allen_OS20160218LGMC_Liu_Allen_OS20160218
LGMC_Liu_Allen_OS20160218
 
Arithmetic relaxation time of induced polarization fractal dimension for char...
Arithmetic relaxation time of induced polarization fractal dimension for char...Arithmetic relaxation time of induced polarization fractal dimension for char...
Arithmetic relaxation time of induced polarization fractal dimension for char...
 
Malampaya work
Malampaya workMalampaya work
Malampaya work
 
Molecular water detected on the sunlit Moon by SOFIA
Molecular water detected on the sunlit Moon by SOFIAMolecular water detected on the sunlit Moon by SOFIA
Molecular water detected on the sunlit Moon by SOFIA
 
Seismic attributes and acoustic impedance,3D reservoir modelling ras fanar
Seismic attributes and acoustic impedance,3D reservoir modelling ras fanarSeismic attributes and acoustic impedance,3D reservoir modelling ras fanar
Seismic attributes and acoustic impedance,3D reservoir modelling ras fanar
 
Arithmetic relaxation time of induced polarization fractal dimension
Arithmetic relaxation time of induced polarization fractal dimensionArithmetic relaxation time of induced polarization fractal dimension
Arithmetic relaxation time of induced polarization fractal dimension
 
Time-lapse Stress Effects in Seismic Data
Time-lapse Stress Effects in Seismic DataTime-lapse Stress Effects in Seismic Data
Time-lapse Stress Effects in Seismic Data
 
Effects of shale volume distribution on the elastic properties of reserviors ...
Effects of shale volume distribution on the elastic properties of reserviors ...Effects of shale volume distribution on the elastic properties of reserviors ...
Effects of shale volume distribution on the elastic properties of reserviors ...
 
Pumped Ambient 2009
Pumped Ambient 2009Pumped Ambient 2009
Pumped Ambient 2009
 
E05722124
E05722124E05722124
E05722124
 
The Impact of Seismic Facies Analysis on the Reservoir Architecture of “CHARL...
The Impact of Seismic Facies Analysis on the Reservoir Architecture of “CHARL...The Impact of Seismic Facies Analysis on the Reservoir Architecture of “CHARL...
The Impact of Seismic Facies Analysis on the Reservoir Architecture of “CHARL...
 
Pressure head fractal dimension for characterizing shajara reservoirs of the ...
Pressure head fractal dimension for characterizing shajara reservoirs of the ...Pressure head fractal dimension for characterizing shajara reservoirs of the ...
Pressure head fractal dimension for characterizing shajara reservoirs of the ...
 
Mercator Ocean newsletter 50
Mercator Ocean newsletter 50Mercator Ocean newsletter 50
Mercator Ocean newsletter 50
 
Geometric relaxation time of induced polarization fractal dimension for chara...
Geometric relaxation time of induced polarization fractal dimension for chara...Geometric relaxation time of induced polarization fractal dimension for chara...
Geometric relaxation time of induced polarization fractal dimension for chara...
 
Geometric relaxation time of induced polarization fractal dimension for chara...
Geometric relaxation time of induced polarization fractal dimension for chara...Geometric relaxation time of induced polarization fractal dimension for chara...
Geometric relaxation time of induced polarization fractal dimension for chara...
 
tle31050528.1
tle31050528.1tle31050528.1
tle31050528.1
 
Effect of Petrophysical Parameters on Water Saturation in Carbonate Formation
Effect of Petrophysical Parameters on Water Saturation in Carbonate FormationEffect of Petrophysical Parameters on Water Saturation in Carbonate Formation
Effect of Petrophysical Parameters on Water Saturation in Carbonate Formation
 
Coulton Sess6 101309
Coulton Sess6 101309Coulton Sess6 101309
Coulton Sess6 101309
 

AAPG2016_Poster

  • 1. GEOPHYSICAL ANALYSIS OF MIO-PLIOCENE MANGAA FORMATION FOR BETTER EXPLORATION WITHIN THE PARAHAKI 3D SURVEY; TARANAKI BASIN, OFFSHORE NEW ZEALAND Jade Bujardand Rui Zhang University of Louisiana at Lafayette Query The Taranaki Basin is the only known producing basin within and around New Zealand with numerous oil and gas fields. Since the drilling of the first well in 1865, the Taranaki basin has remain relatively underexplored. The Arawa-1 well was drilled in 1992 used 2D seismic lines. Since the initial drilling, New Zealand has started an exploration initiative by publicly releasing all geological and geophysical information gathered on and offshore New Zealand. This includes the Parihaka 3D survey which directly overlies the Arawa-1 well and original 2D lines. This poses the question, with the newly acquired 3D survey and with geological information gathered from the Arawa-1 well, can a set of geophysical tools now be used to better locate signatures of hydrocarbon bearing reservoirs within the Parihaka 3D survey. Methods A 3D seismic volume was investigated using geophysical tools in order to locate an area of interest for hydrocarbon exploration. Interpreter found high amplitude teardrop events conforming to structure. An extrapolation from a near by well was used to identify a stratigraphic level of interest. A coherency volume was created to investigate stratigraphic features in an interval zone. A teardrop stratigraphic feature was found in time slice (Figure 2) and further investigated. Average energy volume was created to differentiate this high amplitude event from the background amplitudes (Figure 5). Afterwards an amplitude extraction was made off of the mapped horizon (Figure 3). This was overlaid with structural contours for an idea of structural conformance. A model well was created for a fluid substitution modeling (Figure 6). After creating a model with 100% gas , an amplitude versus offset model was made off of this model well. Both the modeled gas synthetic and the original water saturation synthetic was compared to each other. Additionally these offsets were then compared with the potential reservoir inside and outside of the amplitude anomaly (Figure 8;9). Conclusion With the use of the coherence volume, geomorphological features of interest can easily be pinpoint. These features can be compared with depositional environments from available well logging data. Within the Mangaa formation these features resemble those of potential reservoirs. Potential reservoirs can be compared to paleo- depositional maps for further evidence of potential reservoirs. AVO analysis within the reservoir resembles that of a class 4 anomaly. The model of the modeled gas well resemble the same class 4 AVO anomaly as that of the inside of the potential reservoir. The anomaly outside of the reservoir resembles closely to the original 100% water saturation synthetic. In conclusion, geophysical tools from the workflow described can be used to pinpoint potential areas of interest with a high probability of hydrocarbon signatures. Discussion Upon evaluating well logs of the Arawa-1 (Figure 1), a stratigraphic area of interest was focused around the Mangaa Formation. The geomorphological area of interest circle in (Figure 2) resembled the deposition of a turbidite system and fit with the paleo-depositional map from King and Thrasher 1996 (Figure 4). The amplitude signature was brought out even more, and was better distinguished from background amplitudes within the average energy attribute (Figure 5). After mapping the amplitude, the anomaly resembled the same feature as the coherence an additionally conformed to structure. Additionally this amplitude anomaly fit the paleo-depositional map from King and Thrasher 1996. With these structural contours migration pathways can be inferred from the down-dip faulting (Figure 3). After creating a fluid replacement model with purely gas and an additional AVO model of the same well, the signature of a gas filled reservoir is closely related to the AVO signature within the amplitude anomaly (Figure 8). The original water saturation synthetic resembles that of Figure 9. References Arco Petroleum NZ Inc., 1992; Arawa-1 Final well report PPL38436, Ministry of Economic Development New Zealand, Unpublished Petroleum Report PR1824. Higgs, K.E., D. Strogen, A. Griffin, B. Ilg, M. Arnot, 2012, Reservoirs of the Taranaki Basin, New Zealnd. GNS Science Data Series No. 2012/13a King, P.R., and G.P. Thrasher, 1996, Cretaceous-Cenozoic geology and petroleum systems of the Taranaki Basin, New Zealand, Institute of Geological and Nuclear Sciences, vol. 13. Angle Gather Within Reservoir Angle Gather Outside Reservoir Figure 1 Awara-1 Logs Figure 2 is a coherence time slice through the Mangaa Formation at ~ 1.605sec. Circle in yellow is the area of interest within the Mangaa Formation. Figure 3 Is an amplitude extraction map within the Mangaa Formation. Overlaid is structural contours of the same horizon. Notice the conformance of the amplitude with structure and how brighter amplitudes are higher. Figure 4 is a Paleo-depositional map of Mangaa Formation from King and Thrasher 1996 Figure 5 is an Average Energy cross-section through the amplitude anomaly. This is to delineate the strength of the anomaly from background amplitudes. Figure 7 is the fluid replacement model for the Arawa-1 well with the assumption of 100% gas. Additional the AVO synthetic of both the original water saturation and for the model accompanies this. In yellow is the horizon of interest for AVO comparison. Figure 8 is compilation of near mid and far offsets within the reservoir. Dashed in yellow is the horizon of interest for AVO comparison. Figure 9 is compilation of near mid and far offsets outside of the reservoir. Dashed in yellow is the horizon of interest for AVO comparison. Coherence Time Slice Amplitude Extraction with Structure Overlay Paleo-deposition Average Energy Cross-Section Awara-1 Fluid Replacement Model Arawa-1 P T B B’ C C’ A A’ B B’ C C’