Petrophysical characterisation of the Neoproterozoic and Cambrian successions in the Officer Basin
Liuqi Wang A * , Adam H. E. Bailey A , Lidena K. Carr A , Dianne S. Edwards A , Kamal Khider A , Jade Anderson A , Christopher J. Boreham A , Chris Southby A , David N. Dewhurst B , Lionel Esteban B , Stuart Munday C and Paul A. Henson AA Geoscience Australia, GPO Box 378, Canberra, ACT 2601, Australia.
B CSIRO Energy, Perth, WA 6151, Australia.
C Chemostrat Australia, Perth, WA 6005, Australia.
The APPEA Journal 62(1) 381-399 https://doi.org/10.1071/AJ21076
Submitted: 20 January 2022 Accepted: 28 February 2022 Published: 13 May 2022
© 2022 The Author(s) (or their employer(s)). Published by CSIRO Publishing on behalf of APPEA. This is an open access article distributed under the Creative Commons Attribution 4.0 International License (CC BY).
Abstract
The Neoproterozoic–Paleozoic Officer Basin, located in South Australia and Western Australia, remains a frontier basin for energy exploration, with significant uncertainty due to a paucity of data. As part of Geoscience Australia’s Exploring for the Future (EFTF) program, the objective of this study is to derive the petrophysical properties and to characterise potential reservoirs in the Neoproterozoic–Cambrian sedimentary succession in the Officer Basin through laboratory testing and well log interpretation using both conventional and neural network methods. Laboratory measurements of 41 legacy core samples provide the relationships between gas permeability, Klinkenberg corrected permeability, and nano-scale permeability, as well as grain density, effective and total porosity for various rock types. Conventional log interpretation generates the volume fraction of shale, effective and total porosity from gamma ray and lithology logs. A self-organising map (SOM) was used to cluster the well log data to generate petrophysical group/class index and probability profiles for different classes. Neural network technology was employed to approximate porosity and permeability from logs, conventional interpretation results and class index from SOM modelling. The Neoproterozoic−Cambrian successions have the potential to host both conventional and tight hydrocarbon reservoirs. Neoproterozoic successions are demonstrated to host mainly tight reservoirs with the range in average porosity and geometric mean permeability of 4.77–6.39% and 0.00087–0.01307 mD, respectively, in the different sequences. The range in average porosity and geometric mean permeability of the potential Cambrian conventional reservoirs is 14.54−26.38% and 0.341−103.68 mD, respectively. The Neoproterozoic shales have favourable sealing capacities. This work updates the knowledge of rock properties to further the evaluation of the resource potential of the Officer Basin.
Keywords: Cambrian, characterisation, Exploring for the Future, laboratory measurement, log interpretation, Neoproterozoic, neural network, Officer Basin, permeability, porosity, reservoir, seal.
Liuqi Wang is a Petrophysics Specialist at Geoscience Australia, working in the Minerals, Energy and Groundwater Division. He received his PhD in Petroleum Engineering and worked as a Research Fellow at the University of New South Wales before joining Geoscience Australia. His research interests include petrophysics, static and dynamic reservoir modelling, applied statistics and artificial intelligence. He is a member of PESA and European Association of Geoscientists and Engineers. |
Adam H. E. Bailey is a Petroleum Geoscientist at Geoscience Australia, with expertise in petroleum geomechanics, structural geology and basin analysis. He graduated with a BSc (Hons) in 2012 and a PhD in 2016 from the Australian School of Petroleum at the University of Adelaide. Working with the Onshore Energy Systems team at Geoscience Australia, Adam is currently working on the flagship Exploring for the Future (EFTF) program in Northern Australia, and he is the Geology Discipline Lead for the Geological and Bioregional Assessment Program. |
Lidena K. Carr is a Geoscientist for the Onshore Energy Systems project within the Resources Division at Geoscience Australia. She graduated from the Australian National University (ANU), majoring in Geology and Human Ecology, with a BA/BSc (Hons) in 2004, and she began working as a technical officer at the Research School of Earth Sciences (ANU). In 2007, she joined Geoscience Australia with the then ACRES (satellite imagery), and in 2009 she moved to the then Onshore Energy and Mineral Division to work as a Seismic iInterpreter and Basin Analyst. Currently, she is the acting Director of the Onshore Energy Systems directorate working on the EFTF program. She is a member of PESA and the Geological Society of Australia (GSA). |
Dianne S. Edwards is a Principal Petroleum Geochemist at Geoscience Australia, working in the Minerals, Energy and Groundwater Division. Her scientific focus is on defining the petroleum systems of Australia’s petroliferous basins, including both conventional and unconventional play types. She is involved in building database systems to release petroleum geochemical data via the portal https://portal.ga.gov.au. Dianne received her BSc (Hons) degree in Geology and her MSc degree in Organic Petrology and Organic Geochemistry from the University of Newcastle-upon-Tyne (UK). She was awarded her PhD from the University of Adelaide in 1996. In 2018, she received the Australian Organic Geochemistry Conference Medal for lifetime achievement in the field of Organic Geochemistry. Dianne is a member of PESA. |
Kamal Khider is a Senior Geoscientist in Geoscience Australia’s Resources Division, Energy Systems Branch. He has a BSc, MSc and PhD (Stratigraphy and Sedimentology) and a PhD in Applied Geochemistry. Kamal has long-standing academic and consultative experience in geosciences, working in many academic and industrial geological organisations in Australia, the Middle East and North Africa. He worked on the regional geological appraisal of the Eocene–Oligocene–Miocene boundaries International Geological Correlation Programme 174, regional geochemical assessment of the Cobar-Girilambone region in NSW and the Qld Carbon Dioxide Geological Storage Atlas. Since 2007, he has worked on several of Geoscience Australia’s petroleum and carbon capture and storage projects. Kamal is a member of the American Association of Petroleum Geologists, GSA and the Society for Sedimentary Geology. |
Jade Anderson works as a Geoscientist in basin systems at Geoscience Australia. She completed a PhD at the University of Adelaide in 2015, in the areas of metamorphic geology, geochronology and Proterozoic Australia tectonics. |
Christopher J. Boreham is a Principal Petroleum Geochemist at Geoscience Australia, working in the Minerals, Energy and Groundwater Division. He obtained his PhD in Chemistry at ANU and has worked at Geoscience Australia for over 4 decades. He is a Petroleum Geochemist with extensive experience in the application of organic geochemistry to the evolution of oil and gas in Australian sedimentary basins. More recently, he has extended these geochemical studies to unconventional petroleum (coal seam methane, shale gas and oil), natural molecular hydrogen and in CO2CRC’s studies on the injection of carbon dioxide (CO2) into a depleted natural gas field and a saline aquifer. |
Chris Southby is a Geoscientist in the Geoscience Australia Resources Division, Energy Systems Branch. He completed his Honours at ANU in 2004, on paleo-climate geochemistry of corals from Papua New Guinea. Since joining Geoscience Australia in 2008, he has contributed to a number of projects, including the National Carbon Mapping and Infrastructure Plan, the Vlaming Sub-basin CO2 Storage Assessment and the Houtman Sub-basin Prospectivity Project. He is now part of the Onshore Energy Systems team at Geoscience Australia, currently working under the EFTF project initiative. |
David N. Dewhurst is a Chief Research Scientist at CSIRO Energy in Perth. He holds a BSc (Hons) in Geology from the University of Sheffield (UK) and a PhD in Physics from the University of Newcastle Upon Tyne (UK). He previously held post-doctoral positions at the University of Birmingham (UK), the University of Newcastle upon Tyne (UK), the Institut Français du Pétrole near Paris and Imperial College, London, before moving to CSIRO in 1998. He works on mechanical and physical properties of rocks for petroleum exploration and development, specialising in overburden and gas shales, as well as reservoir and seal evaluation for geological storage of CO2 and other gases. |
Lionel Esteban holds a PhD in applied geophysics, magnetic environment and petrophysics from joint French Universities (University Paul Sabatier-Toulouse and University of Strasbourg, and Institut de Physique du Globe) and the French Nuclear Waste Management (Andra). Lionel Esteban is currently a Principal Petrophysicist at CSIRO (Perth, WA), a member of the Society of Petrophysicists and Well Log Analysts and the Society of Petroleum Engineers, and an academic editor of the Geofluids journal. He develops and tests petrophysical experimental laboratory approaches and integrates them into log analyses to characterise and understand the physical property responses of unconventional and conventional reservoirs at different scales, using a wide spectrum of petrophysical tools, including X-ray imaging, electrical, nuclear magnetic resonance, mechanical, and core flooding under (or not) high pressure/high temperature. His current research focuses on low permeability reservoirs to understand clay mineral relationships, hydrocarbon storage and sealing capacity, CO2–rock interactions and core flooding in carbonates, and drilling mud effects on rock properties in conventional reservoirs. |
Stuart Munday has worked for Chemostrat for 5 years, based initially in New Zealand and now in Perth, working on projects throughout the APAC region. Prior to this, he was a Senior Geologist at New Zealand Oil and Gas, but he has spent most of his career at BG Group, where he has worked on various North African assets prior to being posted to QGC in Brisbane. Stuart previously worked for Roc Oil in the North Sea and at Exploration Consultants Ltd, where his focus was on the basins of sub-Saharan Africa. He has a BSc in Geology, a MSc in Petroleum Geology and is a Fellow of the Geological Society of London. |
Paul A. Henson graduated from the University of Tasmania and is currently the Director of the Onshore Energy Systems Section at Geoscience Australia. He has extensive experience in the minerals sector, working on mineral systems in Proterozoic and Archaean terranes. Since 2010, he has led the Australian Governments’ Onshore Carbon Storage Project, undertaking deep onshore drilling and seismic acquisition programs in collaboration with the states and industry. In addition, he now manages the EFTF–energy program, leading a team of researchers to acquire new pre-competitive geoscientific data to improve our understanding of the oil and gas potential of Australian onshore basins. |
References
Ahmed TH (2002) ‘Reservoir Engineering Handbook’, 2nd edn. p. 184. (Gulf Professional Publishing: Houston, TX)Apak, SN, and Carlsen, GM (2003). Seismic stratigraphic framework of the Neoproterozoic successions, Officer Basin, Western Australia. Geological Survey of Western Australia, Annual Review 2001–02, 80–87.
Apak SN, Moors HT (2001) Basin development and petroleum exploration potential of the Lennis area, Officer Basin, Western Australia. Western Australia Geological Survey, Report 77, p. 42.
Apak SN, Moors HT, Stevens MK (2001) GSWA Vines 1 well completion report, Waigen area, Officer Basin, Western Australia. GSWA Record 2001/18, p. 37.
Asquith G, Krygowski D (2004) Basic well log analysis. AAPG Methods in Exploration Series, No. 16, p. 244.
Avila J, Hauck T (2017) ‘Scikit-learn Cookbook’, 2nd edn. (Copyright ©2017 Packt Publishing Ltd) Available at https://www.packtpub.com/product/scikit-learn-cookbook-second-edition/9781787286382 [verified 20 January 2022]
Bailey A, Wang L, Dewhurst DN, Esteban L, Kager S, Monmusson L, Jarrett AJM, Henson P (2021) Exploring for the Future – petrophysical and geomechanical testing program data release, Officer Basin, Australia. Record 2021/28. Geoscience Australia, Canberra.
| Crossref |
Balashov D, Egorov D, Belozerov B, Slivkin S (2019) Prediction of wells productive characteristics with the use of unsupervised machine learning algorithms. Paper presented at the SPE Russian Petroleum Technology Conference, Moscow, Russia, 22–24 October 2019. Paper no. SPE 196857.
| Crossref |
Boult PJ, Rankin L (2004) Eastern Officer Basin – new play sleeping giant. In ‘Eastern Australasian Basins Symposium II’. (Eds PJ Boult, DR Johns, SC Lang) pp. 231–242. (Petroleum Exploration Society of Australia: Australia)
Bradshaw BE, Khider K, MacFarlane S, Carr L, Henson P (2021) Tectonostratigraphic evolution of the Centralian Superbasin (Australia) revealed through three-dimensional well correlations. Record 2021/01. Geoscience Australia, Canberra.
| Crossref |
Brocher, T (2005). Relations between elastic wavespeeds and density in the Earth’s crust. Bulletin of the Seismological Society of America 95, 2081–2092.
| Relations between elastic wavespeeds and density in the Earth’s crust.Crossref | GoogleScholarGoogle Scholar |
Brownlee J (2019) 8 Tricks for Configuring Backpropagation to Train Better Neural Networks. Available at https://machinelearningmastery.com/best-advice-for-configuring-backpropagation-for-deep-learning-neural-networks/ [verified 20 January 2022]
Carlsen, GM, Simeonova, AP, and Apak, SN (2003). Petroleum systems and exploration potential in the Officer Basin, Western Australia. The APPEA Journal 43, 473–494.
| Petroleum systems and exploration potential in the Officer Basin, Western Australia.Crossref | GoogleScholarGoogle Scholar |
Celma R, Farooq U, Douik H, Alawadhi A, Saputelli L (2020) Novel approach to link petrophysical groups into electrofacies by using NMR logs. Paper presented at the Abu Dhabi International Petroleum Exhibition & Conference, Abu Dhabi, UAE, November 2020. Paper no. SPE-203045-MS.
| Crossref |
Crotogino, F, Schneider, G-S, and Evans, DJ (2018). Renewable energy storage in geological formations. Journal of Power and Energy 232, 100–114.
| Renewable energy storage in geological formations.Crossref | GoogleScholarGoogle Scholar |
Cucuzza J (1987) Munta 1 well completion report. South Australia. Department of Primary Industries and Resources. Open file Envelope 1987, p. 368. Available at https://minerals.sarig.sa.gov.au/Details.aspx?DRILLHOLE_NO=712 [verified 20 January 2022]
Dunster JN (1986) Giles 1 well completion report. South Australia. Department of Primary Industries and Resources. Open file Envelope 1986, p. 199. Available at https://minerals.sarig.sa.gov.au/Details.aspx?DRILLHOLE_NO=1067 [verified 20 January 2022]
Ellis DV, Singer M (2007) ‘Well logging for Earth Scientists.’ (Springer Science and Business Media B.V.)
Gardner, GHF, Gardner, LW, and Gregory, AR (1974). Formation velocity and density – the diagnostic basics for stratigraphic traps. Geophysics 39, 770–780.
Geognostics (2021) ‘OZ SEEBASE® 2021 (March 2021).’ (Geognostics Australia Pty Ltd) Available at https://www.geognostics.com/oz-seebase-2021 [verified 20 January 2022]
Gravestock DI (1997) Chapter 5 Geological setting and structural history. In ‘Petroleum Geology of South Australia. Volume 3: Officer Basin’. Report Book, 97/19. (Eds JGG Morton, JF Drexel) pp. 7–22. (Department of Mines and Energy Resources: South Australia)
Grey K, Hocking RM, Stevens MK, Bagas L, Carlsen GM, Irimies F, Pirajno F, Haines PW, Apak SN (2005). Lithostratigraphic nomenclature of the Officer Basin and correlative parts of the Paterson Orogen, Western Australia. Geological Survey of Western Australia, Report, 93, p. 89.
Haines, WP, Hocking, RM, Grey, K, and Stevens, MK (2008). Vines 1 revisited: are older Neoproterozoic glacial deposits preserved in Western Australia? Australian Journal of Earth Sciences 55, 397–406.
Hashimoto T, Bailey A, Chirinos A (2018) ‘Onshore basin inventory volume 2: the Canning, Perth and Officer basins. Record 2018/18.’ (Geoscience Australia: Canberra). Available at https://ecat.ga.gov.au/geonetwork/srv/eng/catalog.search#/metadata/121557 [verified 20 January 2022]
Hect-Nielsen R (1990) ‘Neurocomputing.’ (Addison-Wesley: Menlo Park, CA, USA)
Henderson SW, Tauer RW (1967) Birksgate 1 well completion report. South Australia. Department of Primary Industries and Resources. Open file Envelope 1967, p. 121. Available at https://minerals.sarig.sa.gov.au/Details.aspx?DRILLHOLE_NO=273 [verified 20 January 2022]
Hopfield, JJ (1985). ‘Neural’ computation of decisions in optimization problem. Biological Cybernetics 52, 141–152.
| ‘Neural’ computation of decisions in optimization problem.Crossref | GoogleScholarGoogle Scholar | 4027280PubMed |
Huang, Y, Gedeon, TD, and Wong, PM (2001). An integrated neural-fuzzy genetic-algorithm using hyper-surface membership functions to predict permeability in petroleum reservoirs. Engineering Applications of Artificial Intelligence 14, 15–21.
| An integrated neural-fuzzy genetic-algorithm using hyper-surface membership functions to predict permeability in petroleum reservoirs.Crossref | GoogleScholarGoogle Scholar |
Julian D (2016) ‘Designing machine learning systems with Python.’ (Packt Publishing Ltd). Available at https://www.packtpub.com/product/designing-machine-learning-systems-with-python/9781785882951 [verified 20 January 2022]
Kalogirou, SA (2000). Applications of artificial neural-networks for energy systems. Applied Energy 67, 17–35.
| Applications of artificial neural-networks for energy systems.Crossref | GoogleScholarGoogle Scholar |
Karajas J, Yaylor D (1983) Hussar No 1 Completion Report. p. 8. Available at https://wapims.dmp.wa.gov.au/WAPIMS/Search/Wells [verified 20 January 2022]
Khider K, MacFarlane S, Bradshaw BE, Carr L, Henson P (2021) The Centralian Superbasin (Canning, Amadeus, Georgina and Officer basins) stratigraphic review and well correlations. Record 2021/10. Geoscience Australia, Canberra.
| Crossref |
Kingma DP, Ba JL (2015) Adam: a method for stochastic optimization. International Conference on Learning Representations (ICLR), 2015. Available at https://arxiv.org/pdf/1412.6980.pdf [verified 20 January 2022]
Morton JGG, Drexel JF (1997) Petroleum Geology of South Australia, Volume 3: Officer Basin. Department of Mines and Energy Resources, South Australia, Report Book, 97/19, p. 173.
Munday S, Edwards DS, Chandra J, Forbes A, Riley D, Wang L, Anderson J, Grosjean E, Bailey A, Boreham CJ (2021) Defining a chemostratigraphic framework for the Officer Basin. Record 2022/07. Geoscience Australia, Canberra.
| Crossref |
Ouadfeul, SA, and Aliouane, L (2015). Total organic carbon prediction in shale gas reservoirs from well logs data using the multilayer perceptron neural network with Levenberg Marquardt training algorithm: application to Barnett Shale. Arabian Journal for Science and Engineering 40, 3345–3349.
| Total organic carbon prediction in shale gas reservoirs from well logs data using the multilayer perceptron neural network with Levenberg Marquardt training algorithm: application to Barnett Shale.Crossref | GoogleScholarGoogle Scholar |
PEPS (2021) Petroleum exploration and production system (PEPS) – South Australia. Available at https://peps.sa.gov.au/home [verified 20 January 2022]
Raven MD, Dewhurst DN (2005) Mineralogical and Chemical Composition of Mudrocks from the Lancer-1 Stratigraphic Drillhole, Officer and Gunbarrel Basins, Western Australia. CSIRO Restricted Report No. 04-043, September 2004. Available at https://wapims.dmp.wa.gov.au/WAPIMS/Search/Wells [verified 20 January 2022]
Samson A (2018) Reservoirs and seals. In ‘The Petroleum Geology of South Australia. Vol 3: Officer Basin’. (Ed JGG Morton, JF Drexel) pp. 7–22. Report Book, 97/19. (Department of Mines and Energy Resources: South Australia)
Saputelli L, Celma R, Boyd D, Shebl H, Gomes J, Bahrini F, Escorcia A, Pandey Y (2019) Driving permeability and reservoir rock typing supported with self-organized maps SOM and artificial neural networks ANN - Optimal workflow for enabling core-log integration. Paper presented at the SPE Reservoir Characterisation and Simulation Conference and Exhibition, Abu Dhabi, UAE, 17–19 September 2019. Paper no. SPE 196704.
| Crossref |
SARIG (2021) South Australian Resource Information Gateway. Available at https://minerals.sarig.sa.gov.au/QuickSearch.aspx [verified 20 January 2022]
Schlumberger (1991) ‘Schlumberger Log Interpretation Principles/Applications.’ Seventh printing, ©Schlumberger 1991. (Schlumberger Wireline and Testing: Texas, USA)
Schlumberger (2013) ‘Schlumberger Log Interpretation Charts’, 2013 edn. ©Schlumberger 1991. (Schlumberger Wireline and Testing: Texas, USA)
Selvam RK (2018) Algorithms selected for neural network modelling. Optimization Algorithms – a brief overview. Available at https://www.sravikiran.com/GSOC18//2018/05/16/optimizers/ [verified 20 January 2022]
Shell Development (Australia) Pty Ltd (1981) Yowalga 3 well completion report (Officer Basin), 1981, p. 67. Available at https://wapims.dmp.wa.gov.au/WAPIMS/Search/Wells [verified 20 January 2022]
Stewart M (2019) Neural network optimization – covering optimizers, momentum, adaptive learning rates, normalization, and more. Available at https://towardsdatascience.com/neural-network-optimization-7ca72d4db3e0 [verified 20 January 2022]
Tingate PR, McKirdy DM (2003) Exploration opportunities in the Officer Basin, South Australia. South Australia. Department of Primary Industries and Resources. Report Book 2003/1.
Walter MR, Gorter JD (1994) The Neoproterozoic Centralian Superbasin in Western Australia: The Savory and Officer basins. In ‘The Sedimentary Basins of Western Australia’. Proceedings of the Petroleum Exploration Society of Australia Symposium, Perth. (Eds PG Purcell, RR Purcell) pp. 851–864.
Wang, L, Wong, PM, Kanevski, M, and Gedeon, TD (1999). Combining neural networks with kriging for stochastic reservoir modelling. In situ 23, 151–169.
Wang, L, Edwards, DS, Bailey, A, Carr, LK, Boreham, CJ, Grosjean, E, Normore, L, Anderson, J, Jarrett, AJM, McFarlane, S, Southby, C, Carson, C, Khider, K, and Henson, P (2021). Petrophysical and geochemical interpretations of well logs from the pre-Carboniferous succession in Waukarlycarly 1, Canning Basin, Western Australia. The APPEA Journal 61, 253–270.
| Petrophysical and geochemical interpretations of well logs from the pre-Carboniferous succession in Waukarlycarly 1, Canning Basin, Western Australia.Crossref | GoogleScholarGoogle Scholar |
WAPIMS (2021) Government of Western Australia, Department of Mines, Industry Regulation and Safety. Wells database. https://wapims.dmp.wa.gov.au/WAPIMS/Search/Wells [verified 20 January 2022]
Wong, PM, Jian, FX, and Taggart, IJ (1995). A critical comparison of neural networks and discriminant analysis in lithofacies, porosity and permeability predictions. Journal of Petroleum Geology 18, 191–206.
| A critical comparison of neural networks and discriminant analysis in lithofacies, porosity and permeability predictions.Crossref | GoogleScholarGoogle Scholar |
Yan, W, Wang, J, Liu, S, Wang, K, and Zhou, Y (2014). Logging identification for the Longmaxi mud shale reservoir in the Jiaoshiba area, Sichuan Basin. Natural Gas Industry 34, 30–36.
| Logging identification for the Longmaxi mud shale reservoir in the Jiaoshiba area, Sichuan Basin.Crossref | GoogleScholarGoogle Scholar |
Yu Y (2013) An experimental method to measure the porosity from cuttings: evaluation and error analysis. MS thesis, Texas Tech University, 2013, p. 74.
Zang WL (1995) Neoproterozoic depositional sequences and tectonics, eastern Officer Basin, South Australia. Department of Mines and Energy, South Australia, Report Book 95/21, p. 53.
