Aeolian origin and palaeoclimatic implications of the ‘red clay’ (north China) as evidenced by grain‐size distribution

The ‘Red Clay’ is an important deposit underlying the Quaternary loess–palaeosol sequence in the Chinese Loess Plateau, being regarded as an excellent record of palaeoclimate changes in the late Tertiary. Several properties of the ‘Red Clay’ have been measured previously in order to derive climatic information. However, the sedimentary processes involved and the origin of the materials remain controversial. Here we present results of grain‐size analyses of the ‘Red Clay’ from four representative sites in the Chinese Loess Plateau. In particular their grain‐size distribution is compared with that of typical Quaternary aeolian loess–palaeosol, as well as lacustrine and fluvial sediments. It appears from the sedimentological evidence that the major part of the ‘Red Clay’ is of aeolian origin. It is rather similar in some of its properties to the Quaternary loessic palaeosols. The dust forming the ‘Red Clay’ was transported by a wind system that was weaker than that involved in the accretion of the Quaternary loess. Furthermore, the ‘Red Clay’ sediment has been modified by post‐depositional weathering. Copyright © 2001 John Wiley & Sons, Ltd.     

A multiscale method for subsurface inverse modeling: Single-phase transient flow

High-resolution geologic models that incorporate observed state data are expected to effectively enhance the reliability of reservoir performance prediction. One of the major challenges faced is how to solve the large-scale inverse modeling problem, i.e., to infer high-resolution models from the given observations of state variables that are related to the model parameters according to some known physical rules, e.g., the flow and transport partial differential equations. There are typically two difficulties, one is the high-dimensional problem and the other is the inverse problem. A multiscale inverse method is presented in this work to attack these problems with the aid of a gradient-based optimization algorithm. In this method, the model responses (i.e., the simulated state data) can be efficiently computed from the high-resolution model using the multiscale finite-volume method. The mismatch between the observations and the multiscale solutions is then used to define a proper objective function, and the fine-scale sensitivity coefficients (i.e., the derivatives of the objective function with respect to each node’s attribute) are computed by a multiscale adjoint method for subsequent optimization. The difficult high-dimensional optimization problem is reduced to a one-dimensional one using the gradient-based gradual deformation method. A synthetic single-phase transient flow example problem is employed to illustrate the proposed method. Results demonstrate that the multiscale framework presented is not only computationally efficient but also can generate geologically consistent models. By preserving spatial structure for inverse modeling, the method presented overcomes the artifacts introduced by the multiscale simulation and may enhance the prediction ability of the inverse-conditional realizations generated.     

Image transforms for determining fit-for-purpose complexity of geostatistical models in flow modeling

Increased diversity of water or energy resources has led to an increased complexity in models aimed at representing accurately dynamic behavior and geological variability in such systems. In terms of variability of properties at least, simple layered models have mostly been replaced with more complex geostatistical models. The newest trend is to replace covariance-based models with geologically more realistic models such as Boolean, multiple-point, surface-, or process-based models. In this paper, we address the following question: given some design purpose or a set of flow-based decision variables, does adding more complexity increase predictability and ultimately improve decisions based on such models? In this paper, we do not attempt to make any generalizing statements or answer this question with yes/no, but provide some initial ideas on practical workflows to discover the needed complexity. We do treat complexity only in the context of decision making under uncertainty. Two workflows are proposed: complexifying versus simplifying. In these workflows, we attempt to extract, using image transforms, relevant features of the variability between geostatistical realizations that are related to uncertainty in flow dynamics. A simple distance-based calibration between the static variability and dynamic variability provides a means to decide on what the relevant complexity of geostatistical models should be for the given purpose.     

Direct Pattern-Based Simulation of Non-stationary Geostatistical Models

Non-stationary models often capture better spatial variation of real world spatial phenomena than stationary ones. However, the construction of such models can be tedious as it requires modeling both statistical trend and stationary stochastic component. Non-stationary models are an important issue in the recent development of multiple-point geostatistical models. This new modeling paradigm, with its reliance on the training image as the source for spatial statistics or patterns, has had considerable practical appeal. However, the role and construction of the training image in the non-stationary case remains a problematic issue from both a modeling and practical point of view. In this paper, we provide an easy to use, computationally efficient methodology for creating non-stationary multiple-point geostatistical models, for both discrete and continuous variables, based on a distance-based modeling and simulation of patterns. In that regard, the paper builds on pattern-based modeling previously published by the authors, whereby a geostatistical realization is created by laying down patterns as puzzle pieces on the simulation grid, such that the simulated patterns are consistent (in terms of a similarity definition) with any previously simulated ones. In this paper we add the spatial coordinate to the pattern similarity calculation, thereby only borrowing patterns locally from the training image instead of globally. The latter would entail a stationary assumption. Two ways of adding the geographical coordinate are presented, (1) based on a functional that decreases gradually away from the location where the pattern is simulated and (2) based on an automatic segmentation of the training image into stationary regions. Using ample two-dimensional and three-dimensional case studies we study the behavior in terms of spatial and ensemble uncertainty of the generated realizations.     

Characterisation of the magnetic iron phases in Clovis Class rocks in Gusev crater from the MER Spirit Mössbauer spectrometer

Mössbauer backscattering spectra of eight Martian rocks, acquired by the MIMOS II spectrometer of Rover Spirit (MER-A) and containing goethite in addition to other iron minerals, have been selected for in-depth numerical analysis. Where feasible, different temperature windows for a given rock were considered. A novel calibration/folding procedure, exclusively based on the fitted positions of the eight prominent absorption lines in the transmission spectra of the reference target and not relying on the error signal of the MIMOS II spectrometer, has been developed. It is demonstrated that this procedure yields reliable and reasonably accurate values for the adjusted Mössbauer parameters of the respective spectra of the rock targets. These spectra are all composed of magnetically split components arising from hematite, magnetite and goethite phases, in addition to a ferrous and a ferric doublet that can be ascribed to the presence of Fe silicates, possibly glasses. It is argued that the Fe³⁺ doublet has no significant contribution from superparamagnetic Fe-oxide particles. The hematite components reflect the coexistence of antiferromagnetic and weakly ferromagnetic spin states. In general the magnetite content in the selected rocks is low. The goethite subspectra are very broad and asymmetric and need to be described by a model-independent distribution of hyperfine fields. The as-such obtained parameter values indicate an average particle size of the order of 10 nm. For all examined rock spectra, the adjusted parameter values for the various Fe oxides are completely in line with those known for terrestrial (natural or synthetic) species.     

Quantifying geological uncertainty for flow and transport modeling in multi-modal heterogeneous formations

In this work, we address the problem of characterizing the heterogeneity and uncertainty of hydraulic properties for complex geological settings. Hereby, we distinguish between two scales of heterogeneity, namely the hydrofacies structure and the intrafacies variability of the hydraulic properties. We employ multiple-point geostatistics to characterize the hydrofacies architecture. The multiple-point statistics are borrowed from a training image that is designed to reflect the prior geological conceptualization. The intrafacies variability of the hydraulic properties is represented using conventional two-point correlation methods, more precisely, spatial covariance models under a multi-Gaussian spatial law. We address the different levels and sources of uncertainty in characterizing the subsurface heterogeneity, and explore their effect on groundwater flow and transport predictions. Typically, uncertainty is assessed by way of many images, termed realizations, of a fixed statistical model. However, in many cases, sampling from a fixed stochastic model does not adequately represent the space of uncertainty. It neglects the uncertainty related to the selection of the stochastic model and the estimation of its input parameters. We acknowledge the uncertainty inherent in the definition of the prior conceptual model of aquifer architecture and in the estimation of global statistics, anisotropy, and correlation scales. Spatial bootstrap is used to assess the uncertainty of the unknown statistical parameters. As an illustrative example, we employ a synthetic field that represents a fluvial setting consisting of an interconnected network of channel sands embedded within finer-grained floodplain material. For this highly non-stationary setting we quantify the groundwater flow and transport model prediction uncertainty for various levels of hydrogeological uncertainty. Results indicate the importance of accurately describing the facies geometry, especially for transport predictions.     

Study of Al-substituted hematites, prepared from thermal treatment of lepidocrocite

A study of the characteristics of the Morin transition in aluminous hematites, α-(Fe_1?xAl_x)₂O₃, produced from thermally transformed lepidocrocites, is reported. Six compositions with Al contents between 0.2 and 10 at% have been considered. It is argued that these samples present the advantage that they contain smaller amounts of hydroxyl and water as compared to hematites obtained by other preparation methods. The samples were characterised by a variety of conventional techniques, including thermal analyses, X-ray diffraction, FTIR, TEM/EDX, BET surface-area measurements and diffuse reflectance spectroscopy. All results indicate that the Al is structurally incorporated in the hematite lattices. Transmission Mössbauer spectra were recorded at various temperatures between 80?K and room temperature in order to precisely determine the Morin-transition region and the spin structure in both the low-temperature antiferromagnetic and weakly ferromagnetic states. It was found that the Morin-transition temperatures are markedly higher as compared to similar hematites made from aluminous goethites and that a transition phenomenon persists to an Al substitution of up to at least 10 at%. This different behaviour is ascribed to lower concentrations of structural hydroxyl groups in these lepidocrocite-based hematites.     

Mössbauer effect study of the spin structure in natural hematites

Three natural hematites, α-Fe₂O₃, from the region of Elba have been investigated by means of ⁵⁷Fe Mössbauer spectroscopy at variable temperatures between 80 and 400K. The samples were selected on the basis of their different morphology as observed from powder X-ray diffraction and transmission electron microscopy. The mean crystallite diameters (MCD) along [104] are 1000, 280 and 40 nm respectively. Energy-dispersive analyses of X-rays revealed the presence of minor amounts of Si impurities in those two hematites having the largest MCD. All three hematites show the coexistence at low temperatures of antiferromagnetic-like (AF) and weakly-ferromagnetic-like (WF) spin states. The saturation values of the AF and WF magnetic hyperfine fields and quadrupole shifts have been determined, from which conclusions are drawn concerning the spin structure in relation to the crystallinity of the samples. The variations of the hyperfine parameters in the Morin-transition region indicate a gradual reorientation of both AF and WF spins towards the basal plane. As expected, the Morin transition itself is affected by the particle size. The two hematites exhibiting the largest particle dimensions still show an AF contribution for T>270K. It is suggested, and argued that this unusual behaviour is due to the presence of Si⁴⁺, and hence Fe²⁺, in the lattice. The characteristic Mössbauer temperatures and the intrinsic isomer shifts were evaluated from the temperature variation of the observed isomer shifts. Both parameters are not significantly affected by the morphology and are in excellent agreement with data obtained for synthetic hematites.     

The age and palæoenvironmental significance of the Kalahari Sands in western Zimbabwe: a thermoluminescence reconnaissance study

Thermoluminescence (TL) dating, has been applied to 10 samples from the æolian Kalahari Sands of western Zimbabwe using the total bleach (additive dose) and regeneration techniques on coarse-grain quartz separates. The results suggest that the main phases of sand accumulation occurred between 10 and 96 ka. This Upper Pleistocene age is consistent with current opinions and argues against an important period of Holocene æolian activity. The oldest sands were found in the Victoria Falls area where they overlie a ferricrete horizon. Based on our age determinations, we were able to constrain the age of this horizon to between 96±8 and 160±23 ka, which approximately coincides with the Last Integlaciation in the high latitudes. The youngest ages were obtained for sands from the southeastern part of the Hwange dune field but our limited sampling permits assigning only a minimum age of ca 20 ka to the ferricrete horizon observed in this area. Thus, we cannot ascertain if this ferricrete horizon is isochronous with the one at Victoria Falls or if it developed during a younger humid phase.Dune building activity most probably occurred in recurrent cycles of aridity interspersed with periods during which æolian activity was limited or non-existent. Unfortunately, besides the ferricrete horizons, no other stratigraphical evidence of climatic fluctuation has been observed in the study area. However, it is possible that palæosols have been entirely eroded before the subsequent deposition of new sediment, resulting in an incomplete stratigraphical record. The possibilities and limitations of luminescence dating for elucidating phases of climatic fluctuation in such situations are discussed briefly. In addition, we noticed serious discrepancies between the results yielded by the different techniques that were used for determining the dose rate. Hence, further work is needed to validate the accuracy of our dose rate measurements that may cause our TL ages to be about 30% too young.