Palaeomagnetic and K—Ar age studies of a 6 km-thick Cretaceous section from the Chilean Andes

Summary. Thirty-six palaeomagnetic sampling sites distributed within 6000 m of dominantly andesitic flows and tuffs of Cretaceous age from the La Serena area, Chile confirm the normal polarity bias of the Cretaceous period. Af, thermal and limited chemical demagnetization techniques have been used in testing the stability of the remanent magnetization isolated in samples from these sites. A positive fold test in the Quebrada Marquesa Formation, the second lowest in the stratigraphic pile, confirms that the magnetization isolated is pre-Tertiary in age. Ages calculated by the K–Ar whole rock method however, appear to have been variably up-dated probably due to argon loss caused by Cretaceous–Tertiary intrusives. Thermal and hydrothermal effects of these intrusions have probably reset the magnetization in the youngest formation of the volcanic pile. A composite palaeomagnetic pole calculated from the 30 site poles of the three lower formations (209° E, 81° S, A₉₅= 4½°), is in good agreement with mid to Late Cretaceous poles derived from rock units of the stable platform of South America. The use of Andean–Caribbean palaeomagnetic data however, to resolve small time-dependent polar shifts within the Cretaceous and thus to estimate the time of opening of the south Atlantic is questioned. Many of the Andean–Caribbean Cretaceous poles appear to have been affected by local tectonic rotation.     

Probabilistic Estimates of Number of Undiscovered Deposits and Their Total Tonnages in Permissive Tracts Using Deposit Densities

Empirical evidence indicates that processes affecting number and quantity of resources in geologic settings are very general across deposit types. Sizes of permissive tracts that geologically could contain the deposits are excellent predictors of numbers of deposits. In addition, total ore tonnage of mineral deposits of a particular type in a tract is proportional to the type’s median tonnage in a tract. Regressions using size of permissive tracts and median tonnage allow estimation of number of deposits and of total tonnage of mineralization. These powerful estimators, based on 10 different deposit types from 109 permissive worldwide control tracts, generalize across deposit types. Estimates of number of deposits and of total tonnage of mineral deposits are made by regressing permissive area, and mean (in logs) tons in deposits of the type, against number of deposits and total tonnage of deposits in the tract for the 50th percentile estimates. The regression equations (R ² = 0.91 and 0.95) can be used for all deposit types just by inserting logarithmic values of permissive area in square kilometers, and mean tons in deposits in millions of metric tons. The regression equations provide estimates at the 50th percentile, and other equations are provided for 90% confidence limits for lower estimates and 10% confidence limits for upper estimates of number of deposits and total tonnage. Equations for these percentile estimates along with expected value estimates are presented here along with comparisons with independent expert estimates. Also provided are the equations for correcting for the known well-explored deposits in a tract. These deposit-density models require internally consistent grade and tonnage models and delineations for arriving at unbiased estimates.     

Some Simple Guides to Finding Useful Information in Exploration Geochemical Data

Most regional geochemistry data reflect processes that can produce superfluous bits of noise and, perhaps, information about the mineralization process of interest. There are two end-member approaches to finding patterns in geochemical data—unsupervised learning and supervised learning. In unsupervised learning, data are processed and the geochemist is given the task of interpreting and identifying possible sources of any patterns. In supervised learning, data from known subgroups such as rock type, mineralized and nonmineralized, and types of mineralization are used to train the system which then is given unknown samples to classify into these subgroups.To locate patterns of interest, it is helpful to transform the data and to remove unwanted masking patterns. With trace elements use of a logarithmic transformation is recommended. In many situations, missing censored data can be estimated using multiple regression of other uncensored variables on the variable with censored values.In unsupervised learning, transformed values can be standardized, or normalized, to a Z-score by subtracting the subset's mean and dividing by its standard deviation. Subsets include any source of differences that might be related to processes unrelated to the target sought such as different laboratories, regional alteration, analytical procedures, or rock types. Normalization removes effects of different means and measurement scales as well as facilitates comparison of spatial patterns of elements. These adjustments remove effects of different subgroups and hopefully leave on the map the simple and uncluttered pattern(s) related to the mineralization only.Supervised learning methods, such as discriminant analysis and neural networks, offer the promise of consistent and, in certain situations, unbiased estimates of where mineralization might exist. These methods critically rely on being trained with data that encompasses all populations fairly and that can possibly fall into only the identified populations.     

The Middle Jurassic Camaraca Formation, Arica, Chile: palaeomagnetism, K—Ar age dating and tectonic implications

Summary. Palaeomagnetic and K–Ar whole rock age studies are reported from samples of the Camaraca Formation exposed near Arica (18.6° S, 70.3° W), Chile. The Camaraca Formation is composed of andesites and interbedded marine shales which yield a fauna placing the formation in the Bajocian–Callovian stages of the Jurassic. Our sampling sites span a strati-graphic thickness of 2 km and yield a reversal stratigraphy of: N–R–N. The K–Ar isochron method, applied to least altered samples from the formation, gives a sharply defined age of 157 Myr which is in agreement with the palaeontologically assigned age of the formation. Normal and reversed directions of remanent magnetization, isolated by of and thermal de-magnetization methods, are statistically antiparallel. The pole position, computed from these directions of magnetization, is at 010° E, 70%0 S ( A ₉₅= 6.0°). This pole position, when compared with the well-studied Chon Alice Formation of Argentina, suggests that the sampling region has under-gone a 28°± 28° counter-clockwise rotation about a local vertical axis. The large uncertainty (between 0° and 56°) in this estimate is due to the large scatter in the South American reference data. When compared with African Jurassic palaeopoles, with allowance made for the opening of the South Atlantic, a counter-clockwise rotation of 44°± 14° is indicated.     

A new SPH-based approach to simulation of granular flows using viscous damping and stress regularisation

The smoothed particle hydrodynamics (SPH) method was recently extended to simulate granular materials by the authors and demonstrated to be a powerful continuum numerical method to deal with the post-flow behaviour of granular materials. However, most existing SPH simulations of granular flows suffer from significant stress oscillation during the post-failure process, despite the use of an artificial viscosity to damp out stress fluctuation. In this paper, a new SPH approach combining viscous damping with stress/strain regularisation is proposed for simulations of granular flows. It is shown that the proposed SPH algorithm can improve the overall accuracy of the SPH performance by accurately predicting the smooth stress distribution during the post-failure process. It can also effectively remove the stress oscillation issue in the standard SPH model without having to use the standard SPH artificial viscosity that requires unphysical parameters. The predictions by the proposed SPH approach show very good agreement with experimental and numerical results reported in the literature. This suggests that the proposed method could be considered as a promising continuum alternative for simulations of granular flows.