• 한국지구물리탐사학회:학술대회논문집
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• 2009.10a
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• pp.75-80
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• 2009

Despite its flexibility to complex geometry, three-dimensional (3D) electromagnetic(EM) modeling schemes using finite element method (FEM) have been faced to practical limitation due to the resulting large system of equations to be solved. An efficient 3D FEM modeling scheme has been developed, which can adopt either direct or iterative solver depending on the problems. The direct solver PARDISO can reduce the computing time remarkably by incorporating parallel computing on multi-core processor systems, which is appropriate for single frequency multi-source configurations. When limited memory, the iterative solver BiCGSTAB(1) can provide fast and stable convergence. Efficient 3D simulations can be performed by choosing an optimum solver depending on the computing environment and the problems to be solved. This modeling includes various types of controlled-sources and can be exploited as an efficient engine for 3D inversion.

• Journal of The Korean Association For Science Education
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• v.28 no.8
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• pp.796-813
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• 2008

A good understanding of how gifted science students understand physics is important to developing and delivering effective curriculum for gifted science students. This dissertation reports on a systematic investigation of gifted science students' reasoning model in learning physics. An analysis of videotaped class work, written work and interviews indicate that I will discuss the framework to characterize student reasoning. There are three main groups of students. The first group of gifted science students holds several different understandings of a single concept and apply them inconsistently to the tasks related to that concept. Most of these students hold the Aristotelian Model about Newton's second law. In this case, I define this reasoning model as the manifold model. The second group of gifted science students hold a unitary understanding of a single concept and apply it consistently to several tasks. Most of these students hold a Newtonian Model about Newton's second law. In this case, I define this reasoning model as the coherence model. Finally, some gifted science students have a manifold model with several different perceptions of a single concept and apply them inconsistently to tasks related to the concept. Most of these students hold the Aristotelian Model about Newton's second law. In this case, I define this reasoning model as the coherence model.

• Geophysics and Geophysical Exploration
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• v.21 no.1
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• pp.15-25
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• 2018

Seismic inversion is a high-resolution tool to delineate the subsurface structures which may contain oil or gas. On the other hand, marine controlled-source electromagnetic (mCSEM) inversion can be a direct tool to indicate hydrocarbon. Thus, the joint inversion using both EM and seismic data together not only reduces the uncertainties but also takes advantage of both data simultaneously. In this paper, we have developed a simultaneous joint inversion approach for the direct estimation of reservoir petrophysical parameters, by linking electromagnetic and seismic data through rock physics model. A cross-gradient constraint is used to enhance the resolution of the inversion image and the maximum likelihood principle is applied to the relative weighting factor which controls the balance between two disparate data. By applying the developed algorithm to the synthetic model simulating the simplified gas field, we could confirm that the high-resolution images of petrophysical parameters can be obtained. However, from the other test using the synthetic model simulating an anticline reservoir, we noticed that the joint inversion produced different images depending on the model constraint used. Therefore, we modified the algorithm which has different model weighting matrix depending on the type of model parameters. Smoothness constraint and Marquardt-Levenberg constraint were applied to the water-saturation and porosity, respectively. When the improved algorithm is applied to the anticline model again, reliable porosity and water-saturation of reservoir were obtained. The inversion results indicate that the developed joint inversion algorithm can be contributed to the calculation of the accurate oil and gas reserves directly.

• Geophysics and Geophysical Exploration
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• v.20 no.4
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• pp.216-225
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• 2017

Recently, steel casing became an interesting issue when applying controlled-source electromagnetic (EM) method to various fields because effects of steel casing on EM responses are not negligible. This study employed an approach that approximates the steel casing as a series of electric dipole sources in order to develop the numerical algorithm for the efficient simulation of EM responses in the presence of steel casing. After verifying the validity of the developed algorithm, we analyze effects of steel casing on EM responses with the synthetic model simulating geothermal reservoir environment. The analysis showed that the effects of steel casing on EM responses are localized near the casing and increase as the transmitter becomes close to the casing. In addition, through the analysis on the EM responses by the injection of clean water, we confirm that the effects of casing are negligible when interpreting the after-injection data acquired using the transmitter located far enough from the casing. Considering the difference in EM responses between before and after injection in inversion, the effects of the casing can be neglected although after-injection data shows considerable difference due to the close distance between the transmitter and casing. To investigate this kind steel casing effect, the precise analysis on EM responses should be preceded. The algorithm introduced in this study will contribute to the reliable calculations of EM responses distorted by the conductive steel casing.