A MODEL FOR MEASURING AND QUANTIFYING SPACING OF DISCONTINUITIES IN ROCK MASS
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The space of discontinuities is one of important indexes which explains the distribution of discontinuities and also classifies quality of engineering rock mass.Unlike the traditional definition of discontinuities space,this paper points out that the distribution of discontinuities can be analyzed as long as the spaces of neighboring discontinuities are measured.It presents the four-type methods of classifying discontinuities to built the discontinuities series.It set up an ARIMA model of discontinuities space by means of theory of time series and provided methods of building and checking model.An actual case is studies to show that the ARIMA model is suitable.Keywords:
Classification of discontinuities
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One of the most serious problems in rock engineering applications is the accidental falling of rock blocks that are formed by discontinuity in the rock mass and free surface(s) of engineering structure such as open pit slope, tunnel wall etc.For the stability analysis of in rock mass, there are so many parameters.However, the most important of them which should be taken into account, are the geometrical parameters of discontinuity because the discontinuities are mechanically weak zones and failures occurred on thought surfaces and intersection lines of them and geometrical characteristics are also used as decisive factors in different scales in all stability analysis.Investigation of starting point of possible fails must be a crucial step both in pre-design analysis on existing structures.Because the failures are mostly beginning at these points which are investigated as an analytic solution in this paper.Starting possible locations of failures can be investigated as points on free surfaces of an engineering construction.This study includes derived series of linear equations for the investigation of these points.In addition, Kernel Densities Estimation (KDE) of intersection points is described using for the prediction of failure locations on the visible surfaces of an engineering structure.Derived methodology was sampled on an experimental highway wall and consistent results were shown successfully.
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Detecting discontinuities within seismic data is a constant concern, therefore a series of geometric attributes have been developed and used. Looking into semblance and coherency attributes led to development of new approaches to get insight on detecting discontinuities. In calculating such attributes usually are used discrete values of the amplitudes in the seismic data within a certain time window. Here we approach the calculations in a different manner, by detecting first the discrete values of corresponding phases and using the sums representing one phase for calculations and detecting discontinuities in the seismic data. There were used different calculations as to better view which is more appropriate, also considering the differences in data quality, some being more or less noisy or clear.
Classification of discontinuities
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This research adopts multivariate clustering algorithms to better characterize discontinuity data from oriented boreholes. Conventional analyses are done by grouping the discontinuities into groups or sets based on orientation only, and then trying to generalize the other attributes to these sets. The new approach uses multivariate cluster analysis to group discontinuities (joints) into sets based on multiple attributes, such as orientation, spatial position (spacing) along the borehole and roughness of the discontinuity surface. Rather than considering one variable at a time, a number of variables are treated simultaneously so that not only the variances but also the covariances are considered. In this way interactions between variables are taken into account. Although drift or surface exposure mapping data allows better characterization of discontinuities, borehole data is often more readily available, because of lower costs. In addition, borehole data may be more useful because boreholes can be drilled to the exact location where the ground needs to be characterized and borehole data is usually available earlier in the life cycle of an engineering project. However, most borehole data are underutilized because of lack of analytical tools.
This research develops a new and cost effective tool of analyzing hard rock discontinuities from oriented core borehole data, various analytical and visualization tools, such as three-dimensional stereonet and stereoscopic net, in the format of software package (named as CYL, short for cylinder), for the characterization of rock mass structure from oriented borehole discontinuity data. It provides fast and objective characterization of oriented core discontinuity data using automated multivariate cluster analysis and the “three dimensional stereonet”. The features of the CYL software includes four methods of cluster analysis, incorporation of multiple variables (orientation, spacing and roughness), various visualization modes, and an automated method to split the data set into different Geotechnical Mapping Units (GMU). In addition the software facilitates the selection of optimum drilling angle for boreholes.
Classification of discontinuities
Discontinuity (linguistics)
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Locating small-scale discontinuities is one of the most challenging geophysical tasks; these subtle geological features are significant since they are often associated with subsurface petroleum traps. Subtle faults, fractures, unconformities, reef textures, channel boundaries, thin-bed boundaries and other structural and stratigraphic discontinuities have subtle geological edges which may provide lateral variation in seismic expression. Among the different geophysical techniques available, 3D seismic discontinuity attributes are particularly useful for highlighting discontinuities in the seismic data. Traditional seismic discontinuity attributes are sensitive to noise and are not very appropriate for detecting small-scale discontinuities. Thus, we present a dip-oriented gradient energy entropy (DOGEE) coherence estimation method to detect subtle faults and structural features. The DOGEE coherence estimation method uses the gradient structure tensor (GST) algorithm to obtain local dip information and construct a gradient correlation matrix to calculate gradient energy entropy. The proposed DOGEE coherence estimation method is robust to noise, and also improves the clarity of fault edges. It is effective for small-scale discontinuity characterisation and interpretation.
Classification of discontinuities
Discontinuity (linguistics)
Structure tensor
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P318 FRACTAL ANALYSIS OF FAULT ATTRIBUTES DERIVED FROM SEISMIC DISCONTINUITY DATA Abstract 1 I create a fault attribute by filtering seismic discontinuity data to retain relatively vertical and planar discontinuities while suppressing all other discontinuities. The fault filter sharpens major faults and reveals many minor faults that are obscure on the original discontinuity data. Fault attribute data resemble fracture maps and can be analyzed similarly to estimate the fractal dimension of the faults. Typical fractal dimensions along time slices and vertical sections range from 1.5 to 1.7. Introduction Seismic discontinuity attributes quantify the degree to which neighboring seismic traces vary
Classification of discontinuities
Discontinuity (linguistics)
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SummaryOver the last decade, spectral decomposition techniques have greatly improved seismic interpretation in the exploration of hydrocarbons. Significant efforts have been directed to the development of such methods for tuning hydrocarbon reservoirs, thin beds and channel estimation.Geological and geophysical changes of the earth formation manifest as discontinuities in a seismic trace. These discontinuities also called singularities thus carry most of the information in the trace. Statistical techniques are required to analyze these discontinuities in order to ascertain the variation in the fluid flow.This paper discusses a technique for detecting reservoir homogeneity/heterogeneity based on singularity spectrum attributes. Singularity spectrum determined from multifractal analysis, can globally describe the singularity content of a signal. Obtaining the singularity spectrum of signals also helps in the identification and classification of different state changes in a signal.The developed technique is applied on synthesized seismograms and two attributes of the singularity spectrum namely correlation dimension and width are determined. Results show that by using these attributes the heterogeneity or homogeneity of the reservoir can be evaluated. Such attributes can increase the reliability of suspected hydrocarbon zones; hence unravelling drilling uncertainties and is potentially useful for reservoir fluid flow modelling.
Classification of discontinuities
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Classification of discontinuities
Discontinuity (linguistics)
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Classification of discontinuities
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This paper extended the photography technique to multi-hole occasion and proposed the connection evidences from aspects of orientation and geological characteristics.It also applied the method to foundation investigation of Longjiang Super-major Bridge to test its reliability.It chose three boreholes on the same side of the bridge,on the basis of analyzing and calculating the parameters including spatial position,geological characteristic,orientation and width of the discontinuities.It then contrasted and screened the discontinuities according to connectivity principle,and finally got three discontinuities between two boreholes and two discontinuities among three boreholes.The discontinuities that could be connected own the similar orientations and their spatial positions meet the requirements of lying in the same plane.In addition,the rocks that formed or around the discontinuities own the similar characteristic.The results indicate that it is practicable to apply discontinuity connection method to the engineering.
Classification of discontinuities
Discontinuity (linguistics)
Position (finance)
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