• Journal of Korean Society for Geospatial Information Science
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• v.17 no.1
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• pp.113-120
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• 2009

Through the automatic sensing of the environment, USN technology can give the best services. In this work, we have developed an active RFID system and examined its performance. By implementing it into water quality sensors, we constructed a system that can detect diverse indoor/outdoor environment and provide information about the pollution level obtained from the temperature and PH sensors. Our RF system had an internal Print-on-PCB antenna for the miniaturization of the tag. We used a RF transceiver CC2510 chipset of TI company to realize the active RFID function. By using RSSI constants obtained, we performed the evaluation of real time location accuracy with a software written in Labview. Among 10 arbitrary locations, we obtained average measurement errors of 1.69 m in x axis and 1.66 m in y axis. This technology can be applied to logistics, environmental monitoring, prevention of missing children and various applications.

• Economic and Environmental Geology
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• v.49 no.3
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• pp.225-242
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• 2016

Rock physics serves as a useful tool for seismic reservoir characterization and monitoring by providing quantitative relationships between rock properties and seismic data. Rock physics models can predict effective moduli for reservoirs with different mineral components and pore fluids from well-log data. The distribution of reservoirs and fluids for the entire seismic volume can also be estimated from rock physics models. The first part of this report discusses the Voigt, Reuss, and Hashin-Shtrikman bounds for effective elastic moduli and the Gassmann fluid substitution. The second part reviews various contact models for moderate- to high-porosity sands. In the third part, constant-cement model, known to work well for the sand that gradually loses porosity with deteriorating sorting, was applied to the well-log data from an oil field in the North Sea. Lastly, the rock physics template constructed from the constant-cement model and the results from the prestack inversion of 2D seismic data were combined to predict the lithology and fluid types for the sand reservoir of this oil field.