• Journal of the Korean earth science society
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• v.32 no.6
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• pp.665-673
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• 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 the Korean earth science society
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• v.39 no.3
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• pp.228-240
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• 2018

Solar energy is calculated using meteorological (14 station), ceilometer (2 station) and microwave radiometer (MWR, 7 station)) data observed from the Weather Information Service Engine (WISE) on the Seoul metropolitan area. The cloud optical thickness and the cloud fraction are calculated using the back-scattering coefficient (BSC) of the ceilometer and liquid water path of the MWR. The solar energy on the surface is calculated using solar radiation model with cloud fraction from the ceilometer and the MWR. The estimated solar energy is underestimated compared to observations both at Jungnang and Gwanghwamun stations. In linear regression analysis, the slope is less than 0.8 and the bias is negative which is less than $-20W/m^2$. The estimated solar energy using MWR is more improved (i.e., deterministic coefficient (average $R^2=0.8$) and Root Mean Square Error (average $RMSE=110W/m^2$)) than when using ceilometer. The monthly cloud fraction and solar energy calculated by ceilometer is greater than 0.09 and lower than $50W/m^2$ compared to MWR. While there is a difference depending on the locations, RMSE of estimated solar radiation is large over $50W/m^2$ in July and September compared to other months. As a result, the estimation of a daily accumulated solar radiation shows the highest correlation at Gwanghwamun ($R^2=0.80$, RMSE=2.87 MJ/day) station and the lowest correlation at Gooro ($R^2=0.63$, RMSE=4.77 MJ/day) station.

• Journal of the Korean earth science society
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• v.36 no.1
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• pp.109-124
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• 2015

A novel approach, hybrid surface rainfall (KNU-HSR) technique developed by Kyungpook Natinal University, was utilized for improving the radar rainfall estimation. The KNU-HSR technique estimates radar rainfall at a 2D hybrid surface consistings of the lowest radar bins that is immune to ground clutter contaminations and significant beam blockage. Two HSR techniques, static and dynamic HSRs, were compared and evaluated in this study. Static HSR technique utilizes beam blockage map and ground clutter map to yield the hybrid surface whereas dynamic HSR technique additionally applies quality index map that are derived from the fuzzy logic algorithm for a quality control in real time. The performances of two HSRs were evaluated by correlation coefficient (CORR), total ratio (RATIO), mean bias (BIAS), normalized standard deviation (NSD), and mean relative error (MRE) for ten rain cases. Dynamic HSR (CORR=0.88, BIAS= $-0.24mm\;hr^{-1}$, NSD=0.41, MRE=37.6%) shows better performances than static HSR without correction of reflectivity calibration bias (CORR=0.87, BIAS= $-2.94mm\;hr^{-1}$, NSD=0.76, MRE=58.4%) for all skill scores. Dynamic HSR technique overestimates surface rainfall at near range whereas it underestimates rainfall at far ranges due to the effects of beam broadening and increasing the radar beam height. In terms of NSD and MRE, dynamic HSR shows the best results regardless of the distance from radar. Static HSR significantly overestimates a surface rainfall at weaker rainfall intensity. However, RATIO of dynamic HSR remains almost 1.0 for all ranges of rainfall intensity. After correcting system bias of reflectivity, NSD and MRE of dynamic HSR are improved by about 20 and 15%, respectively.

• Journal of the Korean earth science society
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• v.33 no.2
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• pp.148-161
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• 2012

The intensive observation (ProbeX-2010) with 6-hour launches of radiosonde was performed over Seoul metropolitan area (Dongducheon, Incheon Airport, and Yangpyeong) from 13 Aug. to 3 Sep. 2010. Five typical heavy rainfall patterns occurred consecutively which are squall line, stationary front, remote tropical cyclone (TC), tropical depression, and typhoon patterns. On 15 Aug. 03 KST, when squall line developed over Seoul metropolitan area, dry mid-level air was drawn over warm and moist low-level air, inducing strong convective instability. From 23 to 26 Aug and from 27 to 29 Aug. Rainfall event occurred influenced by stationary front and remote TC, respectively. During the stationary frontal rainy period, thermal instability was dominant in the beginning stage, but dynamic instability became strong in the latter stage. Especially, heavy rainfall occurred on 25 Aug. when southerly low level jet formed over the Yellow Sea. During the rainy period by the remote TC, thermal and dynamic instability sustained together. Especially, heavy rainfall event occurred on 29 Aug. when the tropical air with high equivalent potential temperature (>345 K) occupied the deep low-middle level. On 27 Aug. and 2 Sep. tropical depression and typhoon Kompasu affected Seoul metropolitan area, respectively. During these events, dynamic instability was very strong.

• Journal of the Korean earth science society
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• v.28 no.4
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• pp.478-490
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• 2007

With groundwater data of seawater intrusion monitoring network in coastal areas of Korea's main land, we analyzed types of seawater intrusion through the coastal aquifer. The data including groundwater level, temperature and electrical conductivity obtained from 45 monitoring wells at 25 watershed regions were evaluated. Based on statistical analysis, correlation analysis and variation type analysis, groundwater levels were mainly affected by rainfall and artificial pumping. About 78% of the monitoring wells showed average temperature higher than $15^{\circ}C$ and about 58% of them showed minimum variations less than $0.2^{\circ}C$. Electrical conductivities showed a large magnitude of variation and irregular characteristics compared with groundwater levels and temperatures. Average electrical conductivities lower than $2,000\;{\mu}S/cm$ were observed at 28 monitoring wells while those of higher than $10,000\;{\mu}S/cm$ were done at 9 monitoring wells. From the cross-correlation analysis, groundwater levels were mostly affected by precipitation while temperature and electrical conductivity showed very low correlation. Meanwhile tidal variations strongly affected the groundwater levels comparing to precipitation. We classified the long-term monitoring data according to variation types such as constant process, linear trend, cyclic variation, impulse, step function and ramp. Impulse type was dominant for variations of groundwater level, which was largely affected by rainfall or artificial pumping, the constant process was dominant for temperature. Compared with groundwater level and temperature, electrical conductivities showed various types like linear trend, step function and ramp. According to the discrepancy of variation characteristics for monitoring data at each well in the same region, periodical analysis of monitoring data is essentially required.

• Journal of the Korean earth science society
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• v.34 no.4
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• pp.303-312
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• 2013

Typhoon Sanba was selected for describing the Korea Meteorological Administration (KMA) Global Data Assimilation Prediction System (GDAPS) model bias tendency in forecast for the interaction between mid-latitude trough and movement speed of typhoon. We used the KMA GDAPS analyses and forecasts initiated 00 UTC 15 September 2012 from the historical typhoon record using Typhoon Analysis and Prediction System (TAPS) and Combined Meteorological Information System-3 (COMIS-3). Sea level pressure fields illustrated a development of the low level mid-latitude cyclogenesis in relation to Jet Maximum at 500 hPa. The study found that after Sanba entered the mid-latitude domain, its movement speed was forecast to be accelerated. Typically, Snaba interacted with mid-latitude westerlies at the front of mid-latitude trough. This event occurred when the Sanba was nearing recurvature at 00 and 06 UTC 17 September. The KMA GDAPS sea level pressure forecasts provided the low level mid-latitude cyclone that was weaker than what it actually analyzed in field. As a result, the mid-latitude circulations affecting on Sanba's movement speed was slower than what the KMA GDAPS actually analyzed in field. It was found that these circulations occurred due to the weak mid-tropospheric jet maximum at the 500 hPa. In conclusion, the KMA GDAPS forecast tends to slow a bias of slow movement speed when Sanba interacted with the mid-latitude trough.