Mineralogical characterization of a unique material having heavy oxygen isotope anomaly in matrix of the primitive carbonaceous chondrite Acfer 094

We report the mineral compositions and micro-texture of the isotopically anomalous (δ^17,18O_SMOW ∼ +180‰) Fe-S-Ni-O material recently discovered in matrix of the primitive carbonaceous chondrite Acfer 094 [Sakamoto N., Seto Y., Itoh S., Kuramoto K., Fujino K., Nagashima K., Krot A. N. and Yurimoto H. (2007) Oxygen isotope evidence for remnants of the early solar system primordial water. Science317, 231-233]. Synchrotron radiation X-ray diffraction and transmission electron microscopy studies indicate that this material consists of the symplectitically intergrown magnetite (Fe₃O₄) and pentlandite (Fe_5.7Ni_3.3S₈) with magnetite/pentlandite volume ratio of ∼2.3. Magnetite forms column-shaped grains (10-30 nm in diameter and 100-200 nm in length); pentlandite occurs as worm-shaped grains or aggregates of grains 100-300 nm in size between magnetite crystals. Although both the X-ray diffraction and electron energy loss spectra support identification of iron oxide as magnetite, the electron diffraction patterns show that magnetite has a weak 3-fold superstructure, possibly due to ordering of vacancies. We infer that the isotopically anomalous symplectite formed by sulfurization and oxidization of metal grains either in the solar nebula or on an icy planetesimal. The intersite cation distribution of pentlandite suggests that timescale of oxidation was no longer than 1000 years.     

Bayesian and Neural Network Approaches to Estimate Deep Temperature Distribution for Assessing a Supercritical Geothermal System: Evaluation Using a Numerical Model

The temperature distribution at depth is a key variable when assessing the potential of a supercritical geothermal resource as well as a conventional geothermal resource. Data-driven estimation by a machine-learning approach is a promising way to estimate temperature distributions at depth in geothermal fields. In this study, we developed two methodologies—one based on Bayesian estimation and the other on neural networks—to estimate temperature distributions in geothermal fields. These methodologies can be used to supplement existing temperature logs, by estimating temperature distributions in unexplored regions of the subsurface, based on electrical resistivity data, observed geological/mineralogical boundaries, and microseismic observations. We evaluated the accuracy and characteristics of these methodologies using a numerical model of the Kakkonda geothermal field, Japan, where a temperature above 500 °C was observed below a depth of about 3.7 km. When using geological and geophysical knowledge as prior information for the machine learning methods, the results demonstrate that the approaches can provide subsurface temperature estimates that are consistent with the temperature distribution given by the numerical model. Using a numerical model as a benchmark helps to understand the characteristics of the machine learning approaches and may help to identify ways of improving these methods.

     

Alkaline leaching characteristics of biogenic opal in Eocene sediments from the central Arctic Ocean: a case study in the ACEX cores

Accurate knowledge of the extent of biogenic opal preservation in marine sediment cores is important for paleoceanographic reconstructions. The alkaline leaching method is widely employed for %biogenic opal analysis due to its ease and speed. In this study, a revised method for measuring %biogenic opal in sediment from arctic coring expedition samples was suggested. The studied middle Eocene sediments from the central Arctic Ocean presented a problem in insufficiently leaching biogenic opal with a Na₂CO₃ solution. Based on XRD analysis, it was suggested that such an alkaline resistance results from slight diagenesis of biogenic opal. In order to solve this problem, an alkaline leaching method utilizing a 2 M NaOH solution was suggested for the accurate measurement of %biogenic opal in the Eocene sediments from the central Arctic. Furthermore, dissolution rates from lithogenic matter by NaOH solution were measured in order to correct the %biogenic opal values.     

Inverse analysis of an embankment on soft clay by extended Bayesian method

A new type of indirect inverse analysis procedure is proposed to overcome the difficulties the geotechnical inverse analyses are encountering (such as unstability and non-uniqueness of the solutions as well as multicollinearity). These difficulties are eased by combining the objective information (i.e. the observation data) and the subjective information (i.e. the prior information) in an appropriate manner by so-called extended Bayesian method. The method is based on a new view on Bayesian model proposed by Akaike. The problem of model identification in the inverse analysis is also tackled by applying well-known AIC but of the Bayesian version. A case study on an embankment on soft clay is presented to illustrate the effectiveness of the new method. A rather thorough review on the geotechnical inverse analysis is also presented to indicate the necessity of the proposed procedure. An appendix is attached to summarize the statistical background of the new method.     

Parametric infinite element for seepage analysis

A set of mapping functions in the form of convergent series for an infinite element, which is capable to include the infinitely distanced constant head boundary condition from the area of disturbance (e.g. pumping), is proposed based on the asymptotic far-field behaviour of typical seepage flow problems. The derived mapping functions have been successfully used in three-dimensional point symmetric, two-dimensional axi-symmetric and one-dimensional unidirectional flow for the fixed head boundary at infinite distance. The result shows excellent agreement with analytical solution. For the first time, the mapping function of an infinite element is presented in the form of a convergent series. The infinite elements are really capable of reducing the cost and efficiency of conventional finite element analysis. Finally, a figure is also proposed to indicate the required size of the near field to obtain accurate drawdown at specified locations based on some calculations for two-dimensional radial flow case.