Mineralogical and chemical evolution of the Ernest Henry Fe oxide–Cu–Au ore system, Cloncurry district, northwest Queensland, Australia

The Ernest Henry Cu–Au deposit was formed within a zoned, post-peak metamorphic hydrothermal system that overprinted metamorphosed dacite, andesite and diorite (ca 1740–1660 Ma). The Ernest Henry hydrothermal system was formed by two cycles of sodic and potassic alteration where biotite–magnetite alteration produced in the first cycle formed ca 1514±24 Ma, whereas paragenetically later Na–Ca veining formed ca 1529 +11/−8 Ma. These new U–Pb_titanite age dates support textural evidence for incursion of hydrothermal fluids after the metamorphic peak, and overlap with earlier estimates for the timing of Cu–Au mineralization (ca 1540–1500 Ma). A distal to proximal potassic alteration zone correlates with a large (up to 1.5 km) K–Fe–Mn–Ba enriched alteration zone that overprints earlier sodic alteration. Mass balance analysis indicates that K–Fe–Mn–Ba alteration—largely produced during pre-ore biotite- and magnetite-rich alteration—is associated with K–Rb–Cl–Ba–Fe–Mn and As enrichment and Na, Ca and Sr depletion. The aforementioned chemical exchange almost precisely counterbalances the mass changes associated with regional Na–Ca alteration. This initial transition from sodic to potassic alteration may have been formed during the evolution of a single fluid that evolved via alkali exchange during progressive fluid-rock interaction. Cu–Au ore, dominated by co-precipitated magnetite, minor specular hematite, and chalcopyrite as breccia matrix, forms a pipe-like body at the core of a proximal alteration zone dominated by K-feldspar alteration. Both the core and K-feldspar alteration overprint Na–Ca alteration and biotite–magnetite (K–Fe) alteration. Ore was associated with the concentration of a diverse range of elements (e.g. Cu, Au, Fe, Mo, U, Sb, W, Sn, Bi, Ag, F, REE, K, S, As, Co, Ba and Ca). Mineralization also involved the deposition of significant barite, K(–Ba)–feldspar, calcite, fluorite and complexly zoned pyrite. The complexly zoned pyrite and variable K–(Ba)–feldspar versus barite associations are interpreted to indicate fluctuating sulphur and/or barium supply. Together with the alteration zonation geochemistry and overprinting criteria, these data are interpreted to indicate that Cu–Au mineralization occurred as a result of fluid mixing during dilation and brecciation, in the location of the most intense initial potassic alteration. A link between early alteration (Na–Ca and K–Fe) and the later K-feldspathization and the Cu–Au ore is possible. However, the ore-related enrichments in particular elements (especially Ba, Mn, As, Mo, Ag, U, Sb and Bi) are so extreme compared with earlier alteration that another fluid, possibly magmatic in origin, contributed the diverse element suite geochemically independently of the earlier stages. Structural focussing of successive stages produced the distinctive alteration zoning, providing a basis both for exploration for similar deposits, and for an understanding of ore genesis.     

Planform of convection with strongly temperature-dependent viscosity

Abstract

This paper experimentally investigates the convective planform near critical in a fluid layer whose temperature-dependent viscosity varies from top to bottom by up to a factor of 1500. Convection occurs in three different planforms: rolls, hexagons and squares. The square planform, which appears only for fluids with viscosity variation greater than about 50, replaces the hexagonal convection pattern as the Rayleigh number increases much above critical. The large amplitude of hexagonal convection with strong viscosity variation precludes studying the hexagon-square transition with perturbation methods of the type used to study the hexagon-roll transitions at smaller viscosity variations.     

Generalized LSG models with spatially varying Coriolis parameter

In this paper, we derive and study approximate balance models for nearly geostrophic shallow water flow where the Coriolis parameter is permitted to vary across the domain as long as it remains nondegenerate. This situation includes, for example, the β-plane approximation to the shallow water equations at mid-latitudes. Our approach is based on changing configuration space coordinates in the underlying variational principle in such a way that consistent asymptotics in the transformed Lagrangian leads to a degenerate Lagrangian structure. In this paper, we restrict our attention to first-order models. We show that the resulting models can be formulated in terms of an advected potential vorticity with a nonlinear vorticity inversion relation. We study the associated solvability conditions and identify a subfamily of models for which these conditions are satisfied without additional restrictions on the data. Finally, we provide the link between our framework and the theory of constrained Hamiltonian systems.     

Interactive Visualization to Advance Earthquake Simulation

The geological sciences are challenged to manage and interpret increasing volumes of data as observations and simulations increase in size and complexity. For example, simulations of earthquake-related processes typically generate complex, time-varying data sets in two or more dimensions. To facilitate interpretation and analysis of these data sets, evaluate the underlying models, and to drive future calculations, we have developed methods of interactive visualization with a special focus on using immersive virtual reality (VR) environments to interact with models of Earth’s surface and interior. Virtual mapping tools allow virtual “field studies” in inaccessible regions. Interactive tools allow us to manipulate shapes in order to construct models of geological features for geodynamic models, while feature extraction tools support quantitative measurement of structures that emerge from numerical simulation or field observations, thereby enabling us to improve our interpretation of the dynamical processes that drive earthquakes. VR has traditionally been used primarily as a presentation tool, albeit with active navigation through data. Reaping the full intellectual benefits of immersive VR as a tool for scientific analysis requires building on the method’s strengths, that is, using both 3D perception and interaction with observed or simulated data. This approach also takes advantage of the specialized skills of geological scientists who are trained to interpret, the often limited, geological and geophysical data available from field observations.     

Calculation of the Inverse of the Covariance

In reservoir characterization, the covariance is often used to describe the spatial correlation and variation in rock properties or the uncertainty in rock properties. The inverse of the covariance, on the other hand, is seldom discussed in geostatistics. In this paper, I show that the inverse is required for simulation and estimation of Gaussian random fields, and that it can be identified with the differential operator in regularized inverse theory. Unfortunately, because the covariance matrix for parameters in reservoir models can be extremely large, calculation of the inverse can be a problem. In this paper, I discuss four methods of calculating the inverse of the covariance, two of which are analytical, and two of which are purely numerical. By taking advantage of the assumed stationarity of the covariance, none of the methods require inversion of the full covariance matrix.     

Late Pleistocene outburst floods from Issyk Kul,Kyrgyzstan?

Elevated shorelines and lake sediments surrounding Issyk Kul, the world's second largest mountain lake, record fluctuating lake levels during Quaternary times. Together with bathymetric and geochemical data, these markers document alternating phases of lake closure and external drainage. The uppermost level of lake sediments requires a former damming of the lake's western outlet through the Boam gorge. We test previous hypothesised ice or landslide dam failures by exploring possible links between late Quaternary lake levels and outbursts. We review and recompile the chronology of reported changes in lake site, and offer new ages of abandoned shorelines using ¹⁴C in bivalve and gastropod shells, and plant detritus, as well as sand lenses in delta and river sediments using Infrared Stimulated Luminescence. Our dates are consistent with elevated lake levels between ~45 ka and 22 ka. Cosmogenic ¹⁰Be and ²⁶Al exposure ages of fan terraces containing erratic boulders (>3 m) downstream of the gorge constrain the timing of floods to 20.5–18.5 ka, postdating a highstand of Issyk Kul. A flow‐competence analysis gives a peak discharge of >10⁴ m³ s^–1 for entraining and transporting these boulders. Palaeoflood modelling, however, shows that naturally dammed lakes unconnected to Issyk Kul could have produced such high discharges upon sudden emptying. Hence, although our data are consistent with hypotheses of catastrophic outburst floods, average lake‐level changes of up to 90 mm yr^–1 in the past 150 years were highly variable without any outbursts, so that linking lake‐level drops to catastrophic dam breaks remains ambiguous using sedimentary archives alone. This constraint may readily apply to other Quaternary lakes of that size elsewhere. Nonetheless, our reconstructed Pleistocene floods are among the largest reported worldwide, and motivate further research into the palaeoflood hydrology of Central Asia. Copyright © 2017 John Wiley & Sons, Ltd.     

Amino acid analyses of Antarctic CM2 meteorites using liquid chromatography‐time of flight‐mass spectrometry

Abstract— Amino acid analyses of the Antarctic CM2 chondrites Allan Hills (ALH) 83100 and Lewis Cliff (LEW) 90500 using liquid chromatography‐time of flight‐mass spectrometry (LC‐ToF‐MS) coupled with UV fluorescence detection revealed that these carbonaceous meteorites contain a suite of indigenous amino acids not present in Antarctic ice. Several amino acids were detected in ALH 83100, including glycine, alanine, β‐alanine, γ‐amino‐n‐butyric acid (γ‐ABA), and α‐aminoisobutyric acid (AIB) with concentrations ranging from 250 to 340 parts per billion (ppb). In contrast to ALH 83100, the CM2 meteorites LEW 90500 and Murchison had a much higher total abundance of these amino acids (440–3200 ppb). In addition, ALH 83100 was found to have lower abundances of the α‐dialkyl amino acids AIB and isovaline than LEW 90500 and Murchison. There are three possible explanations for the depleted amino acid content in ALH 83100: 1) amino acid leaching from ALH 83100 during exposure to Antarctic ice meltwater, 2) a higher degree of aqueous alteration on the ALH 83100 parent body, or 3) ALH 83100 originated on a chemically distinct parent body from the other two CM2 meteorites. The high relative abundance of ?‐amino‐n‐caproic acid (EACA) in the ALH 83100 meteorite as well as the Antarctic ice indicates that Nylon‐6 contamination from the Antarctic sample storage bags may have occurred during collection.     

Evaluation of the Reduction in Uncertainty Obtained by Conditioning a 3D Stochastic Channel to Multiwell Pressure Data

A stochastic channel embedded in a background facies is conditioned to data observed at wells. The background facies is a fixed rectangular box. The model parameters consist of geometric parameters that describe the shape, size, and location of the channel, and permeability and porosity in the channel and nonchannel facies. We extend methodology previously developed to condition a stochastic channel to well-test pressure data, and well observations of the channel thickness and the depth of the top of the channel. The main objective of this work is to characterize the reduction in uncertainty in channel model parameters and predicted reservoir performance that can be achieved by conditioning to well-test pressure data at one or more wells. Multiple conditional realizations of the geometric parameters and rock properties are generated to evaluate the uncertainty in model parameters. The ensemble of predictions of reservoir performance generated from the suite of realizations provides a Monte Carlo estimate of the uncertainty in future performance predictions. In addition, we provide some insight on how prior variances, data measurement errors, and sensitivity coefficients interact to determine the reduction in model parameters obtained by conditioning to pressure data and examine the value of active and observation well data in resolving model parameters.