An ichnofabric approach to the depositional interpretation of the intensely burrowed Bateig Limestone, Miocene, SE Spain

The foraminiferal-rich pelagic Bateig Limestone forms several varieties of the important building stones quarried at Bateig Hill in southeastern Spain. Three principal ichnofabrics (Bichordites, mottled-Palaeophycus and mottled-Ophiomorpha) are recognized, which are present in at least two (possibly up to four) repeated successions (cycles). Each succession begins with an erosional event. The Bichordites ichnofabric represents a new type of facies, formed as thin turbidity/grain flow, stratiform units derived from sediment slips off a fault into deep water. Each slipped unit became almost completely bioturbated by infaunal echinoids, colonizing by lateral migration. Because of the thinness of the units, successive colonizations tended to truncate the underlying burrows giving rise to a pseudo-stratification. As the Bichordites ichnofabric accumulated on the fault apron, thus reducing the effective height of the fault scarp, the substrate gradually came under the influence of currents traversing the shelf. This led to a change in hydraulic regime, and to the mottled-Palaeophycus and mottled-Ophiomorpha ichnofabrics in sediment deposited under bed load transport, and associated with laminar and cross-stratified beds and local muddy intervals. Reactivation of the fault triggered erosion and channeling and a return to grain flow sedimentation, and to the Bichordites ichnofabric of the succeeding cycle. The highest unit of the Bateig Limestone is formed entirely of cross-stratified calcarenites with occasional Ophiomorpha (Ophiomorpha-primary lamination ichnofabric) and is similar to many shallow marine facies but they still bear a significant content of pelagic foraminifera. The sedimentary setting bears resemblance with that described for the Pleistocene Monte Torre Paleostrait and the modem Strait of Messina (Italy), where the narrow morphology of the depositional area enhanced tidal currents and allowed for high-energy sandy deposition in relatively deep areas. More data on the Miocene paleogeography of the Bateig area should provide further testing for this hypothesis. The ichnofacies and stacking of the Bateig Limestone differ from the classic Seilacherian model in that they reflect changes in hydraulic process and are associated with faulting and subsidence and changes in sediment supply. Recognition of the unusual ichnofabrics and their relationships provides a clear indication of the overall dynamic setting. (c) 2006 Elsevier B.V. All rights reserved.

A fuzzy multi-criteria decision approach for enhanced auto-tracking of seismic events

The main activity carried out by the geophysicist when interpreting seismic data, in terms of both importance and time spent is tracking (or picking) seismic events. in practice, this activity turns out to be rather challenging, particularly when the targeted event is interrupted by discontinuities such as geological faults or exhibits lateral changes in seismic character. In recent years, several automated schemes, known as auto-trackers, have been developed to assist the interpreter in this tedious and time-consuming task. The automatic tracking tool available in modem interpretation software packages often employs artificial neural networks (ANN's) to identify seismic picks belonging to target events through a pattern recognition process. The ability of ANNs to track horizons across discontinuities largely depends on how reliably data patterns characterise these horizons. While seismic attributes are commonly used to characterise amplitude peaks forming a seismic horizon, some researchers in the field claim that inherent seismic information is lost in the attribute extraction process and advocate instead the use of raw data (amplitude samples). This paper investigates the performance of ANNs using either characterisation methods, and demonstrates how the complementarity of both seismic attributes and raw data can be exploited in conjunction with other geological information in a fuzzy inference system (FIS) to achieve an enhanced auto-tracking performance.

Spectral design and verification of HIRDLS filters and antireflection coatings using an integrated system performance approach

The HIRDLS instrument contains 21 spectral channels spanning a wavelength range from 6 to 18mm. For each of these channels the spectral bandwidth and position are isolated by an interference bandpass filter at 301K placed at an intermediate focal plane of the instrument. A second filter cooled to 65K positioned at the same wavelength but designed with a wider bandwidth is placed directly in front of each cooled detector element to reduce stray radiation from internally reflected in-band signals, and to improve the out-of-band blocking. This paper describes the process of determining the spectral requirements for the two bandpass filters and the antireflection coatings used on the lenses and dewar window of the instrument. This process uses a system throughput performance approach taking the instrument spectral specification as a target. It takes into account the spectral characteristics of the transmissive optical materials, the relative spectral response of the detectors, thermal emission from the instrument, and the predicted atmospheric signal to determine the radiance profile for each channel. Using this design approach an optimal design for the filters can be achieved, minimising the number of layers to improve the in-band transmission and to aid manufacture. The use of this design method also permits the instrument spectral performance to be verified using the measured response from manufactured components. The spectral calculations for an example channel are discussed, together with the spreadsheet calculation method. All the contributions made by the spectrally active components to the resulting instrument channel throughput are identified and presented.

Simple model of adsorption on external surface of carbon nanotubes: a new analytical approach basing on molecular simulation data

Nitrogen adsorption on carbon nanotubes is wide- ly studied because nitrogen adsorption isotherm measurement is a standard method applied for porosity characterization. A further reason is that carbon nanotubes are potential adsorbents for separation of nitrogen from oxygen in air. The study presented here describes the results of GCMC simulations of nitrogen (three site model) adsorption on single and multi walled closed nanotubes. The results obtained are described by a new adsorption isotherm model proposed in this study. The model can be treated as the tube analogue of the GAB isotherm taking into account the lateral adsorbate-adsorbate interactions. We show that the model describes the simulated data satisfactorily. Next this new approach is applied for a description of experimental data measured on different commercially available (and characterized using HRTEM) carbon nanotubes. We show that generally a quite good fit is observed and therefore it is suggested that the observed mechanism of adsorption in the studied materials is mainly determined by adsorption on tubes separated at large distances, so the tubes behave almost independently.

A new adaptive multiple modelling approach for non-linear and non-stationary systems

This paper proposes a novel adaptive multiple modelling algorithm for non-linear and non-stationary systems. This simple modelling paradigm comprises K candidate sub-models which are all linear. With data available in an online fashion, the performance of all candidate sub-models are monitored based on the most recent data window, and M best sub-models are selected from the K candidates. The weight coefficients of the selected sub-model are adapted via the recursive least square (RLS) algorithm, while the coefficients of the remaining sub-models are unchanged. These M model predictions are then optimally combined to produce the multi-model output. We propose to minimise the mean square error based on a recent data window, and apply the sum to one constraint to the combination parameters, leading to a closed-form solution, so that maximal computational efficiency can be achieved. In addition, at each time step, the model prediction is chosen from either the resultant multiple model or the best sub-model, whichever is the best. Simulation results are given in comparison with some typical alternatives, including the linear RLS algorithm and a number of online non-linear approaches, in terms of modelling performance and time consumption.