Sediment Organic Carbon in Todos Santos Bay, Baja California, Mexico

Sediment grain size and organic carbon (OC) data collected over the past 50 years, together with δ¹³C values of OC in recently collected samples, were analyzed to improve understanding of sediment OC distribution and abundance in Todos Santos Bay. Sediments in the submarine canyon at the mouth of the bay and in quiet-water locations along the shore are fine grained, high in OC, and have generally low δ¹³C values; sediments in high-energy environments are low in OC and have high δ¹³C values. A bivariate isotopic mixing model indicates that none of the sediments contain >50% terrigenous OC (average ~30%), and that the terrigenous OC content of the sediments is a small proportion of the OC content of local soils. Sediment OC composition is apparently controlled by energy-related sorting and deposition, oxidation of much of the original terrigenous OC, and replacement of some terrigenous OC by marine OC.     

A New Algorithm for Wind-Vector Retrieval From Scatterometers

A new efficient algorithm for retrieving wind-vector solutions from scatterometers is developed based on a criterion of minimum normalized standard deviation (NSD) of wind speed derived from backscatter measurements using a geophysical model function (GMF). Its performance has been evaluated through simulations using QSCAT-1 GMF and the QuikSCAT observational geometry. The present algorithm, named the NSD algorithm, is found to be computationally more efficient (two to three times) besides being at par with the maximum-likelihood estimator (MLE) algorithm in terms of retrieval skill, retrieval errors, and distribution of solutions, on the basis of simulations as well as comparison of limited QuikSCAT-data-derived winds with National Centers for Environmental Prediction and European Centre for Medium-Range Weather Forecasts model winds. Simulation results and analysis of sample QuikSCAT data are presented.      

Modeling study of the effects of the coagulation kernel with van der Waals forces and turbulence on the particle size distribution

In this study, variations in the size distributions due to different assumptions for the coagulation kernel are investigated. In order to evaluate how the coagulation kernel influences the form of the particle size distribution and to describe the process of the Brownian coagulation, the Brownian coagulation kernel, including the van der Waals forces, is compared with the most frequently used coagulation coefficients. Retardation should be considered for interparticle interactions for particles larger than 1μm radius. However, for particle sizes larger than 0.1 μm, the Brownian kernel is not dominant, so the retardation effect can be ignored. The inclusion of the van der Waals forces in the Brownian coagulation kernel caused a faster coagulation process in the small particle size range. Taking account of the turbulent coagulation kernel, the turbulent coagulation kernel becomes more important when the turbulent intensity is higher. The turbulent coagulation kernel affects the large particle size range and ignoring the turbulent coagulation kernel will lead to overestimation of particle number concentration in model simulation. The results of this study indicate that the inclusion of van der Waals forces or the turbulent coagulation kernel in the total coagulation kernel impacts on the modeled particle size distributions and total particle number concentration.     

First finds of Late Tithonian and middle-late Albian radiolarian assemblages in volcanogenic-siliceous rocks of the Amur River right lower reaches and their tectonic significance

The lithological-stratigraphic study of volcanogenic-siliceous rocks developed on the left side of the Machtovaya River, a right tributary of the Amur River, yielded the first radiolarian assemblages of the late Late Tithonian, the late Late Tithonian-early Valanginian, and the middle-late Albian age. It is established that the stratigraphic succession of volcanogenic-siliceous rocks in this area is composed of upper Tithonian-Valanginian dark red to red-brown cherts with basalts in the lower part of the section and Albian dark gray clayey cherts, olive-gray siliceous-tuffaceous argillites, and tufaceous siltstones in its upper part. The replacement of cherts by their clayey varieties likely occurred in the Aptian. The composition, structure, and age of these strata and the rocks constituting the Kiselevka-Manoma accretionary complex are different, which indicates their different tectonic origin.     

Geochemistry of magmatic rocks of the Koksharovka alkaline-ultrabasic massif,primorye, and results of trace-element modeling

New geochemical data are presented on the magmatic rocks of the Late Jurassic Koksharovka alkaline-ultrabasic massif, which is associated with deposits of vermiculite, apatite, V-bearing titanomagnetite, and placer isoferroplatinum. The REE geochemistry and strontium, oxygen, and carbon isotopic composition of carbonatites and related ijolites and pyroxenites, together with geological observations, point to the magmatic origin of the Koksharovka carbonatites. The origin of associated magmatic rocks is discussed. Trace element modeling of partial melting of mantle sources was conducted to decipher the genesis of the melts of the Koksharovka carbonatites and host titanite-kaersutite pyroxenites.     

A new concept of pedogenic nodule formation in landscapes of the Russian Far East

The typification of ferromanganese nodules (FMN) formed in subaqueous and subaerial settings and in residual materials, as well as FMN localization in various sediments and soils, is discussed. The genetic diversity of morphologically similar FMN and the transformation of FMN-bearing complexes with changes in landscapes have been established.     

Paleomagnetic studies of the Late Mesozoic deformation stage in the southern Primorye region

The analysis of paleomagnetic data available for the southern Primiorye region revealed that the studied objects were magnetized under regional remagnetization presumably during the Late Mesozoic folding and this magnetization can be interpreted as being synfolding. The interpretation is based on the parameter that characterizes the folding completion degree immediately before regional remagnetization. It is shown that the relaxation of Late Mesozoic horizontal stresses was irregular. The obtained estimates of the degree of folding completion are consistent with the available geological data and Talitskii’s model for tectonic deformations.     

Using Sequential Self-Calibration Method to Identify Conductivity Distribution: Conditioning on Tracer Test data

An iterative inverse method, the sequential self-calibration method, is developed for mapping spatial distribution of a hydraulic conductivity field by conditioning on nonreactive tracer breakthrough curves. A streamline-based, semi-analytical simulator is adopted to simulate solute transport in a heterogeneous aquifer. The simulation is used as the forward modeling step. In this study, the hydraulic conductivity is assumed to be a deterministic or random variable. Within the framework of the streamline-based simulator, the efficient semi-analytical method is used to calculate sensitivity coefficients of the solute concentration with respect to the hydraulic conductivity variation. The calculated sensitivities account for spatial correlations between the solute concentration and parameters. The performance of the inverse method is assessed by two synthetic tracer tests conducted in an aquifer with a distinct spatial pattern of heterogeneity. The study results indicate that the developed iterative inverse method is able to identify and reproduce the large-scale heterogeneity pattern of the aquifer given appropriate observation wells in these synthetic cases.     

Automated Kerogen Classification in Microscope Images of Dispersed Kerogen Preparation

We develop the classification part of a system that analyses transmitted light microscope images of dispersed kerogen preparation. The system automatically extracts kerogen pieces from the image and labels each piece as either inertinite or vitrinite. The image pre-processing analysis consists of background removal, identification of kerogen material, object segmentation, object extraction (individual images of pieces of kerogen) and feature calculation for each object. An expert palynologist was asked to label the objects into categories inertinite and vitrinite, which provided the ground truth for the classification experiment. Ten state-of-the-art classifiers and classifier ensembles were compared: Naïve Bayes, decision tree, nearest neighbour, the logistic classifier, multilayered perceptron (MLP), support vector machines (SVM), AdaBoost, Bagging, LogitBoost and Random Forest. The logistic classifier was singled out as the most accurate classifier, with an accuracy greater than 90. Using a 10 times 10-fold cross-validation provided within the Weka software, we found that the logistic classifier was significantly better than five classifiers (p<0.05) and indistinguishable from the other four classifiers. The initial set of 32 features was subsequently reduced to 6 features without compromising the classification accuracy. A further evaluation of the system alerted us to the possible sensitivity of the classification to the ground truth that might vary from one human expert to another. The analysis also revealed that the logistic classifier made most of the correct classifications with a high certainty.     

The Tau Model for Data Redundancy and Information Combination in Earth Sciences: Theory and Application

Many decision-making processes in the Earth sciences require the combination of multiple data originating from diverse sources. These data are often indirect and uncertain, and their combination would call for a probabilistic approach. These data are also partially redundant with each other or with all others taken jointly. This overlap in information arises due to a variety of reasons—because the data arises from the same geology, because they originate from the same location or the same measurement device, etc. The proposed tau model combines partially redundant data, each taking the form of a prior probability for the event being assessed to occur given that single datum. The parameters of that tau model measure the additional contribution brought by any single datum over that of all previously considered data; they are data sequence-dependent and also data value-dependent. Data redundancy depends on the sequence in which the data is considered and also on the data values themselves. However, for a given sequence, averaging the tau model parameters over all possible data values leads to exact analytical expressions and corresponding approximations and inference avenues. Information on multiple-point connectivity of permeability arrives from core data, well-test data and seismic data which are defined over varying supports with complex redundancy between these information sources. In order to compute these tau weights for determining connectivity, one needs a model of data redundancy, here expressed as a vectorial training image (Ti) constructed using a prior conceptual knowledge of geology and the physics of data measurement. From such a vectorial Ti, the tau weights can be computed exactly. Neglecting data redundancy leads to an over-compounding of individual data information and the possible risk of making extreme decisions.