Fuzzy Decision of Ground Improvement Method

INTRODUCTIONIn recent years, the development of expressway becomesmore and more speedy in China. There is about an increase of2 000 kilometers in the length of expressway every year. Up tol999, the length of the expressway in China totaled 11 605 kil-ometers, which secured it the third place in the world. In vari-ous provinces and city, such as Hunan, Hubei, Jiangxi,Guangdong, and Shanghai etc., there is a large area of soft soilwhich has high compressibility, large quantity of settlem…     

The Geostatistical Information Method of Exploratory Engineering

The geostatistical information method consists in the use of the principleof quantitative evaluation in exploratory engineering research.The principle ofquantitative evaluation is based on the mathematical model of the ore body.Theselection of optimal exploratory scheme and optimal engineering positions hasbeen studied in this paper.     

Structural Earthquake Resistance Design Using Energy Method

A summary of status of researches in the field of structural earthquake resistance design on energy concept is presented in three parts: earthquake input, demands on the structure and supplied capacity of the structure. A new approach is proposed for analysis of the seismic response and damage criteria based on the momentary input energy.     

Fractal Method for Statistical Analysis Geological Data

This paper establishes the phase space in the light of spacial series data,discussesthe fractal structure of geological data in terms of correlated functions and studies thechaos of these data.In addition,it introduces the R/S analysis for time series analysisinto spacial series to calculate the structural fractal dimensions of ranges and standard de-viation for spacial series data,and to establish the fractal dimension matrix and the proce-dures in plotting the fractal dimension anomaly diagram with vector distances of fractal di-mension.At last,it has examples of its application.     

An Improved Dynamic Programming Method for Automatic Stratigraphic Correlation

An improved dynamic programming alogrithm is proposed for reducing the possible mismatching of layer in multi-well correlation. Compared with the standard dynamic programming algorithm, this method restricts the searching range druing layer matching. It can not only avoid possible mismatching between sample and target layer, but also reduce the time spent on layer correlation. The result of applying the imporved methods on the data processed by standard method before indicates that the improved one is more effective and timesaving for the multi-well correlation system than conventional dynamic programming algorithm.     

Application of Multifocusing Method for an Irregular Topography Imaging

INTRODUCTION Astackofrecordedseismicdatabecomesoneof themainstepsinmoderndataprocessingwhenmulti foldacquisitionsystemsaretheleadingmethodof collectingseismicdata.Inthestackprocedure,the crucialoperationistimecorrection.Anaccurateand reliabletraveltimemoveoutcorrectionformulaisnec essaryinordertodostackproperly(Gelchinskyet al.,1999a).Themostfamousmoveoutexpressionis thenormalanddipmoveout(NMO/DMO)designed todescribethetraveltimeofprimaryreflectionsof common midpoint(CMP)data.Beingdes…     

Method of Numerical Modeling for Constitutive Relations of Clay

INTRODUCTIONThe mechanical responses of soils are more com-plicated compared with metals.By comparing thephysical and mechanical properties of the metals withsoils,Lade(1988)found that there are17differentpoints between the metals and soils,which differfrom metals inthree basic mechanical characteristics:pressure sensitivity,dilatancy,and dependence ofstress path.Wang(2004)proposed a principle of theinteraction between plastic volume and shear strains,that is,there are two relatively inde…     

Extended Probability Perturbation Method for Calibrating Stochastic Reservoir Models

Calibrating a stochastic reservoir model on large, fine-grid to hydrodynamic data requires consistent methods to modify the petrophysical properties of the model. Several methods have been developed to address this problem. Recent methods include the Gradual Deformation Method (GDM) and the Probability Perturbation Method (PPM). The GDM has been applied to pixel-based models of continuous and categorical variables, as well as object-based models. Initially, the PPM has been applied to pixel-based models of categorical variables generated by sequential simulation. In addition, the PPM relies on an analytical formula (known as the tau-model) to approximate conditional probabilities. In this paper, an extension of the PPM to any type of probability distributions (discrete, continuous, or mixed) is presented. This extension is still constrained by the approximation using the tau-model. However, when applying the method to white noises, this approximation is no longer necessary. The result is an entirely new and rigorous method for perturbing any type of stochastic models, a modified PPM employed in similar manner to the GDM.     

Waterflood Efficiency Assessment Using Injection–Production Relationship Analysis Method

Mathematical Geosciences - The relationship between injection and production wells is a major component of reservoir evaluation and the foundation for establishing an efficient oilfield development...     

Seismic Behaviour of Excavations Reinforced with Soil–Nailing Method

Geotechnical and Geological Engineering - Soil nailing is an in-situ soil reinforcement technique that is used to enhance the stability of land slopes, retaining walls and excavations. This...     

Reinforcing a Dangerous Rock Mass Using the Flexible Network Method

Because the main failure type of a dangerous rock mass is collapse, the treatment of such a mass should focus on controlling collapse failure. When treating dangerous rock masses, disturbing the mass （e. g. by blasting） needs to be avoided, as this new damage could cause collapse. So the self-bearing capacity of the mountain mass must be used to treat the dangerous rock mass. This article is based on a practical example of the control of a dangerous rock mass at Banyan Mountain, Huangshi, Hubei Province. On the basis of an analysis of damage mechanism and the stability of the dangerous rock mass, a flexible network reinforcement method was designed to prevent the collapse of the rock mass. The deformations of section Ⅱ w of the dangerous rock mass before and after the flexible network reinforcement were calculated using the two-dimensional finite element method. The results show that the maximum deformation reduced by 55 % after the application of the flexible network reinforcement, from 45.99 to 20.75 ram, which demonstrates that the flexible network method is effective, and can provide some scientific basis for the treatment of dangerous rock masses.     

An Intelligent Method for Geochemical Discrimination of Tectonic Settings of Basalt Based on Olivine Composition: GWO-SVM Method and its VerificationEI北大核心CSCD

Geochemical discrimination of tectonic settings of basalts has been an important research direction of geochemistry for decades. Olivine is one of the earliest crystallized minerals of basaltic magma, which records a lot of hidden information of the formation and evolution of the magma. Therefore, basic elements in olivine are used to discriminate three tectonic settings, including the mid-ocean ridge basalt (MORB), ocean island basalt (OIB) and island arc basalt (IAB). However, it is still difficult to accurately discriminate the tectonic settings by using these diagrams. The machine learning algorithm is introduced to solve the aforementioned problem. The classification performance of the machine learning discrimination method largely depends on the rationality of parameter determination. To this end, the paper proposes a coupling intelligent method for geochemical discrimination of tectonic settings using olivine composition of the basalts based on the grey wolf optimizer (GWO)-optimized support vector machine (SVM), or GWO-SVM for short. GWO is used to seek the optimal parameter combination of SVM to form the optimal mapping relationship between basic elements in olivine and basalt tectonic settings, so as to realize the accurate discrimination of MORB, OIB and IAB. In addition, according to the published geochemical data of basalt samples, the discrimination performance of GWO-SVM is evaluated by means of the simulation experiment, hold-out validation and k-fold cross-validation. The evaluation results are represented by the confusion matrix and its derived evaluation indicators. The results show that GWO-SVM can discriminate the tectonic settings of the basalts based on olivine compositions with overall classification accuracy of up to 85%. Thus, in comparison with the traditional discrimination diagram method, the machine learning discrimination method based on multi-algorithm fusion can significantly improve the discrimination accuracy of basalt tectonic settings. © 2020, Science Press. All right reserved.     

Generalized Bootstrap Method for Assessment of?Uncertainty in Semivariogram Inference

The semivariogram and its related function, the covariance, play a central role in classical geostatistics for modeling the average continuity of spatially correlated attributes. Whereas all methods are formulated in terms of the true semivariogram, in practice what can be used are estimated semivariograms and models based on samples. A generalized form of the bootstrap method to properly model spatially correlated data is used to advance knowledge about the reliability of empirical semivariograms and semivariogram models based on a single sample. Among several methods available to generate spatially correlated resamples, we selected a method based on the LU decomposition and used several examples to illustrate the approach. The first one is a synthetic, isotropic, exhaustive sample following a normal distribution, the second example is also a synthetic but following a non-Gaussian random field, and a third empirical sample consists of actual raingauge measurements. Results show wider confidence intervals than those found previously by others with inadequate application of the bootstrap. Also, even for the Gaussian example, distributions for estimated semivariogram values and model parameters are positively skewed. In this sense, bootstrap percentile confidence intervals, which are not centered around the empirical semivariogram and do not require distributional assumptions for its construction, provide an achieved coverage similar to the nominal coverage. The latter cannot be achieved by symmetrical confidence intervals based on the standard error, regardless if the standard error is estimated from a parametric equation or from bootstrap.     

Edge Effect Correction in the S-A Method for Geochemical Anomaly Separation

Anomaly separation using geochemical data often involves operations in the frequency domain, such as filtering and reducing noise/signal ratios. Unfortunately, the abrupt edge truncation of an image along edges and holes (with missing data) often causes frequency distribution distortion in the frequency domain. For example, bright strips are commonly seen in frequency distribution when using a Fourier transform. Such edge effect distortion may affect information extraction results; sometimes severely, depending on the edge abruptness of the image. Traditionally, edge effects are reduced by smoothing the image boundary prior to applying a Fourier transform. Zero-padding is one of the most commonly used smoothing methods. This simple method can reduce the edge effect to some degree but still distorts the image in some cases. Moreover, due to the complexity of geoscience images, which can include irregular shapes and holes with missing data, zero-padding does not always give satisfactory results. This paper proposes the use of decay functions to handle edge effects when extracting information from geoscience images. As an application, this method has been used in a newly developed multifractal method (S-A) for separating geochemical anomalies from background patterns. A geochemical dataset chosen from a mineral district in Nova Scotia, Canada was used to validate the method.     

Theory and Method of Mineral Resource Prediction Based on Synthetic Information

Metallogenic prognosis of synthetic information uses the geological body and the miaeral resource body as a statistical unit to interpret synthetically the information of geology, geophysics, geo-chemistry and remote sensing from the evolution of geology and puts all the information into one entire system by drawing up digitalized interpretation maps of the synthetic information. On such basis, differ-ent grades and types of mineral resource prospecting models and predictive models of synthetic informa-tion can be established. Hence, a new integrated prediction system will be formed of metallogenic prog-nosis (qualitative prediction), mineral resources statistic prediction (determining targets) and mlaeral resources prediction (determining resources amount).     

Environmental Properties of Minerals and Contaminants Purified by the Mineralogical Method

The investigation of the environmental properties of minerals, i.e., environmental mineralogy, is a branch of science dealing with interactions between natural minerals and spheres of the Earth surface as well as a reflection of global change, prevention of ecological destruction, participation in biomineralogy, and remediation of environmental pollution. Pollutant treatment by natural minerals is based on the natural law and reflects natural self-purification functions in the inorganic world, similar to that of the organic world - a biological treatment. A series of case studies related to natural self-purification, which were mostly completed by our group, are discussed in this paper. In natural cryptomelane there is a larger pseudotetragonal tunnel than that formed by [MnO6] octahedral double chains, with an aperture of 0.462-0.466 nm2, filled with K cations. Cryptomelane might be a real naturally-occurring mineral of the active octahedral molecular sieve (OMS-2). CrⅥ-bearing wastewater can be treate     

An Improved Method for Calculating Paleoheat Flow from Vitrinite Reflectance Profiles

lNTRODUCTIONIt is wel1 established that the vitrinite reflectance (R<, ) de-pends on the temperature history that a basin has undergone.In general, Ro is a function of maximum paleotemperature andeffective heating time. Thus, the paleotemperature of sedi-ments and the value of vitrinite ref1ectance are controlled by theflow of heat Q(t) into the basin and by the thermal parametersof the sediments. Therefore, in principle, it is possible to cal-culate the thermal vitrinite reflectance of …     

Decoupling Conditions for Elasto-plastic Consolidation Question Based on Numerical Modeling Method

INTRODUCTION Theconsolidationofsaturatedsoilisanimpor tantsubjectingeomechanics.Biot(1941)proposed thethree dimensionalconsolidationtheory,whichis basedontheprincipleofeffectivestress,continuity conditionsandequilibriumequations.Theremarka blesuccessofthistheoryistheanalysisofthetime dependenteffectandcouplingeffectofsoilandpore water.Thus,thetheoryisaclassictheoryinsatu ratedsoilstatistics.Itwasalmostunfeasibletoperformanalysesof thistheorywithoutthedevelopmentofhigh speed computersandnu…     

Application of Convergence–Confinement Method in Analysis of Shallow Non-circular Tunnels

Stress reduction factor, λ, is a dimensionless coefficient in two-dimensional (2D) analysis based on convergence confinement method (CCM) of tunnel which represents stress relaxation in the tunnel walls at different excavation steps. The aim of this paper is to look into the influencing factors on parameter λ around the tunnel walls using finite difference code in order to improve the accuracy of the CCM. For this purpose, four different ground types with various tunnel radii, depths and cross section shapes are considered. Finally, the 2D analysis using uniform and variable stress reduction factors determined in this paper is compared with the 3D analysis of the tunnel. The results of this study enhance our understanding of the role of geometrical and soil material parameters of tunnel on stress relaxation around tunnel walls. The tunnel depth, soil type and tunnel shape have great influence on λ. Variable stress reduction factor enables the convergence–confinement method to predict the realistic behavior of third dimension of the tunnel and can also be used as the best alternative to 3D models.