A realistic model for point-sources imaged on array detectors: The model and initial results

We have constructed a computer model for simulation of point-sources imaged on two-dimensional detectors. An attempt has been made to ensure that the model produces data that mimic real data taken with 2-D detectors. To be realistic, such simulations must include randomly generated noise of the appropriate type from all sources (e.g. source, background, and detector). The model is generic and accepts input values for parameters such as pixel size, read noise, source magnitude, and sky brightness. Point-source profiles are then generated with noise and detector characteristics added via our model. The synthetic data are output as simple integrations (onedimensional), as radial slices (two-dimensional), and as intensity-contour plots (three-dimensional). Each noise source can be turned on or off so that they can be studied separately as well as in combination to yield a realistic view of an image. This paper presents the basic properties of the model and some examples of how it can be used to simulate the effects of changing image position, image scale, signal strength, noise characteristics, and data reduction procedures.Use of the model has allowed us to confirm and quantify three points: 1) The use of traditionalsize apertures for photometry of faint point-sources adds substantial noise to the measurement which can significantly degrade the quality of the observation; 2) The number of pixels used to estimate the background is important and must be considered when estimating errors; and 3) The CCD equation normally used by the astronomical community consistently overestimates the signal-to-noise obtainable by a measurement while a revised equation, discussed here, provides a better estimator.     

A combined study of macroseismic data and focal mechanisms applied to the West-Bohemian earthquake,Czechoslovakia

The main shock of the West-Bohemian earthquake swarm, Czechoslovakia, (magnitudem=4.5, depthh=10 km) exhibits an irregular areal distribution of macroseismic intensities 6° to 7° MSK-64. Four lobes of the 6° isoseismal are found and the maximum observed intensity is located at a distance of 8 km from the instrumentally determined epicentre. This distribution can be explained by the energy flux of the directS wave generated by a circular source, the hypocentral location and focal mechanism of which are taken from independent instrumental studies. The theoretical intensity, which is assumed to be logarithmically proportional to the integrated squared ground-motion velocity (i.e.,I=const+log v ² (t)dt), fits the observed intensity with an overall root-mean-square error less than 0.5°. It is important that the present intensity data can also be equally well explained by the isotropic source. The fit was attained by means of a horizontally layered model though large fault zones and an extended sedimentary basin suggest a significant lateral heterogeneity of the epicentral region. The results encourage a broader application of the simple modelling technique used.     

The effects of carbon dioxide leakage on fractures, and water quality of potable aquifers during geological sequestration of CO2

Since industrial revolution, the ＂greenhouse effect＂ is one of the most important global environmental issues. Of all the greenhouse gases, CO2 is responsible for about 64% of the enhanced ＂greenhouse effect＂, making it the target for mitigation, so reducing anthropogenic discharge of carbon dioxide attracts more and more attention. Geological sequestration of CO2 in deep saline aquifers is one of the most promising options. But because unknown fractures and faults may exist in the caprock layers which can prevent the leakage of CO2, CO2 will leak upward into upper potable aquifers, and lead to adverse impacts on the shallow potable aquifers. In order to assess the potential effect of CO2 leakage from underground storage reservoirs on fractures and water quality of potable aquifers, this study used the non-isothermal reactive geochemical transport code TOUGHREACT developed by Xu et al to establish a simplified 2-D model of CO2 underground sequestration system, which includes deep saline aquifers, caprock layers, and shallow potable aquifers, and study and analyze the changes of mineral and aqueous components. The simulation results indicated that the minerals of deep saline aquifers and fractures should be mainly composed of aluminosilicate and silicate minerals, which not only enhance the mass of CO2 sequestrated by mineral trapping, but also decrease the porosity and permeability of caprock layers and fractures to prevent and reduce CO2 leakage. The results from deep saline aquifers showed that the mass of carbon dioxide trapped by minerals and solution phases is limited, the rest remained as a supercritical phase, and so once the caprock aquifers have some unknown fractures, the free carbon dioxide phase may leak from CO2 geologic sequestration reservoirs by buoyancy.     

Reservoir description using dynamic parameterisation selection with a combined stochastic and gradient search

There is a correspondence between flow in a reservoir and large scale permeability trends. This correspondence can be derived by constraining reservoir models using observed production data. One of the challenges in deriving the permeability distribution of a field using production data involves determination of the scale of resolution of the permeability. The Adaptive Multiscale Estimation (AME) seeks to overcome the problems related to choosing the resolution of the permeability field by a dynamic parameterisation selection. The standard AME uses a gradient algorithm in solving several optimisation problems with increasing permeability resolution. This paper presents a hybrid algorithm which combines a gradient search and a stochastic algorithm to improve the robustness of the dynamic parameterisation selection. At low dimension, we use the stochastic algorithm to generate several optimised models. We use information from all these produced models to find new optimal refinements, and start out new optimisations with several unequally suggested parameterisations. At higher dimensions we change to a gradient-type optimiser, where the initial solution is chosen from the ensemble of models suggested by the stochastic algorithm. The selection is based on a predefined criterion. We demonstrate the robustness of the hybrid algorithm on sample synthetic cases, which most of them were considered insolvable using the standard AME algorithm.     

Modeling of the classification behavior of the diaphragms used in multi-chamber cement mills

A new approach has been developed for describing the classification that arises at the diaphragm in multi-chamber ball mills. Fourteen industrial scale cement mills have been sampled in this study and after mass balancing, model fits of the equipment were done. Successive mill product predictions for the sampled conditions were achieved, and requirements to build up an optimization capable model are discussed.     

虚拟样机技术在地质工程机械领域的应用研究

基于对国内地质工程机械的研发现状的考虑，根据虚拟样机技术的特点，讨论了在地质工程机械领域实施虚拟样机技术的必要件，并提出了建立地质工程机械虚拟样机的策略。联合PRO／E、ANSYS及ADAMS建立了气动潜孔锤的虚拟样机模型，对气动潜孔锤虚拟样机进行了仿真，阐明了虚拟样机技术在地质工程机械领域的应用前景。     

Optimization of nonconventional wells under uncertainty using statistical proxies

The determination of the optimal type and placement of a nonconventional well in a heterogeneous reservoir represents a challenging optimization problem. This determination is significantly more complicated if uncertainty in the reservoir geology is included in the optimization. In this study, a genetic algorithm is applied to optimize the deployment of nonconventional wells. Geological uncertainty is accounted for by optimizing over multiple reservoir models (realizations) subject to a prescribed risk attitude. To reduce the excessive computational requirements of the base method, a new statistical proxy (which provides fast estimates of the objective function) based on cluster analysis is introduced into the optimization process. This proxy provides an estimate of the cumulative distribution function (CDF) of the scenario performance, which enables the quantification of proxy uncertainty. Knowledge of the proxy-based performance estimate in conjunction with the proxy CDF enables the systematic selection of the most appropriate scenarios for full simulation. Application of the overall method for the optimization of monobore and dual-lateral well placement demonstrates the performance of the hybrid optimization procedure. Specifically, it is shown that by simulating only 10% or 20% of the scenarios (as determined by application of the proxy), optimization results very close to those achieved by simulating all cases are obtained.     

用于湿地气候效应模拟的三江平原下垫面数据获取

三江平原是我国沼泽湿地的重要分布区。在20世纪的后50 a中,三江平原在经过几次大规模的开荒后,其下垫面发生了明显的阶段性变化,湿地大面积消失,农田面积不断增加。为了认识20世纪下半叶不同时期三江平原湿地的气候效应,拟采用第三代区域气候模式(RegCM3)来开展研究。而目前被广泛用于RegCM3的GL-CC数据,所反映的研究区下垫面几乎不存在沼泽湿地,这与事实严重不符,所以必须获取三江平原有沼泽湿地存在的真实的下垫面数据,才能得到可靠的湿地气候效应的模拟结果。分别选择了4期(1954年、1985年、1996年和2000年)有阶段代表性的航片、TM影像数据为主要数据源,利用ERDAS8.7和Arcview3.2等软件,首先得到4期研究区的土地利用数据,然后通过土地利用数据类型向模式数据类型的转换,从4期研究区土地利用数据中提取出了三江平原下垫面的模式数据。经过误差分析,认为获取的4期三江平原下垫面模式数据准确的反映出研究区几个时期的湿地下垫面实况,可以作为三江平原湿地气候效应模拟的基础数据。     

Bayesian Spatial Modelling of Gamma Ray Count Data

Gamma ray logging is a method routinely employed by geophysicists and environmental engineers in site geology evaluations. Modelling of gamma ray data from individual boreholes assists in the local identification of major lithological changes; modelling these data from a network of boreholes assists with lithological mapping and spatial stratigraphic correlation. In this paper we employ Bayesian spatial partition models to analyse gamma ray data spatially. In particular, a spatial partition is defined via a Voronoi tessellation and the mean intensity is assumed constant in each cell of the partition. The number of vertices generating the tessellation as well as the locations of vertices are assumed unknown, and uncertainty about these quantities is described via a hierarchical prior distribution. We describe the advantages of the spatial partition modelling approach in the context of smoothing gamma ray count data and describe an implementation that may be extended to the fitting of a more general model than a constant mean within each cell of the partition. As an illustration of the methodology we consider a data set collected from a network of eight boreholes, which is part of a geophysical study to assist in mapping the lithology of a site. Gamma ray logs are linked with geological information from cores and the spatial analysis of log data assists with predicting the lithology at unsampled locations.