Abstract
Over the past decades, seismic attributes are applied successfully in hydrocarbon detection and reservoir characterization in several world sedimentary basins. In this study, seismic attributes are applied on seismic data from the Northwestern Australian field to detect hydrocarbon-saturated sandstone reservoirs. The targeted Plover Formation encompasses three intervals of gas-saturated sandstones interbedded with shale and siltstone. Due to the geological complexity of the area (tectonic and stratigraphy), the sands are not easy to track and delineate in seismic attributes. The list of attributes used includes frequency components derived from spectral decomposition, and different amplitude components derived from the amplitude decomposition. Images from spectral decomposition and amplitude decomposition have helped in detecting the gas reservoirs and showed that they are different in thickness. The amplitude and frequency components are then combined into one attribute. The resulting attribute allowed better detection and delineation of the reservoirs. The results from the above interpretations, along with information from petroleum system analysis, were used to identify other prospective zones in the area and propose them as potential drilling targets.
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References
Aki K, Richards PG (1980) Quantitative Seismology: Theory and Methods. Freeman and Co., San Francisco, W.H. https://doi.org/10.1002/gj.3350160110
Castagna JP, Smith SW (1994) Comparison of AVO indicators: a modeling study. Geophysics 59:1849–1855
Castagna JP, Sun S, Siegfried RW (2003) Instantaneous spectral analysis: detection of low-frequency shadows associated with hydrocarbons. Lead Edge 22(2):120–127
Chakraborty A, Okaya D (1995) Frequency-time decomposition of seismic data using wavelet-based methods. Geophysics 60:1906–1910
Chen G, Matteucci G, Fahmi B, Finn., Ch., (2008) Spectral-decomposition response to reservoir fluids from a deepwater West Africa reservoir. Geophysics 73:C23–C30
Chen Y (2020) Nonstationary local time-frequency transform. Geophysics 86(3):V245–V254
Chopra S, Marfurt K (2007) Seismic Attributes for Prospect Identification and Reservoir Characterization. Society of Exploration Geophysicists, Tulsa
ConocoPhillips, 2012. Poseidon 3D marine surface seismic survey int. Report (unpublished).https://drive.google.com/drive/folders/0B7brcf-eGK8Cbk9ueHA0QUU4Zjg. (Accessed 01 March 2021), 1–43.
Dixit A, Mandal A (2020) Detection of gas chimney and its linkage with deep-seated reservoir in Poseidon, NW shelf, Australia from 3D seismic data using multi-attribute analysis and artificial neural network approach. Journal of Natural Gas Science and Engineering 83:103586. https://doi.org/10.1016/j.jngse.2020.103586
Farfour M. and Foster, D., 2020. New AVO expression and classification using pseudo-Poisson reflectivity, SEG Technical Program Expanded Abstracts: 325–329.
Farfour, M., 2020. Amplitude components analysis (ACA). Theory and application. The Leading Edge 39 (1):62a1–62a.
Farfour M, Yoon W, Gaci S, Ouabed N (2020) Spectral decomposition and AVO-based amplitude decomposition: a comparative study and application. J Seism Explor 29:261–273
Farfour M, Yoon WJ, Kim J (2015) Seismic attributes and acoustic impedance inversion in interpretation of complex hydrocarbon reservoirs. J Appl Geophys 111(3):66–75
Fatti, J.L. Smith, G.C. Vail, P.J. Strauss, P.J. Levitt P.R., 1994. Detection of gas in sandstone reservoirs using AVO analysis: a 3-D seismic case history using the Geostack technique Geophysics, 59, 1362–1376.
Gaci S (2018) Time-frequency attributes based on complete ensemble empirical mode decomposition. Lead Edge 37(3):208–212
Han J, van der Baan M (2013) Empirical mode decomposition for seismic time-frequency analysis. Geophysics 78(2):O9–O19. https://doi.org/10.1190/geo2012-0199.1
Herrera RH, Han J, van der Baan M (2014) Applications of the synchrosqueezing transform in seismic time-frequency analysis. Geophysics 79(3):V55–V64. https://doi.org/10.1190/geo2013-0204.1
Hossain S (2019) Application of seismic attribute analysis in fluvial seismic geomorphology. Journal of Petroleum Exploration and Production Technology. https://doi.org/10.1007/s13202-019-00809-z
Le Poidevin, S., Kuske, T.J., Temple, P.R. and Edwards, D.S., 2015—Browse Basin Australian Petroleum Accumulations Report 7 – 2nd Edition. Geoscience Australia Report, Geocat 82545.
Liu G, Fomel S, Chen X (2011) Time-frequency analysis of seismic data using local attributes. Geophysics 76(6):P23–P34. https://doi.org/10.1190/geo2010-0185.1
Liu J, Marfurt K (2007) Instantaneous spectral attributes to detect channels. Geophysics 72:P23–P31
Loizou N, Chen S (2012) The application and value of AVO and spectral decomposition for derisking Palaeogene prospects in the UK North Sea. First Break 30:55–67
Ostrander WJ (1984) Plane-wave reflection coefficients for gas sands at non-normal angles of incidence. Geophysics 49(10):1637–1648
Shuey RT (1985) A simplification of the Zoeppritz equations. Geophysics 50(4):609–614
Sinha S, Routh P, Anno P, Castagna JP (2005) Spectral decomposition of seismic data with continuous-wavelet transform. Geophysics 70(6):P19–P25
Stockwell RG, Mansinha L, Lowe RP (1996) Localization of the complex spectrum: the S transform. IEEE Transact Signal Processing 44:998–1001
Tai, S. Puryear, P. and Castagna J., 2009. Local frequency as a direct hydrocarbon indicator. SEG, Expanded Abstracts, 2160–2164.
Tovaglieri F, George AD (2014) Stratigraphic architecture of an Early-Middle Jurassic tidally influenced deltaic system (Plover Formation), Browse Basin, Australian North West Shelf. Mar Pet Geol 49:59–83
Yoon WJ, Farfour M (2012) Spectral decomposition aids AVO analysis in reservoir characterization: a case study of Blackfoot field, Alberta. Canada Journal of Computers & Geosciences 46(9):60–65
Zhang, Z., Chapman M., Liu, E, and Li X, Wang, Sh., and Liu, Z. 2007. Fluid Detection by Spectral Decomposition – Lessons from Numerical, Physical Modelling and Field Studies. Conference: 69th EAGE Conference and Exhibition incorporating SPE EUROPEC.
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We would like to thank dGB Earth Sciences for providing OpendTect software, CGG for providing HampsonRussell software, and Geoscience Australia for providing the data used in the study.
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The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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Responsible Editor: Narasimman Sundararajan
This paper was selected from the 3rd Conference of the Arabian Journal of Geosciences (CAJG), Tunisia 2020
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Farfour, M., El-Ghali, M.A.K., Gaci, S. et al. Seismic attributes for hydrocarbon detection and reservoir characterization: a case study from Poseidon field, Northwestern Australia. Arab J Geosci 14, 2814 (2021). https://doi.org/10.1007/s12517-021-08853-y
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DOI: https://doi.org/10.1007/s12517-021-08853-y