Structure of the Rambler Rhyolite, Baie Verte Peninsula, Newfoundland: Inversions using UBC-GIF Grav3D and Mag3D

Spicer, Bill; Morris, Bill; Ugalde, Hernan

doi:10.1016/j.jappgeo.2011.06.013

Cited by 15 publications

(9 citation statements)

References 20 publications

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“…3). Data preparation prior to interpretation using UBC‐GIF Mag3D followed the methodology described by Spicer et al . (2011) using Pitney Bowes’ ModelVision software to incorporate geological and geophysical constraints into an input / reference model mesh.…”

Section: Methodsmentioning

confidence: 99%

“…The Alpha weight function controls these terms, α s , for smallness and α x , α y , α z , for smoothness, with w s , w x , w y and w z spatially dependent weighting functions for these parameters. These parameters drive the inversion and can be adjusted to achieve the desired spatial and physical limits (Williams 2008; Spicer, Morris and Ugalde 2011). The amount of ‘smoothing’ can be varied to increase the discernible structure: a higher ratio of smallness to smoothness will reproduce the reference model more closely at the expense of smoothness but may introduce excess structure.…”

Section: Geologic Settingmentioning

confidence: 99%

“…The non‐uniqueness associated with the inverse problem stresses the importance of incorporating physical constraints into the starting reference model to force some geologic form on the resulting output model. Procedures for incorporating geological constraints were described by Spicer et al . (2011).…”

Section: Geologic Settingmentioning

confidence: 99%

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3D geophysical inversions of the north‐east Amer Belt and their relationship to the geologic structure

Tschirhart

Morris

Jefferson

et al. 2012

Geophysical Prospecting

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The Amer Lake area is located within the Churchill Structural Province in the Kivalliq Region of Nunavut, approximately 160 km north‐west of Baker Lake. Two distinct geophysical‐geological entities are structurally intercalated: an Archean mixed granitoid gneiss – metasedimentary‐metavolcanic basement and the unconformably overlying Paleoproterozoic Amer Group metasediments. From east of Amer Lake stretching toward the south‐west, these two entities form the Amer fold and thrust belt. At the north‐east end of this belt, high‐resolution aeromagnetic data define a distinctive oval shape that has been interpreted as a south‐west trending doubly plunging synform. The outcrop within the interior of this structure is sparse resulting in limited structural data and speculative geological interpretations with multiple geometries possible. The high‐resolution aeromagnetic data compiled through an industry‐government consortium and newly acquired detailed gravity profiles were modelled to provide constraints on the geometry of this synform. We document a geophysical‐geological feedback process whereby the available geological and geophysical data were used to derive constraints on inversion models for the synform. Starting with available limited litho‐structural data the presence of a double plunging synform was directly inferred from the aeromagnetic data. Segments of the aeromagnetic data have 2D morphology and so can be modelled using a simple parametric 2D dipping slab inversion approach. Models of profiles extracted from the aeromagnetic data were used to provide preliminary dip and magnetic susceptibility constraints for the Three Lakes mudstone with iron formation and the Five Mile Lake basalt. Landsat imagery outlined the spatial limits of the stratigraphically underlying, non‐magnetic Ayagaq quartzite. Incorporating these outputs as bounds in the input / reference model for a UBC‐GIF 3D magnetic inversion helped to accentuate the geological structure in the output mesh: an enhanced inversion that incorporates both geological and geophysical constraints. The validity of the resulting inversion model was tested by computing 2D forward models of the gravity profile data. The inversion model generated by this study emphasizes the importance of integrating information from as many knowledge sources as one can find. More trust can be placed on forward and inversion models where there is agreement among all data sets and a coherency of structural style.

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Section: Methodsmentioning

confidence: 99%

Section: Geologic Settingmentioning

confidence: 99%

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3D geophysical inversions of the north‐east Amer Belt and their relationship to the geologic structure

Tschirhart

Morris

Jefferson

et al. 2012

Geophysical Prospecting

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“…The upper and lower property bounds are initially assigned to be mean ± one standard deviation of the physical property (Williams ; Spicer et al . ).…”

Section: Potential Field Data Inversionmentioning

confidence: 97%

“…). Among the inversion methods, the algorithm developed by Li and Oldenburg (, ) can obtain reliable results and has been successfully applied to several mineral exploration problems (Phillips ; Williams and Dipple ; Farquharson, Ash and Miller ; Williams ; Spicer, Morris and Ugalde ).…”

Section: Introductionmentioning

confidence: 99%

Using constrained inversion of gravity and magnetic field to produce a 3D litho‐prediction model

Mahmoodi

Smith

Spicer³

2017

Geophysical Prospecting

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Geologically constrained inversion of gravity and magnetic field data of the Victoria property (located in Sudbury, Canada) was undertaken in order to update the present three‐dimensional geological model. The initial and reference model was constructed based on geological information from over 950 drillholes to constrain the inversion. In addition, downhole density and magnetic susceptibility measured in six holes were statistically analysed to derive lower and upper bounds on the physical properties attributed to the lithological units in the reference model. Constrained inversion of the ground gravity and the airborne magnetic data collected at the Victoria property were performed using GRAV3D and MAG3D, respectively. A neural network was trained to predict lithological units from the physical properties measured in six holes. Then, the trained network was applied on the three‐dimensional distribution of physical properties derived from the inversion models to produce a three‐dimensional litho‐prediction model. Some of the features evident in the lithological model are remnants of the constraints, where the data did not demand a significant change in the model from the initial constraining model (e.g., the thin pair of diabase dykes). However, some important changes away from the initial model are evident; for example, a larger body was predicted for quartz diorite, which may be related to the prospective offset dykes; a new zone was predicted as sulfide, which may represent potential mineralisation; and a geophysical subcategory of metabasalt was identified with high magnetic susceptibility and high density. The litho‐prediction model agrees with the geological expectation for the three‐dimensional structure at Victoria and is consistent with the geophysical data, which results in a more holistic understanding of the subsurface lithology.

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Resource prediction and assessment based on 3D/4D big data modeling and deep integration in key ore districts of North China

Wang

Zhang

et al. 2021

Sci. China Earth Sci.

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The North China district has been subjected to significant research with regard to the ore-forming dynamics, processes, and quantitative forecasting of gold deposits; it accounts for the highest number of gold reserves and annual products in China. Based on the top-level design of geoscience theory and the method adopted by the National Key R & D Project (deep process and metallogenic mechanism of North China Craton (NCC) metallogenic system), this paper systematically collects and constructs the geoscience data (district, camp, and deposit scales) in four key gold districts of North China (Jiaojia-Sanshandao, Southern Zhaoping, Wulong, and Qingchengzi). The settings associated with the geological dynamics of gold deposits were quantitatively and synthetically analyzed, namely: NCC destruction, metallogenic events, genetic models, and exploration models. Three-dimensional (3D) and four-dimensional (4D) geological modeling was performed using the big data on the districts, while the district-scale 3D exploration criteria were integrated to construct a quantitative exploration model. Among them, FLAC3D modelling and the GeoCube software (version 3.0) were used to implement the numerical simulation of the 3D geological models and the constraints of the fluid saturation parameters of the Jiaojia fault to reconstruct the 4D fault structure models of the Jiaojia fault (with a depth of 5000 m). Using GeoCube3.0, multiple integration modules (general weights of evidence (WofE), Boost WofE, Fuzzy WofE, Logistic Regression, Information Entropy, and Random Forest) and exploration criteria were integrated, while the C-V fractal classification of A, B and C targets in four districts was carried out. The research results are summarized in the following four areas: (1) Four gold districts in the study area have more than three targets (the depth is 3000 m), and the class A, B and C targets exhibit a good spatial correlation with gold bodies that are controlled by mining engineering at depths greater than 1000 m. (2) The Boost WofE method was used to identify the target optimization in 3D spaces (at depths of 3000-5000 m) of the Jiaojia-Sanshandao, Southern Zhaoping, and Wulong districts. (3) The general WofE method is based on the Bayesian theory in 3D space and provides robust integration and target optimization that are suitable for the Jiaojia-Sanshandao and Southern Zhaoping districts in the Jiaodong area; it can also be applied to the Wulong district in the Liaodong area using a quantitative genetic model and an exploration model. Random forest is a multi-objective integration and target optimization method for 3D spaces, and it is suitable for the complex exploration model in the Qingchengzi district of the Liaodong area. The genetic model and exploration criteria associated with the exploration model of the Qingchengzi district were constrained by the common characteristics of the gold fault structure, magmatic rock emplacement in North China, and the strata fold and interlayer detachment structure. (4) Based on the gold...

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Structure of the Rambler Rhyolite, Baie Verte Peninsula, Newfoundland: Inversions using UBC-GIF Grav3D and Mag3D

Cited by 15 publications

References 20 publications

3D geophysical inversions of the north‐east Amer Belt and their relationship to the geologic structure

3D geophysical inversions of the north‐east Amer Belt and their relationship to the geologic structure

Using constrained inversion of gravity and magnetic field to produce a 3D litho‐prediction model

Resource prediction and assessment based on 3D/4D big data modeling and deep integration in key ore districts of North China

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