• 한국지구물리탐사학회:학술대회논문집
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• 2009.05a
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• pp.47-56
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• 2009

Proper reservoir characterization is an integral part of formation evaluation, reserve estimation and planning of field development. Seismic inversion is a widely employed reservoir characterization tool that provides various rock properties of reservoir intervals. This study presents results of the inversion studies including Geostatistical Inversion carried out on the gas fields, offshore Myanmar. Higher resolution and multiple models can be produced by Geostatistical Inversion using input data such as pre-stack seismic data, well logs, petrophysical relationships and geological inferences for example reservoir shape and lateral extent. Detailed reservoir characterization was required for the development plan of gas fields, and the Geostatistical Inversion studies served as a basis for integrated geological modeling and development well planning.

• Geophysics and Geophysical Exploration
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• v.12 no.4
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• pp.309-315
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• 2009

Integrated interpretation of multi-geophysical data has been continuously used in terms that it has provided more confident information than the result from single-geophysical data. Especially, geostatistical integration has its own superiority that it is possible to deal with spatial characteristics as well as physical properties of survey data and the process of integration is clear. This paper further extends the previous work of geostatistical inversion for integrated interpretation. In this paper, we propose a new way of dealing with the case that the multi-geophysical data do not share the measurement range. According to the geostatistical kriging, the closer between the measurement points, the smaller kriging variance we get, and vice versa. We used this spatial properties as a weighting value to the process of geostatistical inversion for the geophysical data integration. An objective way to integrate different kinds of geophysical data measured at different ranges is provided with this algorithm.

• Journal of the Korean earth science society
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• v.23 no.1
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• pp.15-29
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• 2002

Bayesian inversion for gravity and resistivity data was performed to investigate the cavity structure appearing as a lava tunnel in Cheju Island, Korea. Dipole-dipole DC resistivity data were proposed for a prior information of gravity data and we applied the geostatistical techniques such as kriging and simulation algorithms to provide a prior model information and covariance matrix in data domain. The inverted resistivity section gave the indicator variogram modeling for each threshold and it provided spatial uncertainty to give a prior PDF by sequential indicator simulations. We also presented a more objective way to make data covariance matrix that reflects the state of the achieved field data by geostatistical technique, cross-validation. Then Gaussian approximation was adopted for the inference of characteristics of the marginal distributions of model parameters and Broyden update for simple calculation of sensitivity matrix and SVD was applied. Generally cavity investigation by geophysical exploration is difficult and success is hard to be achieved. However, this exotic multiple interpretations showed remarkable improvement and stability for interpretation when compared to data-fit alone results, and suggested the possibility of diverse application for Bayesian inversion in geophysical inverse problem.

• Journal of the Korean earth science society
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• v.31 no.7
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• pp.681-690
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• 2010

Inversion result of geophysical data given as a block type was geostatistically simulated with borehole observation given as a point type and was applied to the rock classifying map. The geophysical data generally involved secondary information for the target material and were obtained for overall region. In contrast, borehole data provided direct information for the target material, but tended to be effective only for a narrow range of region and were dealt as a point type. Integrated simulation or kriging interpolation of these two different kinds of information required the covariance for point-point, point-block and block-block. Using the Bssim module included in SGeMS software, integrated result of geophysical data and borehole data were obtained. The results were then compared with the method of geostatistical inversion proposed by authors. Downscaling method used in this study showed relatively more flexible than the geostatistical inversion.

• 한국지구물리탐사학회:학술대회논문집
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• 2007.06a
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• pp.42-47
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• 2007

We have studied feasibility of the geostatistical approach to enhance the result of analysis of the sparsely obtained MT(Magnetotelluric) data by combining with gravity data. We have attempted to use geostatistics for integrating the MT data along with gravity data. To evaluate the feasibility of this approach, we have studied about interrelation between geological boundary and density distribution, and corrected density distribution for conversion to more sensitive to geological boundary by minimization of difference between z-directional variogram values of resistivity distribution obtained MT inversion and density distributions. Then, this method has been tested on model and field data. In model test, the results obtained were good agreement with real model. And in a real field data, the result of analysis demonstrate convincingly that our geostatistical approach is effective.

• 한국지구물리탐사학회:학술대회논문집
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• 2003.11a
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• pp.340-343
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• 2003

This study presents a practical procedure for the Bayesian inversion of geophysical data by Markov chain Monte Carlo (MCMC) sampling and geostatistics. We have applied geostatistical techniques for the acquisition of prior model information, and then the MCMC method was adopted to infer the characteristics of the marginal distributions of model parameters. For the Bayesian inversion of dipole-dipole array resistivity data, we have used the indicator kriging and simulation techniques to generate cumulative density functions from Schlumberger array resistivity data and well logging data, and obtained prior information by cokriging and simulations from covariogram models. The indicator approach makes it possible to incorporate non-parametric information into the probabilistic density function. We have also adopted the MCMC approach, based on Gibbs sampling, to examine the characteristics of a posteriori probability density function and the marginal distribution of each parameter. This approach provides an effective way to treat Bayesian inversion of geophysical data and reduce the non-uniqueness by incorporating various prior information.

• Journal of Soil and Groundwater Environment
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• v.20 no.3
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• pp.51-64
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• 2015

In the present study, we develop two history matching techniques based on Markov chain Monte Carlo method where radial basis function and Gaussian distribution generated by unconditional geostatistical simulation are employed as the random walk transition kernels. The Bayesian inverse methods for aquifer characterization as the developed models can be effectively applied to the condition even when the targeted information such as hydraulic conductivity is absent and there are transient hydraulic head records due to imposed stress at observation wells. The model which uses unconditional simulation as random walk transition kernel has advantage in that spatial statistics can be directly associated with the predictions. The model using radial basis function network shares the same advantages as the model with unconditional simulation, yet the radial basis function network based the model does not require external geostatistical techniques. Also, by employing radial basis function as transition kernel, multi-scale nested structures can be rigorously addressed. In the validations of the developed models, the overall predictabilities of both models are sound by showing high correlation coefficient between the reference and the predicted. In terms of the model performance, the model with radial basis function network has higher error reduction rate and computational efficiency than with unconditional geostatistical simulation.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2001.09a
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• pp.92-96
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• 2001

Although the problem of seawater intrusion at the coastal aquifer was recognized before over one hundred years at the coastal aquifer, much groundwater keep on being salinitized by several reasons such as groundwater exhaustion, coastalline change, and human activities. The horizontal and vertical electrical soundings and geostatistical methods were used to define the local characteristics of saltwater intrusion and to estimate the saltwater interface in the southeastern area of the Pusan City. The 24 points of the Schlumberger vertical electrical soundings(VES) to loom depth and the 2 lines of dipole-dipole horizontal soundings are peformed. The resistivity data have lognormal distributions. The horizontal extents of saline water intrusion were estimated from the inversion of horizontal prospecting data. Lognormal ordinary kriging is used in A-A' resistivity profiles on May and July because the data have stationary models in semivariograms. Lognormal IRF-k kriging is used for the isopleth maps using vertical resistivity data. The 10 ohm-m resistivity line on the isopleth maps of 21m, 30m, 50m, and 70m depth using resisitivity data measured in July is sifted to the east, cpomparing that of the isopleth maps measured in May. The kriged vertical and horizontal resistivity isopleth maps suggested that the geostatistical methods can be used to define the variation of earth resistivity distribution at the saltwater interface.

• 한국지구물리탐사학회:학술대회논문집
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• 2005.05a
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• pp.59-64
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• 2005

Although experimental analysis for groundwater sample at wells located systematically are very effective to delineate seawater intrusion region at coastal area, this method is restricted in few wells and time. We have conducted electrical resistivity sounding at 30 points in the study areas to analyze the region of seawater intrusion and found the boundary between salt wedge and fresh water lens from the analysis results of geostatistical method using variogram for one-dimensional inversion results. The methodology adopted in this study would be useful for finding the seawater intrusion region and evaluating quantitatively.

• 한국지구물리탐사학회:학술대회논문집
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• 2008.10a
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• pp.63-67
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• 2008

Geostatistical inverse approach using geophysical data was applied to indirectly make the RMR classification at points apart from boreholes. The geostatistical appoach was usually used to find optimized estimation which supports two or more different physical properties at unsampled points. However, in this study, an approach to solve inverse problem was proposed. The primary variable, RMR values obtained at known boreholes, is geostatistically simulated with many realization at pre-defined grid point according to the variogram model. The simulated values are sequentially compared with the physical property resulted from geophysical survey at an arbitrary grid point, and the most similar one is chosen. This process means that the spatial distribution of primary variable, RMR, is conformed well to the original pattern of the borehole observation, and ensure to fit the geophysical survey result to reflect the correlation between different physical properties.