Data

Thermo-chemical inversion of the Australian lithospheric mantle (FR23)

Geoscience Australia
Haynes, M. ; Afonso, J.C.
Viewed: [[ro.stat.viewed]] Cited: [[ro.stat.cited]] Accessed: [[ro.stat.accessed]]
ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.26186/147926&rft.title=Thermo-chemical inversion of the Australian lithospheric mantle (FR23)&rft.identifier=10.26186/147926&rft.publisher=Commonwealth of Australia (Geoscience Australia)&rft.description=Lithospheric structure and composition have direct relevance for our understanding of mineral prospectivity. Aspects of the lithosphere can be imaged using geophysical inversion or analysed from exhumed samples at the surface of the Earth, but it is a challenge to ensure consistency between competing models and datasets. The LitMod platform provides a probabilistic inversion framework that uses geology as the fabric to unify multiple geophysical techniques and incorporates a priori geochemical information. Here, we present results from the application of LitMod to the Australian continent. The rasters summarise the results and performance of a Markov-chain Monte Carlo sampling from the posterior model space. Release FR23 is developed using primary-mode Rayleigh phase velocity grids adapted from Fishwick & Rawlinson (2012).Geoscience Australia's Exploring for the Future program provides precompetitive information to inform decision-making by government, community and industry on the sustainable development of Australia's mineral, energy and groundwater resources. By gathering, analysing and interpreting new and existing precompetitive geoscience data and knowledge, we are building a national picture of Australia's geology and resource potential. This leads to a strong economy, resilient society and sustainable environment for the benefit of all Australians. This includes supporting Australia's transition to a low emissions economy, strong resources and agriculture sectors, and economic opportunities and social benefits for Australia's regional and remote communities. The Exploring for the Future program, which commenced in 2016, is an eight year, $225m investment by the Australian Government.Maintenance and Update Frequency: notPlannedStatement: The inversion is based on Markov chain Monte Carlo sampling of major oxide compositions within the lithospheric mantle (Al2O3, CaO, FeO, and MgO). Coupled with temperature and pressure profiles, Gibbs free-energy minimisation (e.g. Connolly, 2009) allows estimation of the dominant mineral phases and, subsequently, the forward physical response. The LitMod inversion platform was used to perform a joint inversion of the following observed data: elevation (Whiteway, 2009), Rayleigh-wave phase velocities (Fishwick & Rawlinson, 2012), surface heat flow (International Heat Flow Commission, 2021), and long-wavelength geoid anomalies (Afonso et al., 2019). The parameterisation consists of 1D vertical columns across the Australian continent, with 1° lateral grid. The crust was divided into three layers: sediments, upper crust and lower crust. As a starting model, the thicknesses of sedimentary sequences were estimated using the Phanerozoic OZ SEEBASE dataset (Frogtech, 2005), and crustal thicknesses were taken from AusMoho2012 (Salmon et al., 2013). Similarly, the lower crust was assumed to comprise half the total crustal thickness, to a maximum of 15 km. Seismic wave speeds and density within the crust were initially set from AuSREM (Salmon et al., 2012). To help ensure that deep mantle structures are not mapped into the lithospheric mantle, we use the GyPSuM reference model (Simmons et al., 2010) to assign lower mantle seismic wave speed and density profiles.&rft.creator=Haynes, M. &rft.creator=Afonso, J.C. &rft.date=2023&rft.coverage=westlimit=111; southlimit=-46; eastlimit=155; northlimit=-9; projection=WGS 84 / geographic 2D (EPSG: 4326)&rft.coverage=westlimit=111; southlimit=-46; eastlimit=155; northlimit=-9; projection=WGS 84 / geographic 2D (EPSG: 4326)&rft_rights=Creative Commons Attribution 4.0 International Licence https://creativecommons.org/licenses/by/4.0/&rft_rights=© Commonwealth of Australia (Geoscience Australia) 2023&rft_rights=Australian Government Security Classification System https://www.protectivesecurity.gov.au/Pages/default.aspx&rft_subject=geoscientificInformation&rft_subject=EFTF – Exploring for the Future&rft_subject=Lithospheric Geophysics&rft_subject=LitMod&rft_subject=Australia's Resources Framework&rft_subject=Lithospheric mantle&rft_subject=Markov-chain Monte Carlo&rft_subject=Bayesian&rft_subject=Peroditite&rft_subject=Joint inversion&rft_subject=Inorganic geochemistry&rft_subject=Igneous and metamorphic petrology&rft_subject=Structural geology and tectonics&rft_subject=Geothermics and radiometrics&rft_subject=Seismology and seismic exploration&rft_subject=Published_External&rft.type=dataset&rft.language=English Access the data
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Creative Commons Attribution 4.0 International Licence
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© Commonwealth of Australia (Geoscience Australia) 2023

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Full description

Lithospheric structure and composition have direct relevance for our understanding of mineral prospectivity. Aspects of the lithosphere can be imaged using geophysical inversion or analysed from exhumed samples at the surface of the Earth, but it is a challenge to ensure consistency between competing models and datasets. The LitMod platform provides a probabilistic inversion framework that uses geology as the fabric to unify multiple geophysical techniques and incorporates a priori geochemical information. Here, we present results from the application of LitMod to the Australian continent. The rasters summarise the results and performance of a Markov-chain Monte Carlo sampling from the posterior model space. Release FR23 is developed using primary-mode Rayleigh phase velocity grids adapted from Fishwick & Rawlinson (2012).

Geoscience Australia's Exploring for the Future program provides precompetitive information to inform decision-making by government, community and industry on the sustainable development of Australia's mineral, energy and groundwater resources. By gathering, analysing and interpreting new and existing precompetitive geoscience data and knowledge, we are building a national picture of Australia's geology and resource potential. This leads to a strong economy, resilient society and sustainable environment for the benefit of all Australians. This includes supporting Australia's transition to a low emissions economy, strong resources and agriculture sectors, and economic opportunities and social benefits for Australia's regional and remote communities. The Exploring for the Future program, which commenced in 2016, is an eight year, $225m investment by the Australian Government.

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Maintenance and Update Frequency: notPlanned
Statement:
The inversion is based on Markov chain Monte Carlo sampling of major oxide compositions within the lithospheric mantle (Al2O3, CaO, FeO, and MgO). Coupled with temperature and pressure profiles, Gibbs free-energy minimisation (e.g. Connolly, 2009) allows estimation of the dominant mineral phases and, subsequently, the forward physical response. The LitMod inversion platform was used to perform a joint inversion of the following observed data: elevation (Whiteway, 2009), Rayleigh-wave phase velocities (Fishwick & Rawlinson, 2012), surface heat flow (International Heat Flow Commission, 2021), and long-wavelength geoid anomalies (Afonso et al., 2019). The parameterisation consists of 1D vertical columns across the Australian continent, with 1° lateral grid. The crust was divided into three layers: sediments, upper crust and lower crust. As a starting model, the thicknesses of sedimentary sequences were estimated using the Phanerozoic OZ SEEBASE dataset (Frogtech, 2005), and crustal thicknesses were taken from AusMoho2012 (Salmon et al., 2013). Similarly, the lower crust was assumed to comprise half the total crustal thickness, to a maximum of 15 km. Seismic wave speeds and density within the crust were initially set from AuSREM (Salmon et al., 2012). To help ensure that deep mantle structures are not mapped into the lithospheric mantle, we use the GyPSuM reference model (Simmons et al., 2010) to assign lower mantle seismic wave speed and density profiles.

Notes

Purpose
A web service of raster datasets covering the Australian continent. The rasters summarise the results and performance of a Markov-chain Monte Carlo sampling from the posterior model space. Release FR23 is developed using primary-mode Rayleigh phase velocity grids adapted from Fishwick & Rawlinson (2012; "3-D structure of the Australian lithosphere from evolving seismic datasets").

Issued: 19 10 2023

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155,-9 155,-46 111,-46 111,-9 155,-9

133,-27.5

text: westlimit=111; southlimit=-46; eastlimit=155; northlimit=-9; projection=WGS 84 / geographic 2D (EPSG: 4326)

Subjects
Australia's Resources Framework | Bayesian | EFTF – Exploring for the Future | Geothermics and radiometrics | Igneous and metamorphic petrology | Inorganic geochemistry | Joint inversion | LitMod | Lithospheric Geophysics | Lithospheric mantle | Markov-chain Monte Carlo | Peroditite | Published_External | Seismology and seismic exploration | Structural geology and tectonics | geoscientificInformation |

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Other Information
Download the data (mpk) [538.3 KB]

url : https://d28rz98at9flks.cloudfront.net/147926/147926_00_0.MPK

Download FR23 - Nearest Neighbour geotiffs (zip) [429.7 KB]

url : https://d28rz98at9flks.cloudfront.net/147926/147926_01_0.ZIP

Lithospheric Mantle WFS

url : https://services.ga.gov.au/gis/lithospheric-mantle/wfs

Lithospheric Mantle WCS

url : https://services.ga.gov.au/gis/lithospheric-mantle/wcs

Lithospheric Mantle WMTS

url : https://services.ga.gov.au/gis/lithospheric-mantle/gwc/service/wmts

Lithospheric Mantle WMS

url : https://services.ga.gov.au/gis/lithospheric-mantle/wms

Thermo-chemical inversion of the Australian lithospheric mantle (KY22)

local : 147315

Lithospheric Mantle WMS

local : 149295

Lithospheric Mantle WMTS

local : 149296

Lithospheric Mantle WCS

local : 149297

Lithospheric Mantle WFS

local : 149298

Identifiers