Seokhoon Oh

Geostatistical approach to bayesian inversion of geophysical data: Markov chain Monte Carlo method

This paper presents a practical and objective procedure for a Bayesian inversion of geophysical data. We have applied geostatistical techniques such as kriging and simulation algorithms to acquire a prior model information. Then the Markov chain Monte Carlo (MCMC) method is adopted to infer the characteristics of the marginal distributions of model parameters. Geostatistics which is based upon a variogram model provides a means to analyze and interpret the spatially distributed data. For Bayesian inversion of dipole-dipole resistivity data, we have used the indicator kriging and simulation techniques to generate cumulative density functions from Schlumberger and well logging data for obtaining a prior information by cokriging and simulations from covariogram models. Indicator approaches make it possible to incorporate non-parametric information into the probabilistic density function. We have also adopted the Markov chain Monte Carlo approach, based on Gibbs sampling, to examine the characteristics of a posterior probability density function and marginal distributions of each parameter. The MCMC technique provides a robust result from which information given by the indicator method, that is fundamentally non-parametric, is fully extracted. We have used the a prior information proposed by the geostatistical method as the full conditional distribution for Gibbs sampling. And to implement Gibbs sampler, we have applied the modified Simulated Annealing (SA) algorithm which effectively searched for global model space. This scheme provides a more effective and robust global sampling algorithm as compared to the previous study.

Geostatistical integration of seismic velocity and resistivity data for probabilistic evaluation of rock quality

This study applied a geostatistical approach to integrate various geophysical results for the probabilistic evaluation of rock quality designation (RQD) in regions between boreholes. Two of the geophysical survey results, electrical resistivity and seismic velocity, were transformed into a probabilistic distribution with the directly observed RQD values at the boreholes using an indicator value method. The initial spatial distribution of RQD, inferred from indicator kriging of observations from the boreholes, was improved by support of the geophysical results based on the integration by a permanence ratio. The integration was good enough to produce results that compensated for the defection of each exploration method. Also, the probabilistic feature of the final product of the RQD distribution made it possible to assess a more quantitative rock quality evaluation and better decision making for safety design.

Variation Analysis of Geomagnetic Data Observed Around the Event of Andong Earthquake (May 2, 2009)

Geomagnetic variation around May 2, 2009 when Angdong earthquake broke out was analyzed using the data recorded at the Cheong-yang geomagnetic observatory, KMA. Firstly, we predict the geomagnetic variation by PCA analysis of geomagnetic data, and then compare the predicted value with the observed data to find any significant differences in residuals. Secondly, wavelet semblance technique is applied to compare the time series before and after the earthquake. Some meaningful change is detected in the Z-field. Thirdly, eigen value analysis for the 3 component geomagnetic data is performed. The location of the observatory was too far from the epicenter and the magnitude was too small to find decisive precursory phenomenon. Nevertheless we can detect some significant correlation between the earthquake and the variation of the geomagnetic field. Various signal processing methods applied in this study will give some opportunity to find precursory effects in the future.

Geomagnetic variation and its relation to microearthquakes in the seismically inactive Korean Peninsula

Some microearthquakes that occur in the Korean Peninsula show significant geomagnetic variation when subjected to a specialized principal component analysis, wavelet-based semblance filtering and eigenvalue analysis. In this study, the principal component analysis was used to reconstruct and predict the geomagnetic field based on the past observed magnetic fields, and the reconstructed field was compared with the field observed during the earthquake event. The wavelet-based filtering showed improved results in delineating the earthquake event’s geomagnetic variations from their background field. Finally, the change in the tendency of the eigenvalues was detected by the analysis of three components of the geomagnetic fields during the earthquake event. The basement rock of the Korean Peninsula is known to have a highly resistive electrical structure that makes it possible for small-magnitude earthquakes to generate exaggerated geomagnetic variations. This is the first study reporting the relation between these earthquake events and the geomagnetic variations observed in the Korean Peninsula.

Electrical resistivity response due to variation in embankment shape and reservoir levels

The safety of the center-core type of fill dam structure was assessed by examining the effects of the distortion of electrical response verified in terms of two-dimensional (2D) apparent resistivity and its inverted sections from three-dimensional (3D) modeling for the embankment. The distortion effect is due to 2D interpretation of the 3D structure of the embankment. From the analysis, it was found that water level was correctly described by the resistivity section around the middle part rather than each side at the end of the embankment. This is due to the 3D terrain effect when the material of the embankment is assumed to be horizontally uniform. In addition, when the slope of the outer rock-fill section is set as uniform, the resistivity section is more similar for sharper center-core slopes. On the other hand, when the rock-fill slope is steep, the resistivity section shows the water level at a lower position than the real one, and the 3D distortion effect at the end of the embankment is enhanced.

Negative apparent resistivity in dipole–dipole electrical surveys

In field surveys using the dipole–dipole electrical resistivity method, we often encounter negative apparent resistivity. The term ‘negative apparent resistivity’ refers to apparent resistivity values with the opposite sign to surrounding data in a pseudosection. Because these negative apparent resistivity values have been regarded as measurement errors, we have discarded the negative apparent resistivity data. Some people have even used negative apparent resistivity data in an inversion process, by taking absolute values of the data. Our field experiments lead us to believe that the main cause for negative apparent resistivity is neither measurement errors nor the influence of self potentials. Furthermore, we also believe that it is not caused by the effects of induced polarization. One possible cause for negative apparent resistivity is the subsurface geological structure. In this study, we provide some numerical examples showing that negative apparent resistivity can arise from geological structures. In numerical examples, we simulate field data using a 3D numerical modelling algorithm, and then extract 2D sections. Our numerical experiments demonstrate that the negative apparent resistivity can be caused by geological structures modelled by U-shaped and crescent-shaped conductive models. Negative apparent resistivity usually occurs when potentials increase with distance from the current electrodes. By plotting the voltage-electrode position curves, we could confirm that when the voltage curves intersect each other, negative apparent resistivity appears. These numerical examples suggest that when we observe negative apparent resistivity in field surveys, we should consider the possibility that the negative apparent resistivity has been caused by geological structure.

Restoration, Prediction and Noise Analysis of Geomagnetic Time-series Data

Restoration, prediction and noise analysis of geomagnetic data measured in the Korean Peninsula were performed. Restoration methods based on an optimized principal component analysis (PCA) and the geostatistical kriging approach were proposed, and its effectiveness was also interpreted. The PCA-based method seemed to be effective to restore the periodical signals and the geostatistical approach was stable to fill the gaps of measurements. To analyze the noise level for each observatory, the geomagnetic time-series was plotted by scattergram which reflects the spatial variation, using data observed during same period. The scattergram showed that the observation made at Cheongyang seemed to have better quality in spatial continuity and stability, and the restoration result was also better than that of Icheon site. For the restoration, both of the methods, geostatistical and optimizaed PCA, showed stable result when the missing of observation was within 20 points. However, in case of more missing observations than 20 points and prediction problem, the optimized PCA seemed to be closer to the real observation considering the frequency-domain characteristics. The prediction using the optimized PCA seems to be plausible for one day of period for interpretation.

A Study on Temporal Variations of Geomagnetic Transfer Functions and Polarization Values Obtained at Cheongyang Geomagnetic Observatory

We analyzed a total of six months of geomagnetic data obtained at Cheonyang observatory, which is operated by Korean Meteorological Administration, to monitor earthquake precursors. Geomagnetic transfer functions (GTFs) and polarization values, which reflect the time-variations of the resistivity of subsurface, were estimated from 3-component geomagnetic data. The time-variant fluctuations were compared with the earthquake events occurred in the same period. Now that the daily GTFs show fairly irregular variations, we can not identify any correlation with the already occurred earthquakes and Kp index. On the other hand, we detect clear increases of the Ultra-Low-Frequency (ULF) band polarization values before the earthquakes, but the similar features are also observed even though the earthquake did not occur. This result may indicate that these time-variations are not just due to the earthquake precursor. For further understanding about these results, we need to investigate the relationship between the previous earthquake events and the geomagnetic data of other observatories.

Geostatistical Approach to Integrated Modeling of Iron Mine for Evaluation of Ore Body

Evaluation of three-dimensional ore body modeling has been performed by applying the geostatistical integration technique to multiple geophysical (electrical resistivity, MT) and geological (borehole data, physical properties of core) information. It was available to analyze the resistivity range in borehole and other area through multiple geophysical data. A correlation between resistivity and density from physical properties test of core was also analyzed. In the case study results, the resistivity value of ore body is decreased contrast to increase of the density, which seems to be related to a reason that the ore body (magnetite) includes heavy conductive component (Fe) in itself. Based on the lab test of physical properties in iron mine region, various geophysical, geological and borehole data were used to provide ore body modeling, that is electrical resistivity, MT, physical properties data, borehole data and grade data obtained from borehole data. Of the various geostatistical techniques for the integrated data analysis, in this study, the SGS (sequential Gaussian simulation) method was applied to describe the varying non-homogeneity depending on region through the realization that maintains the mean and variance. With the geostatistical simulation results of geophysical, geological and grade data, the location of residual ore body and ore body which is previously reported was confirmed. In addition, another highly probable region of iron ore bodies was estimated deeper depth in study area through integrated modeling.

Application of DC Resistivity Survey from Upper Portion of Concrete and Geostatistical Integrated Analysis

A DC resistivity survey was performed to detect anomalies beneath concrete pavement. A set of high conductive media and planar electrodes were used to lessen the effect’s a high contact resistance of concrete. Results of the resistivity survey were analyzed and compared with those of other geophysical surveys such as Ground Penetration Radar (GPR), Impulse Response (IR), and Multi-channel Analysis of Surface Waves (MASW), which were carried out in the same location. The results of resistivity survey showed a high resistive distribution in the section of sink and pavement where a pattern of reinforcement was observed through the GPR survey. Also, a comparison of results between the IR and resistivity surveys indicated that the high resistivity was produced by the high dynamic stiffness in the reinforced section. The co-Kriging of both the results of DC resistivity and MASW surveys at the same location showed that an integrated geostatistical analysis is able to give more accurate description on the anomalous subsurface region than can a separate analysis of each geophysical approach. This study suggests that the integrated geostatistical approaches were used for a decision-making process based on the geophysical surveys.