• Economic and Environmental Geology
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• v.44 no.1
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• pp.83-94
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• 2011

Extra heavy oil reservoirs are distributed over the world but most of them is deposited in the northern part of the Orinoco River in Venezuela, in the area of 5,500 $km^2$, This region, which has been commonly called "the Orinoco Oil Belt", contains estimated 1.3 trillion barrels of original oil-in-place and 250 billion barrels of established reserves. The Venezuela extra heavy oil has an API gravity of less than 10 degree and in situ viscosity of 5,000 cP at reservoir condition. Although the presence of extra heavy oil in the Orinoco Oil Belt has been initially reported in the 1930's, the commercial development using in situ cold production started in the 1990's. The Orinoco heavy oil deposits are clustered into 4 development areas, Boyaco, Junin, Ayachoco, and Carabobo respectively, and they are subdivided into totally 31 production blocks. Nowadays, PDVSA (Petr$\'{o}$leos de Venzuela, S.A.) makes a development of each production block with the international oil companies from more than 20 countries forming a international joint-venture company. The Eastern Venezuela Basin, the Orinoco Oil Belt is included in, is one of the major oil-bearing sedimentary basins in Venezuela and is first formed as a passive margin basin by the Jurassic tectonic plate motion. The major source rock of heavy oil is the late Cretaceous calcareous shale in the central Eastern Venezuela Basin. Hydrocarbon materials migrated an average of 150 km up dip to the southern margin of the basin. During the migration, lighter fractions in the hydrocarbon were removed by biodegradation and the oil changed into heavy and/or extra heavy oil. Miocene Oficina Formation, the main extra heavy oil reservoir, is the unconsolidated sand and shale alternation formed in fluvial-estuarine environment and also has irregularly a large number of the Cenozoic faults induced by basin subsidence and tectonics. Because Oficina Formation has not only complex lithology distribution but also irregular geology structure, geological evolution and characteristics of the reservoirs have to be determined for economical production well design and effective oil recovery. This study introduces geological formation and evolution of the Venezuela extra heavy oil reservoirs and suggest their significant geological characteristics which are (1) thickness and geometry of reservoir pay sands, (2) continuity and thickness of mud beds, (3) geometry of faults, (4) depth and geothermal character of reservoir, (5) in-situ stress field of reservoir, and (6) chemical composition of extra heavy oil. Newly developed exploration techniques, such as 3-D seismic survey and LWD (logging while drilling), can be expected as powerful methods to recognize the geological reservoir characteristics in the Orinoco Oil Belt.

• Geophysics and Geophysical Exploration
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• v.17 no.1
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• pp.1-10
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• 2014

To reveal and classify site characteristics in densely populated areas in Chuncheon, Korea, Rayleigh-waves were recorded at 50 sites including four sites in the forest area using four 1-Hz velocity sensors and 24 4.5-Hz vertical geophones during the period of January 2011 to May 2013. Dispersion curves of the Rayleigh waves obtained by the extended spatial autocorrelation method were inverted to derive shear-wave velocity ($v_s$) models comprising 40 horizontal layers of 1-m thickness. Depths to weathered rocks ($D_b$), shear wave velocities of these basement rocks ($v_s^b$), average velocities of the overburden layer ($\bar{v}_s^s$), and the average velocity to a depth of 30 m ($v_s30$), were then derived from those models. The estimated values of $D_b$, $v_s^b$, $\bar{v}_s^s$, and $v_s30$ for 46 sites at lower altitudes were in the ranges of 5 to 29 m, 404 to 561 m/s, 208 to 375 ms/s, and 226 to 583 m/s, respectively. According to the Korean building code for seismic design, the estimated $v_s30$ indicates that the lower altitude areas in Chuncheon are classified as $S_C$ (very dense soil and soft rock) or $S_D$ (stiff soil). To determine adequate proxies for $v_s30$, we compared the computed values with land cover, lithology, topographic slope, and surface elevation at each of the measurement sites. Due to a weak correlation (r = 0.41) between $v_s30$ and elevation, the best proxy of them, applications of this proxy to Chuncheon of a relatively small area seem to be limited.

• Journal of the Korean Geotechnical Society
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• v.36 no.2
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• pp.5-15
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• 2020

The liquefaction phenomenon that occurred during the Pohang earthquake (M_L=5.4) brought new awareness to the people about the risk of liquefaction caused by the earthquake. Liquefaction hazard maps with 2 km grid made in 2014 used more than 100,000 borehole data for the whole country, and regions without soil investigation data were produced using interpolation. In the mapping of macro liquefaction hazard for the whole country, the site amplification effect and the ground water level 0 m were considered. Recently, the Ministry of Public Administration and Security (2018) published a new site classification method and amplification coefficient of the common standard for seismic design. Therefore, it is necessary to rewrite the liquefaction hazard map reflecting the revised amplification coefficient. In this study, the results of site classification according to the average shear wave velocity in soils before and after revision were compared in the whole country. Also, liquefaction assessment results were compared in Gangseo-gu, Busan. At this time, two ground accelerations corresponding to the 500 and 1,000 years of return period and two ground water table, 5 m for the average condition and 0 m the extreme condition were applied. In the drawing of liquefaction hazard map, a 500 m grid was applied to secure a resolution higher than the previous 2 km grid. As a result, the ground conditions that were classified as S_C and S_D grounds based on the existing site classification standard were reclassified as S₂, S₃, and S₄ through the revised site classification standard. Also, the result of the Liquefaction assessments with a return period of 500 years and 1,000 years resulted in a relatively overestimation of the LPI applied with the ground amplification factor before revision. And the results of this study have a great influence on the liquefaction assessment, which is the basis of the creation of the regional liquefaction hazard map using the amplification factor.