Measurement of the signal to noise ratio in seismic profiling

The measurement of the signal to noise ratio in continuous seismic profiling systems is carried out by means of a small general purpose digital computer equipped with an analog to digital converter. The computer is programmed to compute and compare the power spectrum of a sample of noise to the power spectrum of a sample of noise plus an echo. Power spectra of some twenty to fifty shots are averaged to yield reliable estimates of the signal to noise ratio as a function of frequency. The observed spectra agree well with spectra calculated from signals measured near to an air-gun. This measurement of signal to noise ratio as a function of frequency provides unambiguous information for the adjustment of the necessary band-pass filter thus improving the operation of a continuous seismic profiler.     

Seismic buffer recognition using wavelet-based features and neural classification

One of the first operations in a seismic signal processing system applied to earthquake data is to distinguish between valid and invalid records. Since valid signals are characterized by a combination of their time and frequency properties, wavelets are natural candidates for describing seismic features in a compact way. This paper develops a seismic buffer pattern recognition technique, comprising wavelet-based feature extraction, feature selection based on the mutual information criterion, and neural classification based on feedforward networks. The ability of the wavelet transform to capture discriminating information from seismic data in a small number of features is compared with alternative feature reduction techniques, including statistical moments. Three different variations of the wavelet transform are used to extract features: the discrete wavelet transform, the single wavelet transform and the continuous wavelet transform. The mutual information criterion is employed to select a relatively small set of wavelets from the time–frequency grid. Firstly, it is determined whether wavelets can capture more informative data in an equal number of features compared with other features derived from raw data. Secondly, wavelet-based features are compared with features selected based on prior knowledge of class differences. Thirdly, a technique is developed to optimize wavelet features as part of the neural network training process, by using the wavelet neural network architecture. The automated classification techniques developed in this paper are shown to perform similarly to human operators trained for this function. Wavelet-based techniques are found to be useful, both for preprocessing of the raw data and for extracting features from the data. It is demonstrated that the definition of wavelet features can be optimized using the classification wavelet network architecture.     

Managed water levels and the expansion of emergent vegetation along a lakeshore

Water-level fluctuations may be used to promote the expansion of emergent vegetation along lakeshores. We present the case of the lake Volkerak-Zoommeer in the Netherlands, a fresh-water lake created in 1987 after the enclosure of an estuary. Using an experimental area in which the water level could be manipulated, it was shown that partial summer drawdown of the shoreline created suitable conditions for germination and growth of tall emergent species (in particular Phragmites australis). Plant survival and growth depended on subsequent water-level fluctuations and grazing by waterbirds. Based on the experiment and empirical data, a model was developed to predict the effects of the water-level regime on potential reed bed development. The model was applied for four hydrological scenarios that have been considered for the water-level management of the lake.     

Hydrologic testing during drilling: application of the flowing fluid electrical conductivity (FFEC) logging method to drilling of a deep borehole

Drilling of a deep borehole does not normally allow for hydrologic testing during the drilling period. It is only done when drilling experiences a large loss (or high return) of drilling fluid due to penetration of a large-transmissivity zone. The paper proposes the possibility of conducting flowing fluid electrical conductivity (FFEC) logging during the drilling period, with negligible impact on the drilling schedule, yet providing important information on depth locations of both high- and low-transmissivity zones and their hydraulic properties. The information can be used to guide downhole fluid sampling and post-drilling detailed testing of the borehole. The method has been applied to the drilling of a 2,500-m borehole at Åre, central Sweden, firstly when the drilling reached 1,600 m, and then when the drilling reached the target depth of 2,500 m. Results unveil eight hydraulically active zones from 300 m down to borehole bottom, with depths determined to within the order of a meter. Further, the first set of data allows the estimation of hydraulic transmissivity values of the six hydraulically conductive zones found from 300 to 1,600 m, which are very low and range over one order of magnitude.     

Seismic hazard computations for regions with low earthquake activity — A case study for the Belgium,The Netherlands and NW Germany area

The algorithms to evaluate seismic hazard, used and/or developed by five teams participating in the TERESA project, applied to the low seismicity area Belgium, The Netherlands and NW Germany are compared. The main differences in the results can be explained by the majority criterion of Egozcue et al. (1989), the differences in the upper bound and zonification and, in some cases, by a higher attenuation.     

Deriving rules from activity diary data: A learning algorithm and results of computer experiments

 Activity-based models consider travel as a derived demand from the activities households need to conduct in space and time. Over the last 15 years, computational or rule-based models of activity scheduling have gained increasing interest in time-geography and transportation research. This paper argues that a lack of techniques for deriving rules from empirical data hinders the further development of rule-based systems in this area. To overcome this problem, this paper develops and tests an algorithm for inductively deriving rules from activity-diary data. The decision table formalism is used to exhaustively represent the theoretically possible decision rules that individuals may use in sequencing a given set of activities. Actual activity patterns of individuals are supplied to the system as examples. In an incremental learning process, the system progressively improves on the selection of rules used for reproducing the examples. Computer experiments based on simulated data are performed to fine-tune rule selection and rule value update functions. The results suggest that the system is effective and fairly robust for parameter settings. It is concluded, therefore, that the proposed approach opens up possibilities to derive empirically tested rule-based models of activity scheduling. Follow-up research will be concerned with testing the system on empirical data. Received: 31 January 2001 / Accepted: 13 September 2001     

Chemical Mechanism Development: Laboratory Studies and Model Applications

Within the German Tropospheric Research Programme (TFS) numerous kinetic and mechanistic studies on the tropospheric reaction/degradation of the following reactants were carried out: oxygenated VOC, aromatic VOC, biogenic VOC, short-lived intermediates, such as alkoxy and alkylperoxy radicals.At the conception of the projects these selected groups were classes of VOC or intermediates for which the atmospheric oxidation mechanisms were either poorly characterised or totally unknown. The motivation for these studies was the attainment of significant improvements in our understanding of the atmospheric chemical oxidation processes of these compounds, particularly with respect to their involvement in photooxidant formation in the troposphere. In the present paper the types of experimental investigations performed and the results obtained within the various projects are briefly summarised. The major achievements are highlighted and discussed in terms of their contribution to improving our understanding of the chemical processes controlling photosmog formation in the troposphere.     

Petrologic, isotopic, and radiometric age constraints on the origin and tectonic history of the Malino Metamorphic Complex, NW Sulawesi, Indonesia

The Malino Metamorphic Complex (MMC) is located at the western end of the north arm of Sulawesi. It consists of mica schists and gneisses (derived from proximal turbidite and granitoid protoliths), with intercalations of greenschist, amphibolite, marble, and quartzite, forming an E-W elongated dome-like structure bounded on all sides by faults. The age of the MMC is constrained between Devonian and Early Carboniferous. This Paleozoic age, the presence of Archean and Proterozoic inherited zircons, and the isotopic signature of the mica schists and gneisses indicate that the terrane was derived from the New Guinea-Australian margin of Gondwana. Similarities with basement rocks in the Bird’s Head suggests a common origin. Greenschists forming a discontinuous selvage (metamorphic carapace) around the complex were derived from adjacent autochthonous Paleogene formations. The rocks of the MMC show a Barrovian-type progression from greenschist through epidote-amphibolite to amphibolite facies. P–T estimations suggest a depth of burial of up to 27–30 km. K/Ar and 40Ar/39Ar cooling ages of 23–11 Ma, and a 7 Ma age for unconformably overlying volcanic rocks, indicate that the complex was exhumed during the Miocene. Two tectonic scenarios are considered: 1. the continental fragment docked with Sulawesi during the Mesozoic and was exhumed as a metamorphic core complex during the Miocene; 2. it was subducted beneath the north arm during the late Oligocene and then rapidly returned back to the surface.