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The Proterozoic assembly of Australia, the understanding of which is critical for reconstructing Proterozoic supercontinents, involved amalgamation of the West Australian (WAC), North Australian (NAC), and South Australian cratons (SAC). However, the basement between these Archean to early Proterozoic lithospheric blocks is mostly buried beneath younger basins; hence, its composition and age and the timing of Proterozoic assembly remain uncertain. In situ zircon U-Pb-O-Hf analyses of igneous rocks from drillholes that intersected basement beneath the northwestern Canning Basin reveal the presence of a substantial domain of juvenile Proterozoic lithosphere, the Percival Lakes province, between the WAC and NAC. Although isotopically distinct from the neighboring WAC and NAC, the Percival Lakes province is strikingly similar to other juvenile Proterozoic tectonic elements between the WAC, NAC, and SAC. Combining isotope and seismic data, we interpret the Percival Lakes province as part of an ~1700 × 400 km Proterozoic lithospheric domain that lacks evidence of Archean provenance but consists mainly of reworked remnants of Mesoproterozoic oceanic crust that survived WAC-NAC-SAC convergence. The apparent absence of Archean lithosphere between the cratons implies they never directly collided or that complete collision was prevented by impingement of three-dimensional promontories in the converging lithospheric blocks. Instead, the Percival Lakes province and other Proterozoic elements between the WAC, NAC, and SAC consist of oceanic lithosphere extracted from Earth's mantle in the Proterozoic. Our results imply that WAC-NAC convergence was younger than Columbia amalgamation at ca. 1.8 Ga and that Proterozoic Australia formed during the earliest phases of Rodinia assembly at ca. 1.3 Ga.

In this paper we give an example from the Fortitude North prospect in the Kurnalpi Terrane of the eastern Yilgarn Craton, where the integration of geochemistry with borehole petrophysics can be used to identify lithological units, infer geological processes (e.g., magmatic differentiation, alteration and weathering) and constrain geological and geophysical models of the prospect. We use major and immobile trace element concentrations to discriminate between primary lithologies and identify differentiation trends in the mafic magmatic units. Density and seismic velocity measurements show broad correlation with primary rock types, with unaltered dolerite tending to have higher density and velocity compared to basalts and altered rocks. Magnetic susceptibility measurements are used to corroborate geochemical differentiation trends, specifically magnetite fractionation in dolerite units. A range of gold pathfinder and chalcophile elements are used to identify hydrothermal alteration related to gold mineralisation. Integrating geochemistry and petrophysics at drillhole- and prospect-scales helps to constrain important geological processes and demonstrates how those processes can be interpreted from geophysical data sets., Open-Access Online Publication: May 29, 2023

One of the main tasks in 3D geological modeling is the boundary parametrization of the subsurface from geological observations and geophysical inversions. Several approaches have been developed for geometric inversion and joint inversion of geophysical datasets. However, the robust, quantitative integration of models and datasets with different spatial coverage, resolution, and levels of sparsity remains challenging. One promising approach for recovering the boundary of the geological units is the utilization of a level set inversion method with potential field data. We focus on constraining 3D geometric gravity inversion with sparse lower-uncertainty information from a 2D seismic section. We use a level set approach to recover the geometry of geological bodies using two synthetic examples and data from the geologically complex Yamarna Terrane (Yilgarn Craton, Western Australia). In this study, a 2D seismic section has been used for constraining the location of rock unit boundaries being solved during the 3D gravity geometric inversion. The proposed work is the first we know of that automates the process of adding spatially distributed constraints to the 3D level set inversion. In many hard-rock geoscientific investigations, seismic data are sparse, and our results indicate that unit boundaries from gravity inversion can be much better constrained with seismic information even though they are sparsely distributed within the model. Thus, we conclude that it has the potential to bring the state of the art a step further towards building a 3D geological model incorporating several sources of information in similar regions of investigation.

We have developed an inversion method for recovery of the geometry of an arbitrary number of geologic units using a regularized least-squares framework. The method addresses cases in which each geologic unit can be modeled using a constant physical property. Each geologic unit or group assigned the same physical property value is modeled using the signed distance to its interface with other units. We invert for this quantity and recover the location of interfaces between units using the level-set method. We formulate and solve the inverse problem in a least-squares sense by inverting for such signed distances. The sensitivity matrix to perturbations of the interfaces is obtained using the chain rule, and model mapping from the signed distance is used to recover the physical properties. Exploiting the flexibility of the framework that we develop allows any number of rock units to be considered. In addition, it allows the design and use of regularization incorporating prior information to encourage specific features in the inverted model. We apply this general inversion approach to gravity data favoring minimum adjustments of the interfaces between rock units to fit the data. The method is first tested using noisy synthetic data generated for a model compoed of six distinct units, and several scenarios are investigated. It is then applied to field data from the Yerrida Basin (Australia) where we investigate the geometry of a prospective greenstone belt. The synthetic example demonstrates the proof of concept of the proposed methodology, whereas the field application provides insights into, and potential reinterpretation of, the tectonic setting of the area.

Vascular calcification is a hallmark of atherosclerotic disease and serves as a strong predictor and risk factor for cardiovascular events1. Growing evidence points towards macroautophagy (herein referred to simply as autophagy), a cellular self-degradation process, as being protective during early atherosclerosis2. However, autophagy may become dysregulated with advanced atherosclerosis3. Vascular smooth muscle cells (VSMC) contribute to early and advanced atherosclerosis by regulating vascular remodeling and calcification. The precise effects of autophagy on VSMC-mediated calcification are unknown. Here, we combined multi-omic profiling and high-resolution structural imaging to pinpoint an epigenetic mechanism by which impaired autophagy drives VSMC calcification. Our studies revealed dysfunctional autophagy initiation4 to be responsible for altered autophagy flux during VSMC calcification. In vivo pharmacologic and genetic activation of autophagy using chromatin modulator GSK343 and Becn1F121A knock-in mice, respectively, inhibited vascular calcification and improved survival rates in mouse models of spontaneous large (Mgp-/-) and small (Abcc6-/-) artery calcification. Taken together, these data enhance our mechanistic understanding of vascular calcification by specifically implicating impairment in the initiation of the autophagy pathway and provide important insights for a broad range of cardiovascular diseases involving VSMC phenotype switch.

Reflection seismic data, although sparsely distributed due to the high cost of acquisition, is the only type of data that can provide high-resolution images of the crust to reveal deep subsurface structures and the architectural complexity that may vector attention to minerally prospective regions. However, these datasets are not commonly considered in integrated geophysical inversion approaches due to computationally expensive forward modeling and inversion. Common inversion techniques on reflection seismic images are mostly utilized and developed for basin studies and have very limited application for hard-rock studies. Post-stack acoustic impedance inversions, for example, rely a lot on extracted petrophysical information along drilling borehole for depth correction purposes which are not necessarily available. Furthermore, the available techniques do not allow simple, automatic integration of seismic inversion with other geophysical datasets. We introduce a new methodology that allows the utilization of the seismic images within the gravity inversion technique with the purpose of 3D boundary parametrization of the subsurface. The proposed workflow is a novel approach for incorporating seismic images into the integrated inversion techniques which relies on the image-ray method for depth-to-time domain conversion of seismic datasets. This algorithm uses a convolutional neural network to iterate over seismic images in time and depth domains. This iterative process is functional to compensate for the low depth resolution of the gravity datasets. We use a generalized level-set technique for gravity inversion to link the interfaces of the units with the depth-converted seismic images. The algorithm has been tested on realistic synthetic datasets generated from scenarios corresponding to different deformation histories. The preliminary results of this study suggest that post-stack seismic images can be utilized in integrated geophysical inversion algorithms without the need to run computationally expensive full wave-form inversions.

Antarctica preserves Earth’s largest ice sheet which, in response to climate warming, may lose ice mass and raise sea level by several metres. The ice-sheet bed exerts critical controls on dynamic mass loss through feedbacks between water and heat fluxes, topographic forcing and basal sliding. Here we show that through hydrogeological processes, sedimentary basins amplify critical feedbacks that are known to impact ice-sheet retreat dynamics. We create a high-resolution subglacial bedrock classification for Antarctica by applying a supervised machine learning method to geophysical data, revealing the distribution of sedimentary basins. Sedimentary basins are found in the upper reaches of Antarctica’s most rapidly changing ice streams, including Thwaites and Pine Island Glaciers. Hydro-mechanical numerical modelling reveals that where sedimentary basins exist, water discharge rate scales with the rate of ice unloading and the resulting hydrological instabilities are likely to amplify further retreat and unloading. These results indicate that the presence of a sedimentary bed in the catchment focuses instabilities that increase the vulnerability of the ice streams to rapid retreat and enhanced dynamic mass loss.

Background Endoscopic and microneurosurgical approaches to third ventricular lesions are commonly performed under general anesthesia. Objective To report our initial experience with awake transsulcal parafascicular corridor surgery (TPCS) of the third ventricle and its safety, feasibility, and limitations. Methods A total of 12 cases are reviewed: 6 colloid cysts, 2 central neurocytomas, 1 papillary craniopharyngioma, 1 basal ganglia glioblastoma, 1 thalamic glioblastoma, and 1 ependymal cyst. Lesions were approached using TPCS through the superior frontal sulcus. Pre-, intra-, and postoperative neurocognitive (NC) testing were performed on all patients. Results No cases required conversion to general anesthesia. Awake anesthesia changed intraoperative management in 4/12 cases with intraoperative cognitive changes that required port re-positioning; 3/4 recovered. Average length of stay (LOS) was 6.1 d ± 6.6. Excluding 3 outliers who had preoperative NC impairment, the average LOS was 2.5 d ± 1.2. Average operative time was 3.00 h ± 0.44. Average awake anesthesia time was 5.05 h ± 0.54. There were no mortalities. Conclusion This report demonstrated the feasibility and safety of awake third ventricular surgery, and was not limited by pathology, size, or vascularity. The most significant factor impacting LOS was preoperative NC deficit. The most significant risk factor predicting a permanent NC deficit was preoperative 2/3 domain impairment combined with radiologic evidence of invasion of limbic structures - defined as a "NC resilience/reserve" in our surgical algorithm. Larger efficacy studies will be required to demonstrate the validity of the algorithm and impact on long-term cognitive outcomes, as well as generalizability of awake TPCS for third ventricular surgery.

One of the main tasks in 3D geological modelling is the boundary parametrization of the subsurface from geological observations and geophysical inversions. Several approaches have been developed for geometric inversion and joint inversion of geophysical datasets. However, the robust, quantitative integration of models and datasets with different spatial coverage, resolution, and levels of sparsity remains challenging. One promising approach for recovering the boundary of the geological units is the utilization of a level-set inversion method with potential field data. We focus on constraining 3D geometric gravity inversion with sparse lower-uncertainty information from a 2D seismic section. We use a level-set approach to recover the geometry of geological bodies using two synthetic examples and data from the geologically complex Yamarna terrane (Yilgarn craton, Western Australia). In this study, a 2D seismic section has been used for constraining the location of rock unit boundaries being solved during the 3D gravity geometric inversion. The proposed work is the first we know of that automates the process of adding spatially distributed constraints to the 3D level-set inversion. In many hard-rock geoscientific investigations, seismic data is sparse and our results indicate that unit boundaries from gravity inversion can be much better constrained with seismic information even though they are sparsely distributed within the model. Thus, we conclude that it has the potential to bring the state of the art a step further towards building a 3D geological model incorporating several sources of information in similar regions of investigation.

Exploration and mining companies rely on geological drill core logs to target and obtain initial information on geology of the area to build models for prospectivity mapping or mine planning. A huge amount of legacy drilling data is available in geological survey but cannot be used directly as it is compiled and recorded in an unstructured textural form and using different formats depending on the database structure, company, logging geologist, investigation method, investigated materials and/or drilling campaign. It is subjective and plagued with uncertainty as it is likely to have been conducted by tens to hundreds geologists, all of whom would have their own personal biases. However, this is valuable information that adds value to geoscientific data for research and exploration, specifically in efficiently targeting sustainable new discoveries and providing better shallow subsurface constraints for 3D geological models. dh2loop (https://github.com/Loop3D/dh2loop) is an open-source python library that provides the functionality to extract and standardize geologic drill hole data and export it into readily importable interval tables (collar, survey, lithology). In this contribution, we extract, process and classify lithological logs from the Geological Survey of Western Australia Mineral Exploration Reports Database in the Yalgoo-Singleton Greenstone Belt (YSGB) region. For this study case, the extraction rate for collar, survey and lithology data is respectively 93 %, 865 and 34 %. It also addresses the subjective nature and variability of nomenclature of lithological descriptions within and across different drilling campaigns by using thesauri and fuzzy string matching. 86% of the extracted lithology data is successfully matched to lithologies in the thesauri. Since this process can be tedious, we attempted to test the string matching with the comments, which resulted to a matching rate of 16 % (7,870 successfully matched records out of 47,823 records). The standardized lithological data is then classified into multi-level groupings that can be used to systematically upscale and downscale drill hole data inputs for multiscale 3D geological modelling. dh2loop formats legacy data bridging the gap between utilization and maximization of legacy drill hole data and drill hole analysis functionalities available in existing python libraries (lasio, welly, striplog).

We present two Python libraries (map2loop and map2model) which combine the observations available in digital geological maps with conceptual information, including assumptions regarding the subsurface extent of faults and plutons to provide sufficient constraints to build a reasonable 3D geological model. At a regional scale, the best predictor for the 3D geology of the near-subsurface is often the information contained in a geological map. This remains true even after recognising that a map is also a model, with all the potential for hidden biases that this model status implies. One challenge we face is the difficulty in reproducibly preparing input data for 3D geological models. The information stored in a map falls into three categories of geometric data: positional data such as the position of faults, intrusive and stratigraphic contacts; gradient data, such as the dips of contacts or faults and topological data, such as the age relationships of faults and stratigraphic units, or their adjacency relationships. This work is being conducted within the Loop Consortium, in which algorithms are being developed that allow automatic deconstruction of a geological map to recover the necessary positional, gradient and topological data as inputs to different 3D geological modelling codes. This automation provides significant advantages: it reduces the time to first prototype models; it clearly separates the primary data from subsets produced from filtering via data reduction and conceptual constraints; and provides a homogenous pathway to sensitivity analysis, uncertainty quantification and Value of Information studies. We use the example of the re-folded and faulted Hamersley Basin in Western Australia to demonstrate a complete workflow from data extraction to 3D modelling using two different Open Source 3D modelling engines: GemPy and LoopStructural.

Karatungk Mine is the second-largest Cu-Ni sulfide mine in China. However, the detailed structure beneath the mine remains unclear. Using continuous waveforms recorded by a dense temporary seismic array, here we apply ambient noise tomography to study the shallow crustal structure of Karatungk Mine down to ~1.3 km depth. We obtain surface-wave dispersions at 0.1&ndash, 1.5 s by calculating cross-correlation functions, which are inverted for 3D shear-wave structure at the top-most (0&ndash, 1.3 km) crust by a joint inversion of group and phase dispersions. Our results show that low-velocity zones beneath Y1 ore-hosting intrusion (hereafter called Y1) at 0&ndash, 0.5 km depth and northwest of the Y2 ore-hosting intrusion (hereafter called Y2) at 0&ndash, 0.6 km depth are consistent with highly mineralized areas. A relatively high-velocity zone is connected with a weakly mineralized area located to the southeast of Y2 and Y3 (hereafter called Y3) ore-hosting intrusions. Two high-velocity zones, distributed at 0.7&ndash, 1.3 km depth in the northernmost and southernmost parts of the study area respectively, are interpreted to be igneous rocks related to early magma intrusion. Furthermore, the low-velocity zone at 0.7&ndash, 1.3 km depth in the middle of the study area may be related to: a possible channel related to initial magma transport, mine strata or a potentially mineralized area. This study demonstrates a new application of dense-array ambient noise tomography to a mining area that may guide future studies of mineralized regions.

We introduce a workflow integrating geological modelling uncertainty information to constrain gravity inversions. We test and apply this approach to the Yerrida Basin (Western Australia), where we focus on prospective greenstone belts beneath sedimentary cover. Geological uncertainty information is extracted from the results of a probabilistic geological modelling process using geological field data and their inferred accuracy as inputs. The uncertainty information is utilized to locally adjust the weights of a minimum-structure gradient-based regularization function constraining geophysical inversion. Our results demonstrate that this technique allows geophysical inversion to update the model preferentially in geologically less certain areas. It also indicates that inverted models are consistent with both the probabilistic geological model and geophysical data of the area, reducing interpretation uncertainty. The interpretation of inverted models reveals that the recovered greenstone belts may be shallower and thinner than previously thought.

Combining two or more geophysical datasets with different resolutions and characteristics is now a common practice to recover one or more physical properties. Building 3D geological models for mineral exploration targeting is often an expensive task even for inversion of a single dataset, because of extremely complicated structures with small scale targets. In this context, seismic methods, among all other traditional techniques in mineral exploration, are receiving increasing attention due to their higher resolution in depth. With more limited spatial coverage and higher resolution, they are usually used to refine the interpretation of potential field data.As each seismic survey is designed for a particular intention with specific targets and may not be available in all regions of interests, we develop an iterative cooperative inversion algorithm for inverting gravity and seismic travel-time data. This enables the utilization of localized high-resolution seismic data in a larger full 3D volume which is covered by gravity data. Geological information in the form of probabilistic geological modelling is used to extend information away from the high-resolution data and constrain the inversion result. We use these data as the prior model and to derive constraints incorporated into the objective function of gravity inversion. This allows us to obtain information about the probability of the presence of lithologies associated with the formation of mineral systems. To ensure structural consistency between density and velocity we develop a geologically constrained structure-based coupling technique following the same principle as the cross-gradient technique but with a higher degree of freedom in spatial directions. We apply local structure-based constraints conditioned by a geological probability distribution, which is considering direction and magnitude and provide a higher degree of freedom for model variations. An investigation of the proposed methodology and a proof-of-concept using realistic synthetic data are presented. Our results reveal that the methodology has the potential to constrain the gravity inversion results using the limited seismic data.

We introduce a methodology for the integration of results from 1D stochastic magnetotelluric (MT) data inversion into deterministic least-square inversions of gravity measurements. The goal of this study is to provide a technique capable of exploiting complementary information between 1D magnetotelluric data and gravity data to reduce the effect of non-uniqueness existing in both methodologies. Complementarity exists in terms of resolution, the 1D MT being mostly sensitive to vertical changes and gravity data sensitive to lateral property variations, but also in terms of the related petrophysics, where the sensitivity to different physical parameters (electrical conductivity and density) allows to distinguish between different contrasts in lithologies. To this end, we perform a three-step workflow. Stochastic 1D MT inversions are performed first. The results are then fused to create 2D model ensembles. Thirdly, these ensembles are utilised as a source of prior information for gravity inversion. This is achieved by extracting geological information from the ensemble of resistivity model realisations honouring MT data (typically, ensemble comprising several thousands of models) to constrain gravity data inversion. In our investigations, we generate synthetic data using the 3D geological structural framework of the Mansfield area (Victoria, Australia) and subsequently perform stochastic MT inversions using a 1D trans-dimensional Markov chain Monte Carlo sampler. These inversions are designed to account for the uncertainty introduced by the presence of non-1D structures. Following this, the 1D probabilistic ensembles for each site are fused into an ensemble of 2D models which can then be used for further modelling. The fusion method incorporates prior knowledge in terms of spatial lateral continuity and lithological sequencing, to create an image that reflects different scenarios from the ensemble of models from 1D MT inversion. It identifies several domains across the considered area where it is plausible for the different lithologies to occur. This information is then used to constrain gravity inversion using a clustering algorithm by varying the weights assigned to the different lithologies spatially accordingly with the domains defined from MT inversions. Our results reveal that gravity inversion constrained by MT modelling results in this fashion provide models that present a lower model misfit and are geologically closer to the causative model than without MT-derived prior information. This is particularly true in areas poorly constrained by gravity data such as the basement. Importantly, in this example, the basement is better imaged by the combination of both gravity and MT data than by the separate techniques. The same applies, to a lesser extent, to dipping geological structures closer to surface. In the case of the Mansfield area, the synthetic modelling investigation we performed shows the potential of the workflow introduced here and that it can be confidently applied to real world data.

Most currently constructed 3D geological models are to a first order the result of transformations of data with different dimensionality into 3D: • 0D (e.g. outcrop data, at the regional scale), • 1D (e.g. drill hole data, at the mine scale), • 2D data (e.g. satellite data, at the regional scale) or • 3D data (e.g. seismic data, when high resolution 3D geophysical data are available, such as in basins), • 4D models (3D evolutions with time). The datasets used to project between dimensions vary according to the scenario, however they generally consist of a mixture of 0D observations and local temporal or spatial relationships (their topology). Modern software systems are able to use a sub-set of these relationships (fault-stratigraphy relationships for example) to build 3D geological models, however the relationships are not typically used as an independent constraint on how much of the 3D model is constrained by observations, and how much is generated by the end user (or the algorithms they use). This study explores the relationships between topological observations in 1, 2 and 3D in order to better understand how these may be used in the future as inputs to a revised 3D modelling workflow. We have investigated both synthetic cases, where we have full control, and natural examples, which permit alternate hypotheses. This approach has potential relevance to mine-scale and regional 3D models where the 3D topologies are poorly defined by the existing data, but 1D and 2D constraints are available.

In this work two plausible tectonic scenarios for the Halls Creek Orogen are examined using a 2D thermo-mechanical-petrological numerical experiment based on I2VIS code. The initial constraints for the model setup are appropriate to the inferred tectonic environment for the protoliths to the Tickalara Metamorphics in an intra-ocean subduction or ocean-continent subduction/collision. These numerical models allowed us to examine a range of conceptual models for the different geodynamic settings for the Halls Creek Orogen through time. With this approach, we determined experiments with specific physical parameters that are compatible with the geology observed in the Halls Creek Orogen. Finding the model most compatible with observed geology can help to reveal geological processes which are not observable without the aid of geodynamic simulation. The results indicate that the geology of the Halls Creek Orogen is best represented by the ensialic marginal basin scenario. A further aspect of the numerical models is the degree to which they reveal magmatic activities which lead to the generation of key lithological units during the tectonic evolution of the Halls Creek Orogen. Development and closure of a marginal basin and the role of collisional magmatism are important parts of tectono-thermal evolution of the Halls Creek Orogen. The numerical models predict magma sources through time, linked to the tectonothermal evolution of the region. Hf-isotopic evolution patterns from the region have been used to verify and improve the models as this isotopic system is able to chart the influence of crust and mantle in melts through time. Lu-Hf data from zircon grains indicate a substantial juvenile melt addition in c. 1865-1840 Ma linked to marginal basin development in the Halls Creek Orogen.

Basins along the northern margin of the Yilgarn Craton developed in response to extensional and compressional processes during the Paleoproterozoic. Early extension resulted in the formation of the Yerrida Basin as a large single basin over the northern Yilgarn Craton. Subsequent rifting led to voluminous volcanism in the northern part of the basin, within two depositional centres – the c. 2.03 to 1.96 Ga Bryah and Mooloogool Sub-basins. Cu-Au VMS deposits formed in the Bryah Sub-basin. Yilgarn Craton crust can be mapped using gravity and magnetic data beneath the Yerrida Basin, and Mooloogool Sub-basin. However, the Yerrida Basin can’t be mapped below much of the Bryah Basin, implying the formation of an ocean in this region. The degree of rifting of the Yilgarn Craton, and resulting architecture influenced subsequent basin development, and deformation in the region. For example, in areas where Yilgarn Craton crust can’t be mapped beneath basin sediments deformation is pronounced with the formation of disharmonic folds, refolded folds, and anastomosing shear zones. The southern part of the Yerrida Basin and the Earaheedy Basin formed shallow depositional centres over the Yilgarn Craton, and subsequent deformation in these regions is less intense. Base metal mineralisation in the region can, in part be related to the presence of deep crustal scale structures that initially developed in the Archean, and were re-activated during the Proterozoic. However, the location of c. 1800 Ma orogenic Au mineralization in the Bryah Sub-basin may not have been influenced by localisation of fluid flow around deep crustal-scale faults that formed as 200 Ma earlier, or even as early as the Archean.

Three-dimensional (3D) geological models describe geological information in a 3D space using structural data and topological rules as inputs. They are necessary in any project focused on / studying the properties of the subsurface as they express our understanding of geometries at depth. These models, however, are fraught with uncertainties originating from the inherent flaws of the modelling engines combined with input uncertainty. Because 3D geological models are often used for impactful decision making it is critical that all 3D geological models provide reliable estimates of uncertainty. This research focusses on the effect of various structural input data uncertainty propagation in 3D geological modelling. This aim is achieved using Monte Carlo simulation uncertainty estimation (MCUE), a stochastic method which samples from predefined probability distributions that are estimates of the uncertainty of the original input data set. MCUE is used to produce a series of altered unique data sets. The altered data sets are used as inputs to produce a range of plausible 3D models. These models are then combined into a series of probabilistic models to propagate uncertainty from the input data to a probabilistic model. The present paper presents an innovative way to improve MCUE by using model clustering based on topological signatures and sensitivity analysis.

The integration of geological modelling, petrophysics and geophysics in a single inversion scheme is a complex and powerful strategy for solving challenges faced in geoscientific resource explorati...

Monte Carlo Uncertainty Estimation (MCUE) is an emerging heuristic uncertainty propagation method designed to provide reliable and time/cost efficient estimates of geometrical uncertainties in 3D geological modeling. MCUE is a subtype of Bayesian Monte Carlo method similar to geostatistical simulation. The methods described here rely on disturbance probability distributions that are parameterized to best represent individual input uncertainty. Essentially, disturbance distributions quantify the error about the location (x, y, z) and orientation (dip and azimuth) of observed geological structures. The disturbance distributions are sampled either independently or via a Markov-Chain to produce many plausible alternative datasets. These plausible datasets are then input to a 3D geological modeling engine to build a series of plausible alternative model realizations. Further processing may be applied to the series of plausible models to provide valuable decision aids such as probabilistic models, reliability models, or uncertainty reduction hotspot maps. In this paper, a complete and comprehensive MCUE procedure for common drillhole path and log uncertainty propagation is proposed. Basic concepts of drillhole uncertainty are introduced and are applied to a Markov Chain scheme. Appropriate disturbance distributions for the different parts of the problem and their respective parameterization are discussed. The method proposed is demonstrated on three separate proof of concept case studies of increasing complexity. Results demonstrate that the method is able to propagate path and log uncertainty appropriately. First order interpretation indicates that both path and log uncertainty increase with depth and angle of attack to the geological interfaces. Ignoring drillhole uncertainty was found to be detrimental to the understanding of a modeled area which is most likely due to the over-constraining effect brought by “perfect” drillholes. The third case study (Mansfield) hints that uncertainty is better reduced when drillholes intersect the “triple line” that partitions three distinct lithologies. In cross-sections, triples lines appear as triple points.

Exploration programs involve long, multi-branched decision pathways with many potential outcomes from a single starting point. Critical decisions along this pathway include the choice of the area(s) in which to explore, and the choice to acquire new data sets to assist in exploration. Included in this is a factoring of risks, including the technical risks associated with imperfect data and the value relative to cost of collecting more data. In our experience it is not common practice to explicitly assess and quantify the impact of data on exploration decisions. A better understanding of the opportunity provided by data has the potential to improve the quality and/or ease of decision making. In this study we explore the potential role of data richness mapping as part of a decision making workflow. We outline a method to quantitatively assess data richness following a four level hierarchy, namely presence of data (L1), quality of data (L2) and attributes of data (L3). Measures of these are combined across several data sets to give an overall estimate of data richness (L4). Using this data richness map, along with past exploration records and a prospectivity model, we conduct an illustrative case study for gold exploration in the Bryah Sub-basin (Yerrida Basin) region of Western Australia. The first application is to produce a simple data based classification of regions with different technical risk characteristics. The second application is to combine this with a prospectivity model to better understand exploration potential. The third application uses data richness mapping to understand which data sets are most likely to have an impact on regional exploration. In each case we show how an understanding of data richness can help support exploration decision making.

BACKGROUND A number of vertical prolongations of the superior longitudinal fasciculus, which we refer to as the vertical rami (Vr), arise at the level of the supramarginal gyrus, directed vertically toward the parietal lobe. OBJECTIVE To provide the first published complete description of the white matter tracts (WMT) of the Vr, their relationship to the intraparietal and parieto-occipital sulci (IPS-POS complex), and their importance in neurosurgical approaches to the parietal lobe. METHODS Subcortical dissections of the Vr and WMT of the IPS were performed. Findings were correlated with a virtual dissection using high-resolution diffusion tensor imaging (DTI) tractography data derived from the Human Connectome Project. Example planning of a transparietal, transsulcal operative corridor is demonstrated using an integrated neuronavigation and optical platform. RESULTS The Vr were shown to contain component fibers of the superior longitudinal fasciculus (SLF)-II and SLF-III, with contributions from the middle longitudinal fasciculus merging into the medial bank of the IPS. The anatomic findings correlated well with DTI tractography. The line extending from the lateral extent of the POS to the IPS marks an ideal sulcal entry point that we have termed the IPS-POS Kassam-Monroy (KM) Point, which can be used to permit a safe parafascicular surgical trajectory to the trigone. CONCLUSION The Vr are a newly conceptualized group of tracts merging along the banks of the IPS, mediating connectivity between the parietal lobe and dorsal stream/SLF. We suggest a refined surgical trajectory to the ventricular atrium utilizing the posterior third of the IPS, at or posterior to the IPS-POS Point, in order to mitigate risk to the Vr and its considerable potential for postsurgical morbidity.

Three-dimensional (3-D) geological structural modeling aims to determine geological information in a 3-D space using structural data (foliations and interfaces) and topological rules as inputs. This is necessary in any project in which the properties of the subsurface matters; they express our understanding of geometries in depth. For that reason, 3-D geological models have a wide range of practical applications including but not restricted to civil engineering, the oil and gas industry, the mining industry, and water management. These models, however, are fraught with uncertainties originating from the inherent flaws of the modeling engines (working hypotheses, interpolator's parameterization) and the inherent lack of knowledge in areas where there are no observations combined with input uncertainty (observational, conceptual and technical errors). Because 3-D geological models are often used for impactful decision-making it is critical that all 3-D geological models provide accurate estimates of uncertainty. This paper's focus is set on the effect of structural input data measurement uncertainty propagation in implicit 3-D geological modeling. This aim is achieved using Monte Carlo simulation for uncertainty estimation (MCUE), a stochastic method which samples from predefined disturbance probability distributions that represent the uncertainty of the original input data set. MCUE is used to produce hundreds to thousands of altered unique data sets. The altered data sets are used as inputs to produce a range of plausible 3-D models. The plausible models are then combined into a single probabilistic model as a means to propagate uncertainty from the input data to the final model. In this paper, several improved methods for MCUE are proposed. The methods pertain to distribution selection for input uncertainty, sample analysis and statistical consistency of the sampled distribution. Pole vector sampling is proposed as a more rigorous alternative than dip vector sampling for planar features and the use of a Bayesian approach to disturbance distribution parameterization is suggested. The influence of incorrect disturbance distributions is discussed and propositions are made and evaluated on synthetic and realistic cases to address the sighted issues. The distribution of the errors of the observed data (i.e., scedasticity) is shown to affect the quality of prior distributions for MCUE. Results demonstrate that the proposed workflows improve the reliability of uncertainty estimation and diminish the occurrence of artifacts.

Major structures considered important for controlling mineralisation in the Halls Creek Orogen, east Kimberley are identified via integrated interpretation of geophysical and geological data combined with geodynamic numerical modelling. In the numerical geodynamic models, the second invariant of strain rate ( e II ) is used to investigate the shearing processes that led to the development of major faults or shear zones and assessing their role as lithospheric-scale conduits and pathways for the movement of magmatic and hydrothermal fluids into the upper crust. The influence of these deep structures interpreted from the geodynamic models is evaluated through structural interpretation of geophysical, remotely-sensed and geological data. When compared to the location of Ni and Au mineral deposits the deep-crustal scale structures delineated in the models and compared to those mapped in the region contain a close spatial relationship with mineral deposits. It is apparent that 1st order crustal-scale structures acted as fluid conduits in the deep crust resulting in the formation of Ni-Cu-PGE deposits and are associated with Au mineralisation. However, 2nd and 3rd order structures manifesting in the upper crust as deformation focused mineralising fluids and magma resulting in the formation of gold deposits. Large-scale structures developed early in the genesis of the Halls Creek Orogen, appear to be long-lived and have been reactivated. These form the margins of Kimberley Craton domains and influence the location of Ni-Cu-PGE mineralisation, whereas the lower-order structures acted as structural traps for the subsequent deposition of Au mineralisation.

Extensional episodes in Precambrian orogens are often difficult to decipher because of subsequent orogenesis and intracontinental reworking. Here, we use geochemical and geochronological constraints of a suite of preserved mafic–ultramafic rocks in the Paleoproterozoic Capricorn Orogen of Western Australia to reveal ophiolites, continental ribbons and aborted rifts. The Capricorn Orogen separates the Archean Yilgarn and Pilbara cratons and includes mafic–ultramafic rocks of the fault-bounded Trillbar Complex and Bryah Sub-basin. The Trillbar Complex is situated within a fault wedge between the Yilgarn Craton and a reworked portion of the craton to the north (Yarlarweelor Gneiss Complex), and has been variously interpreted as an obducted ophiolite, oceanic plateau or continental rift-related magmatic suite. In this study, a new U–Pb zircon age of 2069 ± 9 Ma from the Trillbar Complex indicates that it is at least 40 Myr older than the mafic and ultramafic rocks of the Bryah Sub-basin, with which it has previously been linked. The Trillbar Complex is characterised by E-MORB-like signatures, hydrous crystallization and a lack of crustal contamination, and probably formed in a mid-ocean ridge or, alternatively, an oceanic intraplate setting. Conversely, the 2030–1990 Ma mafic and ultramafic rocks in the Bryah Sub-basin show evidence of crustal contamination and are interpreted to have formed in a continental rift setting. Moreover, there is no evidence for boninites in the Bryah Sub-basin and, therefore, no justification for invoking a fore-arc setting. Thus, these pieces of evidence reveal a different tectonic and geodynamic origin for the Trillbar Complex compared to the Bryah Sub-basin rocks. The tectonic setting for the Trillbar Complex requires oceanic crust to have existed between the Yilgarn Craton and the Yarlarweelor Gneiss Complex. However, almost identical Archean histories of these crustal blocks support a proximal origin for the Yarlarweelor Gneiss Complex and a likely origin as a microcontinental ribbon. Farther east (in present-day coordinates), the Bryah Sub-basin and other sedimentary basins record punctuated rifting that never led to the formation of oceanic crust. Therefore, rigorous evaluation of high quality geochemical data coupled to geochronology from mafic–ultramafic rocks is able to provide valuable constraints on extensional episodes, where other evidence has since been erased from the rock record.

The cratonisation of Western Australia during the Proterozoic overlapped with several key events in the evolution of Earth. These include global oxidation events and glaciations, as well as the assembly, accretionary growth, and breakup of the supercontinents Columbia and Rodinia, culminating in the assembly of Gondwana. Globally, Proterozoic mineral systems evolved in response to the coupled evolution of the atmosphere, hydrosphere, biosphere and lithosphere. Consequently, mineral deposits form preferentially in certain times, but they also require a favourable tectonic setting. For Western Australia a distinct plate-margin mineralisation trend is associated with Columbia, whereas an intraplate mineralisation trend is associated with Rodinia and Gondwana, each with associated deposit types. We compare the current Proterozoic record of ore deposits in Western Australia to the estimated likelihood of ore-deposit formation. Overall likelihood is estimated with a simple matrix-based approach that considers two components: The “global secular likelihood” and the “tectonic setting likelihood”. This comparative study shows that at least for the studied ore-deposit types, deposits within Western Australia developed at times, and in tectonic settings compatible with global databases. Nevertheless, several deposit types are either absent or poorly-represented relative to the overall likelihood models. Insufficient exploration may partly explain this, but a genuine lack of deposits is also suggested for some deposit types. This may relate either to systemic inadequacies that inhibited ore-deposit formation, or to poor preservation. The systematic understanding on the record of Western Australia helps to understand mineralisation processes within Western Australia and its past connections in Columbia, Rodinia and Gondwana and aids to identify regions of high exploration potential.

Loop is a new open source 3D geological and geophysical modelling platform in full development.The new platform consists of 4 main work packages: Knowledge Management: use of AI techniques for know...

Using a Rb cell and a wavemeter, with a Doppler-free two-photon transition near 993 nm, we have measured the four hyperfine components (two isotopes, ΔF = 0) of the 5S–6S transition, finding the absolute energies of those transitions to a spectral resolution of 0.002 cm−1 = 60 MHz. We find the (87 minus 85) isotope shift of the 5S–6S transition to be +94(12) MHz. Using our single frequency cw laser with focused intensity up to 104 W cm−2 at the cell, we find no AC Stark or light shift of the lines at 6 MHz spectral resolution. We find no density shift of the lines at 6 MHz spectral resolution, for a range of Rb atom densities from 3 × 1011 to 5 × 1013 atoms/cm3.

With the increasing size and complexity of geoscientific databases, statistical tools and machine learning algorithms are needed to highlight subtle patterns within dense data clouds and reduce human-related bias in geological mapping. This study presents a new tool that maps structural complexity using circular variance and spherical dispersion in two Archean greenstone belts near Dryden and Timmins in the Superior Province, Ontario. Structural complexity quantitatively highlights areas where structures are folded, juxtaposed, and/or parallel. Bedding measurements and autodetected aeromagnetic lineaments are used as inputs to test if structural complexity can refine or add confidence to existing geological interpretations. Linear, low variance trends frequently delineate the location and extent of deformation zones, which likely reflect parallel transposed fabrics in high strain corridors. Areas of high variance spatially correlate with fold traces. Sharp boundaries between high and low variance anomalies are interpreted as faults and/or shear zones that juxtapose structural blocks. The near continuous and representative nature of autodetected magnetic lineaments was effective in capturing structural complexity at a regional scale; however, spherical dispersion captured the highest resolution of structural complexity at local scales ( μ + 1σ). Additionally, the gold grade of large deposits (> 1 Moz) increases with proximity to high variance anomalies. When paired with expert knowledge, these techniques will increase repeatability in future exploration endeavors, making exploration a more rigorous process with increased confidence.

The interaction of structure development and magmatism in rift-settings provides systemic controls on the emplacement of ore deposits both during rifting and subsequently, and a knowledge of these may help to predict better the likely locations of major deposits. The Paleoproterozoic Bryah Rift Basin includes substantial mafic magmatism and deep-crust penetrating structures and possesses syn-rift volcanogenic massive sulphide (VMS) and later gold mineralisation, providing a good opportunity to study interactions between magmatism, structures, and mineralisation. The volcano-sedimentary Bryah Group was deposited in a continental rift developed within the broader Yerrida Basin on the northern margin of the Yilgarn Craton at ca. 2030 Ma. Multi-scale interpretation and forward modelling of gravity and magnetic data were applied to characterise the magmatic and structural patterns of the Bryah Group, enabling a better understanding of its tectono-magmatic development and controls on VMS and gold mineralisation. The interpretation highlights the bounding extensional faults and the inward-deepening structural pattern of the Bryah Rift Basin that reflects the initial rift geometry. Deep-rooted gravity sources show magmatism focused in the southern-central part of the basin, where mafic rocks' thickness can reach more than 10 km. At shallower levels, the rift magmatism extends in three east to east-northeast trending magmatic corridors with an en-echelon arrangement along the rift, oblique to major structures. These magmatic corridors have an intrinsic relationship with the internal structure of the rift. VMS mineralisation associated with mafic magmatism shows a spatial connection with magmatic corridors and major syn-rift faults, whereas VMS mineralisation associated with felsic volcanic rocks is related with off-axis volcanism and regional pre-rift faults. Later orogenic gold mineralisation is also spatially associated with the borders of the magmatic centres and rift faults, despite occurring ~200 Ma later. These associations suggest that primary rift architecture has substantially focused syn-rift VMS mineralisation and also later gold mineralisation, as a consequence of rheological and compositional contrasts.

We have developed a joint geophysical inversion workflow that aims to improve subsurface imaging and decrease uncertainty by integrating petrophysical constraints and geologic data. In this framework, probabilistic geologic modeling is used as a source of information to condition the petrophysical constraints spatially and to derive starting models. The workflow then uses petrophysical measurements to constrain the values retrieved by geophysical joint inversion. The different sources of constraints are integrated into a least-squares framework to capture and integrate information related to geophysical, petrophysical, and geologic data. This allows us to quantify the posterior state of knowledge and to calculate posterior statistical indicators. To test this workflow, using geologic field data, we have generated a set of geologic models, which we used to derive a probabilistic geologic model. In this synthetic case study, we found that the integration of geologic information and petrophysical constraints in geophysical joint inversion could reduce uncertainty and improve imaging. In particular, the use of petrophysical constraints retrieves sharper boundaries and better reproduces the statistics of the observed petrophysical measurements. The integration of probabilistic geologic modeling permits more accurate retrieval of model geometry, and it better constrains the solution while still satisfying the statistics derived from geologic data. The analysis of statistical indicators at each step of the workflow indicates that (1) the inversion methodology is effective when applied to complex geology and (2) the integration of prior information and constraints from geology and petrophysics significantly improves the inversion results while decreasing uncertainty. Finally, the analysis of uncertainty to the integration of the conditioned petrophysical constraints also indicates that, for this example, the best results are obtained for joint inversion using petrophysical constraints spatially conditioned by geologic modeling.

A regional tectonic model is presented for the formation and evolution of Paleoproterozoic basins over the northern Yilgarn Craton, integrating new and published regional geological, geochronological, geochemical and geophysical data. The basins formed as a response to both extensional and compressional processes in the early Paleoproterozoic along the craton margin. Early rifting and basin formation coincided with the Ophthalmia Orogeny, the result of the convergence and accretion of the Archean to Proterozoic Glenburgh Terrane with the Pilbara Craton, and led to the formation of the Yerrida Basin at c. 2180 Ma as a single sub-basin containing the Windplain Group. This led to the eventual development of the Bryah and Mooloogool Sub-basins of the Yerrida Basin at c. 2030 Ma, and voluminous extrusion and intrusion of mafic rocks. The depth and nature of the Bryah Sub-basin suggests formation in response to rifting, with its orientation corresponding to the rift axis. Continued rifting along the northern Yilgarn margin resulted in subduction of the Yilgarn Craton beneath the composite Glenburgh–Pilbara craton. Eventual collision was marked by cessation of volcanism and rift-sediment deposition in the Bryah and Mooloogool Sub-basins, the onset of a pro-foreland basin (Padbury Basin) in the west, and approximately NE–SW rifting further east (the Earaheedy Basin), all at c. 2000 Ma. Banded iron-formation and granular iron-formation (Robinson Range and Frere Formations) was deposited much later (c. 1890 Ma) in a large basin that deepened from east to west, spanning the Earaheedy and Yerrida Basins. The deepest parts of this basin coincide with the Bryah Sub-basin, which was the most rifted portion of the Yilgarn Craton in this region. Deposition in all basins probably ceased with onset of the Capricorn Orogeny at c. 1820 Ma.