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Bayesian geological and geophysical data fusion for the construction and uncertainty quantification of 3D geological models 被引量:6
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作者 hugo k.h.olierook Richard Scalzo +5 位作者 David Kohn Rohitash Chandra Ehsan Farahbakhsh Chris Clark Steven M.Reddy R.Dietmar Müller 《Geoscience Frontiers》 SCIE CAS CSCD 2021年第1期479-493,共15页
Traditional approaches to develop 3D geological models employ a mix of quantitative and qualitative scientific techniques,which do not fully provide quantification of uncertainty in the constructed models and fail to ... Traditional approaches to develop 3D geological models employ a mix of quantitative and qualitative scientific techniques,which do not fully provide quantification of uncertainty in the constructed models and fail to optimally weight geological field observations against constraints from geophysical data.Here,using the Bayesian Obsidian software package,we develop a methodology to fuse lithostratigraphic field observations with aeromagnetic and gravity data to build a 3D model in a small(13.5 km×13.5 km)region of the Gascoyne Province,Western Australia.Our approach is validated by comparing 3D model results to independently-constrained geological maps and cross-sections produced by the Geological Survey of Western Australia.By fusing geological field data with aeromagnetic and gravity surveys,we show that 89%of the modelled region has>95%certainty for a particular geological unit for the given model and data.The boundaries between geological units are characterized by narrow regions with<95%certainty,which are typically 400-1000 m wide at the Earth's surface and 500-2000 m wide at depth.Beyond~4 km depth,the model requires geophysical survey data with longer wavelengths(e.g.,active seismic)to constrain the deeper subsurface.Although Obsidian was originally built for sedimentary basin problems,there is reasonable applicability to deformed terranes such as the Gascoyne Province.Ultimately,modification of the Bayesian engine to incorporate structural data will aid in developing more robust 3D models.Nevertheless,our results show that surface geological observations fused with geophysical survey data can yield reasonable 3D geological models with narrow uncertainty regions at the surface and shallow subsurface,which will be especially valuable for mineral exploration and the development of 3D geological models under cover. 展开更多
关键词 Capricorn orogen Machine learning Bayesian inference Markov chain Monte Carlo Solid earth Mineral exploration
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Potassium isotopes trace the formation of juvenile continental crust
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作者 Hamed Gamaleldien Kun Wang +5 位作者 Tim E.Johnson Jian-Feng Ma Mohamed Abu Anbar Xinmu J.Zhang hugo k.h.olierook Christopher L.Kirkland 《Geoscience Frontiers》 SCIE CAS CSCD 2024年第6期37-42,共6页
Constraining the processes associated with the formation of new(juvenile)continental crust from mantle-derived(basaltic)sources is key to understanding the origin and evolution of Earth’s landmasses.Here we present h... Constraining the processes associated with the formation of new(juvenile)continental crust from mantle-derived(basaltic)sources is key to understanding the origin and evolution of Earth’s landmasses.Here we present high-precision measurements of stable isotopes of potassium(K)from Earth’s most voluminous plagiogranites,exposed near El-Shadli in the Eastern Desert of Egypt.These plagiogranites exhibit a wide range of d41K values(–0.31‰±0.06‰to 0.36‰±0.05‰;2 SE,standard error)that are significantly higher(isotopically heavier)than mantle values(–0.42‰±0.08‰).Isotopic(87Sr/86Sr and^(143)Nd/^(144)Nd)and trace element data indicate that the large variation in d41K was inherited from the basaltic source rocks of the El-Shadli plagiogranites,consistent with an origin through partial melting of hydrothermally-altered mid-to-lower oceanic crust.These data demonstrate that K isotopes have the potential to better constrain the source of granitoid rocks and thus the secular evolution of the continental crust. 展开更多
关键词 Potassium isotopes Plagiogranites Arabian-Nubian Shield NEOPROTEROZOIC Crustal growth
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