A Best-Estimate Approach for Determining Self-potential Parameters Related to Simple Geometric Shaped Structures

A new approach is proposed in order to interpret field self-potential (SP) anomalies related to simple geometric-shaped models such as sphere, horizontal cylinder, and vertical cylinder. This approach is mainly based on solving a set of algebraic linear equations, and directed towards the best estimate of the three model parameters, e.g., electric dipole moment, depth, and polarization angle. Its utility and validity are demonstrated through studying and analyzing synthetic self-potential anomalies obtained by using simulated data generated from a known model and a statistical distribution with different random errors components. Being theoretically tested and proven, this approach has been consequently applied on two real field self-potential anomalies taken from Colorado and Turkey. A comparable and acceptable agreement is obtained between the results derived by the new proposed method and those deduced by other interpretation methods. Moreover, the depth obtained by such an approach is found to be very close to that obtained by drilling information.     

基于欧拉反褶积方法估算华北地区重力变化的等效源参数

利用华北地区2009—2014年绝对重力与相对重力多期重复观测资料, 得到不同时空尺度的华北区域重力场动态变化图像。 采用欧拉反褶积方法, 通过对理论模型试算, 获得最优反演参数, 对引起华北地区重力场变化的场源深度和空间分布规律进行了反演计算和分析。 结果表明: 当构造指数为1时, 适合对流动重力场变化数据进行反演。 实际资料的反演结果在2009—2014年间的场源位置集中于河套断裂带。 本文研究方法可以用于重力场反演和以场求源的定量研究。 本工作为流动重力变化信号的反演和解释提供一条新思路, 也为构建地震重力预报指标体系提供了定量依据。     

An Approach for Interpretation of Self-Potential Anomalies due to Simple Geometrical Structures Using Fair Function Minimization

A quantitative interpretation method of self-potential field anomalies has been proposed. The method is designed and implemented for the estimation of center depth, electric dipole moment or magnitude of polarization, polarization angle, and geometric shape factor of a buried body from SP field data, related to simple geometric structures such as cylinders, spheres and sheet-like bodies. The proposed method is based on Fair function minimization and also on stochastic optimization modeling. This new technique was first tested on theoretical synthetic data randomly generated by a chosen statistical distribution from a known model with different random noise components. Such mathematical simulation shows a very close agreement between assumed and estimated model parameters. Being theoretically proven, it has been applied and tested on self-potential field data taken from the United States, Germany, India and Turkey. The agreement between results obtained by the suggested method and those obtained by other previous methods is good and comparable. Moreover, the depth obtained by this method is found to be in high accordance with that obtained from drilling information.     

Estimating Field Source Parameters of Gravity Change in North China Based on the Euler Deconvolution Method

Based on the absolute and relative gravity observations in North China from 2009 to 2014, spatial dynamic variations of the regional gravity field are obtained. We employed the Euler deconvolution method and the theoretical model to get the best estimates of parameters. Gravity field change caused by the depth and distribution in North China is calculated by back analysis. The results show the structural index that equals 1 is suitable for inversion of the gravity variation data. The inversion results indicate that the depths of anomaly field sources are spread over the Hetao fault. The research method of this paper can be used in the quantitative study on the field source and may shed new light on the interpretations of gravity change, and also provide quantitative basis for earthquake prediction index criterions based on the gravity change.     

基于多元线性回归方法的砌体结构加固费用估算模型研究

为建立适用于砌体结构的加固费用快速估算模型,对中国陕西、山西、四川等地砌体结构建筑物的历史加固费用及相关建筑参数进行统计,建立涵盖35栋砌体结构建筑物加固费用估算模型的回归与验证数据库,同时对影响加固费用的各建筑参数作显著性分析,并基于后向消去的多元线性回归方法,利用SPSS统计分析软件对已采集的加固数据进行回归,得到4个费用估算模型;按照相应评价准则分别对各模型进行评价,提出一套最优的砌体结构加固费用快速估算模型,并对该回归模型进行验证分析。回归得到的费用估算模型满足精度要求,具有一定的工程应用价值。     

A New Best-Estimate Methodology for Determining Magnetic Parameters Related to Field Anomalies Produced by Buried Thin Dikes and Horizontal Cylinder-like Structures

A new best estimate methodology is proposed and oriented towards the determination of parameters related to a magnetic field anomaly produced by a simple geometric-shaped model or body such as a thin dike and horizontal cylinder. This approach is mainly based on solving a system of algebraic linear equations for estimating the three model parameters, e.g., the depth to the top (center) of the body (z), the index parameter or the effective magnetization angle (θ) and the amplitude coefficient or the effective magnetization intensity (k). The utility and validity of this method is demonstrated by analyzing two synthetic magnetic anomalies, using simulated data generated from a known model with different random errors components and a known statistical distribution. This approach was also examined and applied to two real field magnetic anomalies from the United States and Brazil. The agreement between the results obtained by the proposed method and those obtained by other interpretation methods is good and comparable. Moreover, the depth obtained by such an approach is found to be in high accordance with that obtained from drilling information. The advantages of such a proposed method over other existing interpretative techniques are clarified, where it can be generalized to be automatically applicable for interpreting other geological structures described by mathematical formulations.     

Identification of Vortex Currents in the Ionosphere and Estimation of Their Parameters Based on Ground Magnetic Data

Geomagnetism and Aeronomy - A system to process data from a 2D network of magnetic stations is proposed for the identification of eddy currents in the ionosphere and the estimation of their...     

A Constrained Nonlinear Inversion Approach to Quantitative Interpretation of Self-potential Anomalies Caused by Cylinders,Spheres and Sheet-like Structures

An interpretative method based on a nonlinearly mathematical optimization concept has been developed in this paper, in order to interpret self-potential anomalies (SP) due to horizontal cylinder, vertical cylinder, sphere and sheet-like structures. This interpretative method comprises three main steps. The first step is to formulate mathematically a nonlinearly constrained minimization problem (NCMP) to describe the geophysical problem related to the studied structure. The second one is to suggest an interior penalty function in order to convert the nonlinearly constrained minimization problem (NCMP) into a nonlinearly unconstrained minimization one (NUMP). The third step is to solve the converted nonlinearly unconstrained minimization problem (NUMP) by the well-known Hooke and Jeeves direct search algorithm in order to estimate the geophysical parameters of the studied structure, i.e., depth, polarization angle, electric dipole moment (magnitude of polarization) and geometric shape factor. The Hooke and Jeeves direct search algorithm is purposely chosen for being robust and its application to SP data allows a rapid convergence towards the optimal estimate of parameters. This interpretative method was first tested on theoretical synthetic models with different random noise, where a very close agreement was obtained between assumed and evaluated parameters.The validity of the proposed interpretative method is also tested on practical field examples taken from Turkey, India and Germany, where available SP data existed and was previously analyzed by different interpretative methods. The agreement between the results obtained by the developed method and those obtained by other published methods is good.Acknowledgment Authors would like to thank Dr. I. Othman Director General of the Atomic Energy Commission of Syria for his interest and continuous encouragement to achieve this work. Special thanks to the reviewers for their constructive suggestions aimed at enhancing the quality of this paper.     

Modeling and Prediction of Monthly Total Ozone Concentrations by Use of an Artificial Neural Network Based on Principal Component Analysis

In the work discussed in this paper we considered total ozone time series over Kolkata (22°34′10.92″N, 88°22′10.92″E), an urban area in eastern India. Using cloud cover, average temperature, and rainfall as the predictors, we developed an artificial neural network, in the form of a multilayer perceptron with sigmoid non-linearity, for prediction of monthly total ozone concentrations from values of the predictors in previous months. We also estimated total ozone from values of the predictors in the same month. Before development of the neural network model we removed multicollinearity by means of principal component analysis. On the basis of the variables extracted by principal component analysis, we developed three artificial neural network models. By rigorous statistical assessment it was found that cloud cover and rainfall can act as good predictors for monthly total ozone when they are considered as the set of input variables for the neural network model constructed in the form of a multilayer perceptron. In general, the artificial neural network has good potential for predicting and estimating monthly total ozone on the basis of the meteorological predictors. It was further observed that during pre-monsoon and winter seasons, the proposed models perform better than during and after the monsoon.     

Biosorption of Cd(II), Ni(II) and Pb(II) from Aqueous Solution by Dried Biomass of Aspergillus niger: Application of Response Surface Methodology to the Optimization of Process Parameters

In this study, the biosorption of Cd(II), Ni(II) and Pb(II) on Aspergillus niger in a batch system was investigated, and optimal condition determined by means of central composite design (CCD) under response surface methodology (RSM). Biomass inactivated by heat and pretreated by alkali solution was used in the determination of optimal conditions. The effect of initial solution pH, biomass dose and initial ion concentration on the removal efficiency of metal ions by A. niger was optimized using a design of experiment (DOE) method. Experimental results indicated that the optimal conditions for biosorption were 5.22 g/L, 89.93 mg/L and 6.01 for biomass dose, initial ion concentration and solution pH, respectively. Enhancement of metal biosorption capacity of the dried biomass by pretreatment with sodium hydroxide was observed. Maximal removal efficiencies for Cd(II), Ni(III) and Pb(II) ions of 98, 80 and 99% were achieved, respectively. The biosorption capacity of A. niger biomass obtained for Cd(II), Ni(II) and Pb(II) ions was 2.2, 1.6 and 4.7 mg/g, respectively. According to these observations the fungal biomass of A. niger is a suitable biosorbent for the removal of heavy metals from aqueous solutions. Multiple response optimization was applied to the experimental data to discover the optimal conditions for a set of responses, simultaneously, by using a desirability function.     

Formation and Evolution of the Anaerobic Zone in the Black Sea from the Most Recent Salinization to the Present State: Retrospective Estimation Based on Mathematical Modeling

It is established that the formation and evolution of the anaerobic zone of the Black Sea are associated with the beginning and development of the most recent salinization of the sea and the formation of pycnocline at intermediate depths; a deterioration of deep-water aeration and the formation of anaerobic conditions in deeper layers; the rate of sulfate-reduction first in the near-bed layer and later, as oxygen is depleted, in the water mass. Formalization of these processes based on refined present-day data on water balance enabled the reproduction of profiles of water salinity and vertical-exchange coefficient for different formation stages of salinity regime in the Black Sea. The vertical distribution of oxygen and hydrogen sulfide is reconstructed, and the rates of oxygen consumption in water column and sulfate reduction in the near-bed layer and at the upper boundary of the anaerobic zone are evaluated in numerical experiments. The obtained data show the transformation of the vertical distribution of oxygen and hydrogen sulfide in the Black Sea from the beginning of its most recent salinization to the present-day state. It is shown that the anaerobic zone rises from 2000 to 200 m within 500–600 years (in the period 3.9–4.5 Ka from the beginning of water exchange through the Bosphorus), and next the upper boundary of the anaerobic zone slowly ascends up to its present-day position (130–180 m). Mathematical modeling was used to evaluate the fluxes of oxygen and hydrogen sulfide at different formation stages of the anaerobic zone in the sea.__________Translated from Vodnye Resursy, Vol. 32, No. 3, 2005, pp. 307–321.Original Russian Text Copyright © 2005 by Leonov, Shaporenko.