地震相分析技术在滨里海盆地AS油田沉积相分析中的应用

针对滨里海AS地区的勘探开发目标层系,运用人工神经网络和主组分分析等技术和方法,对研究区的地震反射波形变化特征及其反映的地质特征进行识别和分类,得到地震相图,应用主要地震相单元中单井相分析成果建立地震相与沉积相的对应关系,将地震相转化为沉积相.该方法弥补了单纯用钻井资料进行沉积相划分的缺陷,提高了沉积相划分精度.     

Magnetic mineral transport and sorting in the swash‐zone: northern Lake Erie,Canada

A combined field and laboratory study in northern Lake Erie has provided new insights into the origin and dynamics of heavy mineral placer deposits on beaches consisting primarily of non‐magnetic sediment. Work was conducted on the cross‐shore and longshore transport of heavy magnetic minerals using magnetic susceptibility and fluorescent paints to trace the movement, in the field, of samples of magnetic (magnetite) and non‐magnetic (quartz and calcite) grains, respectively. Laboratory experiments examined how the burial of small, dense magnetic minerals is affected by the grain size of the non‐magnetic host material, and how grain burial affects magnetic susceptibility measurements at the surface. The field experiments demonstrated that the magnetic mineral tracers were buried rapidly beneath coarser, non‐magnetic grains under low to moderate wave conditions, and subsequently were unable to move in the longshore or cross‐shore directions. The laboratory experiments showed that the magnetic susceptibility rapidly decreased with the rate and depth of burial of the magnetic minerals, and that magnetic grain burial was most effective beneath coarser rather than finer non‐magnetic sand and, for the latter sediments, under less rather than more energetic conditions. The results imply that magnetic mineral concentrations develop in this area through magnetic grain burial under fairly mild conditions, and subsequent settling, exposure and concentration in the upper swash zone during more energetic periods, when the non‐magnetic grains are eroded. It is probably during these erosional periods, when the magnetic minerals are exposed in fairly homogeneous deposits, that longshore and cross‐shore transport takes place.     

Bank Erosion in Fifteen Tributaries in the Glaciated Upper Susquehanna Basin of New York and Pennsylvania

The proportional contributions of cultivated lands and stream banks as sources of fine sediment loads were quantified in 15 rural watersheds in the Glaciated Appalachian Plateau region of the Susquehanna River basin of New York and Pennsylvania. We utilized a relatively simple method of fingerprinting sediment sources by comparing the concentrations of the nuclear bomb-derived radionuclide ¹³⁷ Cs in fluvial sediment samples collected from channel margins with sediment from cultivated fields and stream banks. The proportion of fine sediment from bank erosion ranged from none to 100% in the study tributaries, with a median contribution of 53% across the 15 study streams. In one stream with no evidence of bank sediment, anomalously high ¹³⁷ Cs levels in the samples indicated that the sources were pasture or forest, probably scoured from marshy floodplains upstream of the sampling sites. In the 14 other streams, cultivated lands accounted for an average of 42% of the fine sediment. We discuss sources of eroded bank material and the processes driving stream bank erosion in this glaciated region, and examine the impact of historic mill-dam deposits on bank erosion.     

Image and non-image parameters of atmospheric Cherenkov events: a comparative study of their γ-ray/hadron classification potential in ultrahigh energy regime

In this exploratory simulation study, we compare the event-progenitor classification potential of a variety of measurable parameters of atmospheric Cherenkov pulses which are produced by ultrahigh energy γ-ray and hadron progenitors and are likely to be recorded by the TACTIC (TeV atmospheric Cherenkov telescope with imaging camera) array of atmospheric Cherenkov telescopes. The parameters derived from Cherenkov images include Hillas, fractal and wavelet moments, while those obtained from non-image Cherenkov data consist of pulse profile rise time and base width and the relative ultraviolet to visible light content of the Cherenkov event. It is shown by a neural-net approach that these parameters, when used in suitable combinations, can bring about a proper segregation of the two event types, even with modest sized data samples of progenitor particles.     

Application of transition metal isotope tracers in global change research

High-precision isotope composition determinations using multicollector, magnetic-sector inductively coupled plasma mass spectrometry (MC-ICPMS) have recently revealed that some transition metal isotopes such as those of Mo, Fe, Cu, Zn etc. can be used as biogeochemical tracers in global change research.The Mo isotope system may be useful in paleoredox investigations indicating that δ^97 ^95Mo in seawater may co-vary with changes in the relative proportions of anoxic and oxic sedimentation in the ocean, and that this variation may be recorded in δ^97 ^95Mo of anoxic sediments. The Mo continental flux into the oceans and the global Mo isotope budget can be estimated from δ^97 ^95M0 values. The Fe isotope composition in seawater is an important issue because Fe plays a controlling role in biological productivity in the oceans and its abundance in seawater may have substantial effect on climate changes. Iron isotope fractionations could result from bio- and abio-processes and have about 0.1% variation ( δ^56 ^54Fe), so Fe isotopes considered alone cannot be used to distinguish the products of abiotic and biotic Fe processing in geological records. Cu and Zn isotopes are also used as biogeochemical tracers, but the researches are relatively less. This review mainly focuses on the methods for preparation, purification and determination of new isotope tracer samples, and on isotope applications in marine environmental changes.     

Neural networks and landslide susceptibility: a case study of the urban area of Potenza

For those working in the field of landslide prevention, the estimation of hazard levels and the consequent production of thematic maps are principal objectives. They are achieved through careful analytical studies of the characteristics of landslide prone areas, thus, providing useful information regarding possible future phenomena. Such maps represent a fundamental step in the drawing up of adequate measures of landslide hazard mitigation. However, for a complete estimation of landslide hazard, meant as the degree of probability that a landslide occurs in a given area, within a given space of time, detailed and uniformly distributed data regarding their incidence and causes are required. This information, while obtainable through laborious historical research, is usually partial, incomplete and uneven, and hence, unsatisfactory for zoning on a regional scale. In order to carry this out effectively, the utilization of spatial estimation of the relative levels of landslide hazard in the various areas was considered opportune. These areas were classified according to their levels of proneness to landslide activity without taking recurrence periods into account. Various techniques were developed in order to obtain upheaval numerical estimates. The method used in this study, which was applied in the area of Potenza, is based on techniques derived from artificial intelligence (Artificial Neural Network—ANN). This method requires the definition of appropriate thematic layers, which parameterize the area under study. These are recognized by means of specific analyses in a functional relationship to the event itself. The parameters adopted are: slope gradient, slope aspect, topographical index, topographical shape, elevation, land use and lithology.     

Response of the interaction between groundwater and other components of the environment in Mexico

This article reviews and discusses environmental aspects related to vertical upward and downward groundwater flow. Flow systems are an important tool to understand groundwater functioning as related to the environment, in terms of obtaining indicators of human impact and solving specific questions about a groundwater-environment system that has been influenced by anthropogenic means. This involves two broad processes. First, groundwater changes due to activities of man in the surrounding environment as a result of: (1) alteration of recharge by modification of native vegetation and original soil cover; (2) reduction of groundwater discharge to coastal areas and to inland water bodies producing desiccation of wetlands, lakes and springs; (3) groundwater contamination from sewage looses and uncontrolled waste disposal locations, and (4) up-welling of undesirable water quality induced by extraction. Second, environmental alterations due to changes in the groundwater regime produce: (1) increase in soil erosion through the disappearance of vegetation due to water-table decline, (2) water-table rise due to unplanned artificial recharge resulting from water imports to a catchment, (3) decline in water levels for improper extraction regime, (4) soil subsidence due to extraction mismanagement, and (5) disappearance of phreatofites caused by excessive extraction. Unless further understanding between groundwater and the other components of the environment is sought, the relationship between people and its environment will be subject to some of these effects, potentially endangering adequate human development and sustainable water management.     

An application of artificial intelligence for rainfall-runoff modeling

This study proposes an application of two techniques of artificial intelligence (AI) for rainfall-runoff modeling: the artificial neural networks (ANN) and the evolutionary computation (EC). Two different ANN techniques, the feed forward back propagation (FFBP) and generalized regression neural network (GRNN) methods are compared with one EC method, Gene Expression Programming (GEP) which is a new evolutionary algorithm that evolves computer programs. The daily hydrometeorological data of three rainfall stations and one streamflow station for Juniata River Basin in Pennsylvania state of USA are taken into consideration in the model development. Statistical parameters such as average, standard deviation, coefficient of variation, skewness, minimum and maximum values, as well as criteria such as mean square error (MSE) and determination coefficient (R ²) are used to measure the performance of the models. The results indicate that the proposed genetic programming (GP) formulation performs quite well compared to results obtained by ANNs and is quite practical for use. It is concluded from the results that GEP can be proposed as an alternative to ANN models.     

Case-based system for slope design

A key part of slope design is the review of past examples of slopes in similar ground conditions. This paper details the development of the SlopeSafe computer program which uses case-based reasoning to formalise this process. The program, written in Visual Basic, draws on a case-base of nearly 3000 case histories of successful and failed slopes to give an indication of the likely success of a proposed slope by matching its geometry and ground conditions to the slopes held in the case-base. XML (Extensible Markup Language) has been used to store the data and a specific set of tags has been defined to provide a standard way of storing slope information. The system has been identified by practising engineers as having the potential to be a very useful design tool.