Product catalogue
Petrophysical interpretation and reservoir characterisation on Proterozoic shales in NDI Carrara 1, Northern Territory
The Proterozoic succession in the NDI Carrara 1 drill hole, Northern Territory, consists predominantly of tight shales, siltstones, and calcareous clastic rocks. As part of Geoscience Australia’s Exploring for the Future program, this study aims to derive porosity, permeability and gas content from both laboratory testing and well log interpretation from machine learning approaches, to improve the Proterozoic shale gas reservoir characterisation.
The Proterozoic Lawn Hill Formation was divided into four chemostratigraphic packages. The middle two packages were further divided into seven internal units according to principal component analysis and self-organising map clustering on well logs and inorganic geochemical properties. Artificial neural networks were then applied to interpret the mineral compositions, porosity and permeability from well logs, density and neutron-density crossplot interpretations. Gas content was estimated from the interpreted porosity, gas saturation, total organic carbon and clay contents.
Petrophysical interpretation results are summarised for all chemostratigraphic packages and units. Package 2 (1116–1430.1 m) has the highest potential among the four chemostratigraphic packages. P2U1 (1116–1271 m) and P2U3 (1335.5–1430.1 m) units have the most favourable petrophysical properties for organic-rich shales with the average total gas contents of 1.25 cm3/g and 1.30 cm3/g, geometric mean permeability of 4.79 µD and 17.56 µD, and net shale thickness of 54.4 m and 85.3 m, respectively. P3U4 unit (687.9–697.9 m) has high gas content and permeability, with the net shale thickness of 29.1 m. Besides the organic-rich shales, the tight non-organic-rich siltstone and shale reservoirs in package 1 (below 1430.1 m) have average gas saturation of 14% and geometric mean permeability of 1.31 µD, respectively.
Published in The APPEA Journal 2023.
<b>Citation:</b>
Wang Liuqi, Bailey Adam H. E., Grosjean Emmanuelle, Carson Chris, Carr Lidena K., Butcher Grace, Boreham Christopher J., Dewhurst Dave, Esteban Lionel, Southby Chris, Henson Paul A. (2023) Petrophysical interpretation and reservoir characterisation on Proterozoic shales in National Drilling Initiative Carrara 1, Northern Territory. <i>The APPEA Journal</i><b> 63</b>, 230-246.
Simple
Identification info
- Date (Creation)
- 2022-08-18
- Date (Publication)
- 2023-06-22T02:29:11
- Citation identifier
- Geoscience Australia Persistent Identifier/https://pid.geoscience.gov.au/dataset/ga/147318
- Cited responsible party
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Role Organisation / Individual Name Details Author Wang, L.
MEG Internal Contact Author Bailey, A.
MEG Internal Contact Author Grosjean, E.
MEG Internal Contact Author Carson, C.
MEG Internal Contact Author Carr, L.
MEG Internal Contact Author Butcher, G.
MEG Internal Contact Author Boreham, C.
MEG Internal Contact Author Dewhurst, D.
External Contact Author Esteban, L.
External Contact Author Southby, C.
MEG Internal Contact Author Henson, P.
MEG Internal Contact Publisher CSIRO
External Contact
- Name
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The APPEA Journal
- Issue identification
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63 (S1: Proceedings)
- Page
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230-246
- Purpose
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Submission to APPEA Journal 2023
- Status
- Completed
- Point of contact
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Role Organisation / Individual Name Details Point of contact Commonwealth of Australia (Geoscience Australia)
Voice Point of contact Wang, L.
MEG Internal Contact
- Spatial representation type
- Topic category
-
- Geoscientific information
Extent
))
- Maintenance and update frequency
- As needed
Resource format
- Title
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Product data repository: Various Formats
- Website
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Data Store directory containing the digital product files
Data Store directory containing one or more files, possibly in a variety of formats, accessible to Geoscience Australia staff only for internal purposes
- theme.ANZRC Fields of Research.rdf
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EARTH SCIENCES
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- Place
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NDI Carrara 1
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- Theme
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Proterozoic shale
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- Feature type
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porosity
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- Feature type
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permeability
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- Feature type
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gas content
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- Discipline
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machine learning
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- Discipline
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reservoir characterisation
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- Project
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Exploring For The Future
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- Keywords
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Published_External
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Resource constraints
- Title
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Creative Commons Attribution 4.0 International Licence
- Alternate title
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CC-BY
- Edition
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4.0
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Role Organisation / Individual Name Details User Any
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© 2023 The Author(s) (or their employer(s)).
Resource constraints
- Title
-
Australian Government Security Classification System
- Edition date
- 2018-11-01T00:00:00
- Classification
- Unclassified
- Classification system
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Australian Government Security Classification System
- Language
- English
- Character encoding
- UTF8
Distribution Information
- Distributor contact
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Role Organisation / Individual Name Details Distributor Commonwealth of Australia (Geoscience Australia)
Voice facsimile
- OnLine resource
-
Link to Journal
Link to Journal
- Distribution format
-
Resource lineage
- Statement
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This work is part of Exploring for the Future program. All the results have been integrated into a pdf document for The APPEA Journal.
Metadata constraints
- Title
-
Australian Government Security Classification System
- Edition date
- 2018-11-01T00:00:00
- Classification
- Unclassified
Metadata
- Metadata identifier
-
urn:uuid/d6c70e8c-d4eb-4a1f-a840-f84f999e896c
- Title
-
GeoNetwork UUID
- Language
- English
- Character encoding
- UTF8
- Contact
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Role Organisation / Individual Name Details Point of contact Commonwealth of Australia (Geoscience Australia)
Voice Owner Wang, L
Internal Contact
Type of resource
- Resource scope
- Document
- Name
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Journal Articles and Conference Papers
Alternative metadata reference
- Title
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Geoscience Australia - short identifier for metadata record with
uuid
- Citation identifier
- eCatId/147318
- Date info (Creation)
- 2022-10-17T07:05:12
- Date info (Revision)
- 2022-10-17T07:05:12
Metadata standard
- Title
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AU/NZS ISO 19115-1:2014
Metadata standard
- Title
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ISO 19115-1:2014
Metadata standard
- Title
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ISO 19115-3
- Title
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Geoscience Australia Community Metadata Profile of ISO 19115-1:2014
- Edition
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Version 2.0, September 2018
- Citation identifier
- https://pid.geoscience.gov.au/dataset/ga/122551