• Geophysics and Geophysical Exploration
• /
• v.9 no.3
• /
• pp.231-240
• /
• 2006

A variety of geophysical well loggings have been conducted to investigate the geological characteristics for basaltic volcanic area in Jeju Island. Specially, there is no precedent case study using geophysical well loggings in Jeju Island. And so, the proper understandings for geological features of Jeju Island are the key to interpret geophysical well logs. Presently, seawater intrusion monitoring systems have been constructed for systematic development and conservation of groundwater resources. As the results of geophysical well loggings in this seawater intrusion monitoring boreholes, the responses of well logs for saturated zone have distinctly identified basalt sequences. In particular, neutron logging, gamma-gamma (density) logging, and resistivity logging have well exhibited the characteristics of lava flows and lithologic boundaries. In hyalocastite, porosity is high, and resistivity is low. Eventually, geophysical well logs are useful for securing sustainable development of groundwater in Jeju Island in that it has identified the characteristics of geological responses.

• Geophysics and Geophysical Exploration
• /
• v.10 no.4
• /
• pp.332-344
• /
• 2007

Various geophysical well logs have been made along the four deep wells in Pohang, Gyeongbuk. The primary focus of geophysical well loggings was to improve understanding the subsurface geologic structure, to evaluate in situ physical properties, and to estimate aquifer production zones using fluid temperature and conductivity gradient logs. Especially natural gamma logs interpreted with core logs of borehole BH-1 were useful to discriminate the lithology and to determine the lithologic sequences and boundaries consisting of semi-consolidated Tertiary sediments and intrusive rocks such as basic dyke and Cretaceous sediments. Cross-plot of physical properties inferred from geophysical well logs were used to identify rock types such as Cretaceous sandstone and mudstone, Tertiary sediments, rhyolite, and basic dyke. The temperature log indicated $82.51^{\circ}C$ at the depth of 1,981.3 meters in borehole BH-4. However, considering the temperature of borehole BH-2 measured under stable condition, we expect the temperature at the depth in borehole BH-4, if it is measured in stable condition, to be about 5 or $6^{\circ}C$ higher. Several permeable fractures also have been identified from temperature and conductivity gradient logs, and cutting logs.

• Geophysics and Geophysical Exploration
• /
• v.3 no.3
• /
• pp.101-111
• /
• 2000

In order to assess the seawater intrusion, induction, temperature and conductivity of fluid, and natural gamma logs were obtained in nine wells at the three study areas having different hydrogeologic characteristics. Besides surface geophysical exploration, supplementary geophysical well logs were carried out to understand the hydrogeological characteristics related to the seawater intrusion in the study areas. The geophysical well logs have been proved to increase the accuracy of interpretation of the surface geophyscial exploration's data for assessment of seawater intrusion, and to get the optimum depth for a long monitoring of groundwater. They, also, revealed that the identification of hydrogeological units for strata's porosity was able to be achieved and were illustrated the applicability of geophysical well logs monitoring. Finally, geophysical well logs are expected to play to get the more quantitative information of seawater infusion, if it is fully collaborated with a better method that is strata's resistivity determination with not relatively much effected by seawater within the drilled borehole and that is the porosity measurement with built on small diameter PVC casing.

• Geophysics and Geophysical Exploration
• /
• v.7 no.2
• /
• pp.109-116
• /
• 2004

Petroleum reservoir characterization is a process for quantitatively describing various reservoir properties in spatial variability using all the available field data. Porosity and permeability are the two fundamental reservoir properties which relate to the amount of fluid contained in a reservoir and its ability to flow. These properties have a significant impact on petroleum fields operations and reservoir management. In un-cored intervals and well of heterogeneous formation, porosity and permeability estimation from conventional well logs has a difficult and complex problem to solve by conventional statistical methods. This paper suggests an intelligent technique using fuzzy logic and neural network to determine reservoir properties from well logs. Fuzzy curve analysis based on fuzzy logics is used for selecting the best related well logs with core porosity and permeability data. Neural network is used as a nonlinear regression method to develop transformation between the selected well logs and core analysis data. The intelligent technique is demonstrated with an application to the well data in offshore Korea. The results show that this technique can make more accurate and reliable properties estimation compared with previously used methods. The intelligent technique can be utilized a powerful tool for reservoir characterization from well logs in oil and natural gas development projects.

• Economic and Environmental Geology
• /
• v.27 no.3
• /
• pp.289-294
• /
• 1994

This paper describes an effective utilization method of well logging data and boring cores for understanding the geology of Keoje-do area. Six holes were drilled in 1988-1989, and all rock cores were recovered. Nevertheless, seven kinds of logs were carried out in each borehole. The geologic situations of the drilling sites are accurately evaluated from a comparison between core descriptions and well logging data. Porosities and clay contents of sedimentary rocks can be calculated using the data of density and gamma-ray logs. Fractured zones are easily detected from the change in inside diameter of borehole by caliper log. Sonic, density and gamma-ray logging data clearly indicate alternated and dyke zones; the former can be detceted from an acoustic wave attenuation and a decline of compaction by sonic and density logs, the latter can be detected from the amount of potassium contents of bed rock and dyke by gamma-ray log.

• 한국지구물리탐사학회:학술대회논문집
• /
• 2005.09a
• /
• pp.55-71
• /
• 2005

Jeju Island is mainly composed of basaltic lava flows and subordinate amounts of volcaniclastic sedimentary rocks. Jeju Province operates the monitoring wells for seawater intrusion problems around Jeju Island to evaluate of groundwater resources in coastal area. Various surveys and monitoring have been performed in boreholes, and also conventional geophysical well loggings conducted to identify basalt sequences and assess seawater intrusion problems. Various conventional geophysical well logs, including radioactive logs, electrical log, caliper log, and temperature and conductivity log and heat-pulse flowmeter log were obtained in 29 boreholes. The results of geophysical well loggings for saturated rocks are interesting and consistent. Natural gamma logs are useful in basalt sequences to sedimentary interbeds, unconsolidated U formation, and seoguipo formation with higher natural gamma log regardless of saturated or unsaturated basalts. Neutron logs are very effective to discriminate among individual lava flows, flow breaks, and sedimentary interbeds in saturated formation. In hyalocastite, porosity is high and resistivity is low, and we think that hyalocastite is a major pathway of fluid flow. In trachybasalt, porosity has a wide range and resistivity is high. In sedimentary interbeds, unconsolidated U formation and seoguipo formation, porosity is high and resistivity is low. The temperature logs in eastern area in Jeju are useful to interpret the hydrogeological unit and evaluate seawater intrusion in Suan area.

• 한국지구물리탐사학회:학술대회논문집
• /
• 1999.08a
• /
• pp.156-175
• /
• 1999

Recently the application of geophysical well logging to geotechnical site investigation is increasing, because the merit that geophysical logs provide the high resolution and in-situ physical properties in volumes of rock surrounding the borehole. Geophysical well logs are used to identify lithologic boundaries and fracture, to determine the physical properties of rock(i.e., density, velocity etc.), and to detect permeable fracture zones that could be conduits for ground water movement through the rocks. The principle of heat-pulse meter, the calibration of gamma-gamma logging, and principles and data processing of full waveform sonic logging are briefly reviewed, and the case studies of geophysical logs are discussed. Correlation between velocity by sonic logging and rock mass classification such as RMR(Rock Mass Rating) value is considered.

• Journal of Information Processing Systems
• /
• v.17 no.4
• /
• pp.772-786
• /
• 2021

The process of tracking suspicious behavior manually on a system and gathering evidence are labor-intensive, variable, and experience-dependent. The system logs are the most important sources for evidences in this process. However, in the Microsoft Windows operating system, the action events are irregular and the log structure is difficult to audit. In this paper, we propose a model that overcomes these problems and efficiently analyzes Microsoft Windows logs. The proposed model extracts lists of both common and key events from the Microsoft Windows logs to determine detailed actions. In addition, we show an approach based on the proposed model applied to track illegal file access. The proposed approach employs three-step tracking templates using Elastic Stack as well as key-event, common-event lists and identify event lists, which enables visualization of the data for analysis. Using the three-step model, analysts can adjust the depth of their analysis.

• Journal of the Korean earth science society
• /
• v.32 no.6
• /
• pp.665-673
• /
• 2011

In order to estimate the hydrocarbon reserves, the porosity of the reservoir must be determined. The porosity of the area without a well is generally calculated by extrapolating the porosity logs measured at wells. However, if not only well logs but also seismic data exist on the same site, the more accurate pseudo porosity log can be obtained through artificial neural network technique by extracting the relations between the seismic data and well logs at the site. In this study, we have developed a module which creates pseudo porosity logs by using the polynomial neural network method. In order to obtain more accurate pseudo porosity logs, we selected the seismic attributes which have high correlation values in the correlation analysis between the seismic attributes and the porosity logs. Through the training procedure between selected seismic attributes and well logs, our module produces the correlation weights which can be used to generate the pseudo porosity log in the well free area. To verify the reliability and the applicability of the developed module, we have applied the module to the field data acquired from F3 Block in the North Sea and compared the results to those from the probabilistic neural network method in a commercial program. We could confirm the reliability of our module because both results showed similar trend. Moreover, since the pseudo porosity logs from polynomial neural network method are closer to the true porosity logs at the wells than those from probabilistic method, we concluded that the polynomial neural network method is effective for the data sets with insufficient wells such as F3 Block in the North Sea.

• Journal of Internet Computing and Services
• /
• v.20 no.1
• /
• pp.87-96
• /
• 2019

In this paper, we propose a MapReduce-supported clustering technique for collecting and classifying distributed workflow enactment event logs as a preprocessing tool. Especially, we would call the distributed workflow enactment event logs as Workflow BIG-Logs, because they are satisfied with as well as well-fitted to the 5V properties of BIG-Data like Volume, Velocity, Variety, Veracity and Value. The clustering technique we develop in this paper is intentionally devised for the preprocessing phase of a specific workflow process mining and analysis algorithm based upon the workflow BIG-Logs. In other words, It uses the Map-Reduce framework as a Workflow BIG-Logs processing platform, it supports the IEEE XES standard data format, and it is eventually dedicated for the preprocessing phase of the ${\rho}$-Algorithm that is a typical workflow process mining algorithm based on the structured information control nets. More precisely, The Workflow BIG-Logs can be classified into two types: of activity-based clustering patterns and performer-based clustering patterns, and we try to implement an activity-based clustering pattern algorithm based upon the Map-Reduce framework. Finally, we try to verify the proposed clustering technique by carrying out an experimental study on the workflow enactment event log dataset released by the BPI Challenges.