• Proceedings of the KSEEG Conference
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• 2001.04a
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• pp.268-270
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• 2001

• 한국지구과학회:학술대회논문집
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• 2010.04a
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• pp.106-106
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• 2010

오일샌드는 비투멘(bitumen), 물, 점토, 모래의 혼합체로 이루어진 비재래형 탄화수소 자원으로 세계적인 고유가 시대에 큰 관심을 받고 있는 석유자원 중 하나이다. 오일샌드는 대부분이 캐나다 앨버타주에 분포하고 있으며 주요 저류층으로는 아스바스카(Athabasca), 콜드레이크(Cold Lake) 지역의 멕머레이층(McMurray Formation), 클리어워터층(Clearwater Formation), 그랜드래피드층(Grand Rapid Formation)과 피스리버(Peace River) 지역의 블루스카이층(Bluesky Formation), 게팅층(Gathing Formation)이 있다. 오일샌드 저류층은 고생대 탄산염 기반암 위에 하성-에스츄어리에 이르는 다양한 퇴적환경에서 형성되어 매우 복잡한 지질특성이 나타난다. 오일샌드 저류층의 효율적인 개발을 위해서는 저류층의 복잡한 지질학적 특성의 이해가 반드시 필요하다. 본 연구에서 캐나다 오일샌드 시추코어 분석 DB, 물리검층 자료, 현장 및 현생 시추코어를 통하여 오일샌드 저류층의 지질특성화 정보의 도출을 시도하였다. 우선 캐나다 앨버타 전역에 분포하는 시추공의 기본 정보(표고, 위경도, 층서별 최상부 심도, 생산광구명, 광구개발업체)를 제공하는 AccuMap DB 프로그램을 이용하여 광역적인 오일샌드 저류층의 분포 특성을 이해하고자 주요층서에 대한 고지형도 및 층후도를 생산광구별로 도면화하여 분석하였다. 또한 캐나다 ENCANA사와 국제공동연구의 일환으로 확보된 크리스티나 레이크(Christina Lake)광구의 현장 시추코어를 이용하여 코어의 상세기재, 비파괴 물성측정, 입도/비투멘 함유량 분석과 같은 다양한 실내 시추코어분석 실험을 수행 중이다. 비파괴 물성측정은 현장 시추코어의 물리적/화학적 특성을 파악하고자 MSCL(Multi sensor core logger)과 XRF 코어 스캐너(X-ray fluorescence core scaner)를 통해 이루어지며, 분석결과로 시추코어의 감마밀도(gamma density), P파 속도(P-wave velocity), 전기비저항(resistivity), 대자율(magnetic susceptibility) 및 색지수의 물성과 정량적 화학조성을 측정한다. 현장 시추코어의 일부는 유기용매를 이용하여 퇴적물 내의 비투멘을 완전히 추출하고 퇴적물 입도와 저류층 비투멘 함유량 측정에 이용되었다. 현장 시료 분석 결과들은 물리검층 자료와 대비를 통하여 저류층의 지질특성을 규명하는 연구에 이용될 예정이다. 마지막으로 오일샌드의 현생 유사 퇴적환경으로 알려진 서해 경기만 조간대에서 시추코어 퇴적물을 획득하여 상세 기재하였으며, 이를 통해 오일샌드 저류층의 퇴적 모델을 제시하고자 퇴적층서 연구를 진행 중이다. 향후 오일샌드 관련 시추코어의 분석 결과들이 종합되면 기존 보다 비투멘 회수효율을 향상시킬 수 있는 정밀한 오일샌드 저류층 지질모델을 수립할 수 있을 것으로 기대된다.

• Geophysics and Geophysical Exploration
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• v.7 no.2
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• pp.109-116
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• 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
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• v.47 no.4
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• pp.455-466
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• 2014

We investigated reservoir properties of coalbed methane and typical development of drilling, completion, and stimulation methods. We optimized selection technique for development methods by consifering characteristics of coalbed methane resercoir in the San Juan, Black Warrior and Powder River basins of United States. Finally, well-optimized development methods for coalbed methane in the Barito Basin, Indonesia are suggested. This study may be useful to select economical and efficient drilling, completion, and stimulation methods in coalbed methane development especially in Indonesia.

• The Korean Journal of Petroleum Geology
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• v.14 no.1
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• pp.12-20
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• 2008

Oil sands in Canada are representative example of unconventional resources whose reserve estimates are as large as those in Saudi Arabia. Typical reservoir rocks of oil sands consist of channel-related deposits formed in a tide-dominated depositional setting. The tidal deposits are commonly characterized by spatially complicated and heterogeneous properties. Successful engineering methods to develop oil sands require in-depth understanding in the spatial distribution of reservoir properties. Geological model for oil sand reservoir characterization can be built on the basis of comparative studies of ancient and modem analogues. In particular, modern analogue studies become increasingly indispensable, since they provide better understanding in the reservoir-rock forming process and more importantly in the external mechanism responsible for the reservoir heterogeneity. Tide-dominated environment along the west coast of Korea is considered as one of the most excellent modem analogues of oil-sand forming depositional environment. Korean tidal environment provides insights on the origin of mud breccia, facies and stratigraphic architecture which are key issues to the characterization of oil sand reservoirs.

• 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.

• Journal of the Korean Institute of Gas
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• v.23 no.3
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• pp.7-19
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• 2019

In this study, a model was developed for estimating deliverability considering the pressure dependent permeability and predicting production profile with Material Balance Equation(MBE) for Coalbed Methane(CBM) fields. The estimated deliverability was compared with the conventional deliverability based on CBM well testing data with coefficient of determination($R^2$). As a result, the former was 0.76 and the latter was 0.69. It was confirmed that the deliverability which consider the pressure dependent permeability is more adoptable when representing the productivity of CBM fields. Through this process, in order to calculate pressure dependent permeability when well testing data exist, a method to infer reservoir pressure within the radius of investigation was proposed. The production profile of 31 gas wells was predicted for 15 years, using the estimated deliverability and the MBE. After that, the results was compared with simulation results of the literature. The simulation results did not account the pressure dependent permeability and the developed model results considered that. As the applied field permeability rised 1.17 times, field production rate was increased approximately 15% than the literature results. According to other researches, the permeability of CBM fields can be rise 6 ~ 25 times. For these cases, the production profiles may have significant difference with conventional gas fields.

• The Korean Journal of Petroleum Geology
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• v.14 no.1
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• pp.1-11
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• 2008

As conventional oil and gas reservoirs become depleted, interests for oil sands has rapidly increased in the last decade. Oil sands are mixture of bitumen, water, and host sediments of sand and clay. Most oil sand is unconsolidated sand that is held together by bitumen. Bitumen has hydrocarbon in situ viscosity of >10,000 centipoises (cP) at reservoir condition and has API gravity between $8-14^{\circ}$. The largest oil sand deposits are in Alberta and Saskatchewan, Canada. The reverves are approximated at 1.7 trillion barrels of initial oil-in-place and 173 billion barrels of remaining established reserves. Alberta has a number of oil sands deposits which are grouped into three oil sand development areas - the Athabasca, Cold Lake, and Peace River, with the largest current bitumen production from Athabasca. Principal oil sands deposits consist of the McMurray Fm and Wabiskaw Mbr in Athabasca area, the Gething and Bluesky formations in Peace River area, and relatively thin multi-reservoir deposits of McMurray, Clearwater, and Grand Rapid formations in Cold Lake area. The reservoir sediments were deposited in the foreland basin (Western Canada Sedimentary Basin) formed by collision between the Pacific and North America plates and the subsequent thrusting movements in the Mesozoic. The deposits are underlain by basement rocks of Paleozoic carbonates with highly variable topography. The oil sands deposits were formed during the Early Cretaceous transgression which occurred along the Cretaceous Interior Seaway in North America. The oil-sands-hosting McMurray and Wabiskaw deposits in the Athabasca area consist of the lower fluvial and the upper estuarine-offshore sediments, reflecting the broad and overall transgression. The deposits are characterized by facies heterogeneity of channelized reservoir sands and non-reservoir muds. Main reservoir bodies of the McMurray Formation are fluvial and estuarine channel-point bar complexes which are interbedded with fine-grained deposits formed in floodplain, tidal flat, and estuarine bay. The Wabiskaw deposits (basal member of the Clearwater Formation) commonly comprise sheet-shaped offshore muds and sands, but occasionally show deep-incision into the McMurray deposits, forming channelized reservoir sand bodies of oil sands. In Canada, bitumen of oil sands deposits is produced by surface mining or in-situ thermal recovery processes. Bitumen sands recovered by surface mining are changed into synthetic crude oil through extraction and upgrading processes. On the other hand, bitumen produced by in-situ thermal recovery is transported to refinery only through bitumen blending process. The in-situ thermal recovery technology is represented by Steam-Assisted Gravity Drainage and Cyclic Steam Stimulation. These technologies are based on steam injection into bitumen sand reservoirs for increase in reservoir in-situ temperature and in bitumen mobility. In oil sands reservoirs, efficiency for steam propagation is controlled mainly by reservoir geology. Accordingly, understanding of geological factors and characteristics of oil sands reservoir deposits is prerequisite for well-designed development planning and effective bitumen production. As significant geological factors and characteristics in oil sands reservoir deposits, this study suggests (1) pay of bitumen sands and connectivity, (2) bitumen content and saturation, (3) geologic structure, (4) distribution of mud baffles and plugs, (5) thickness and lateral continuity of mud interbeds, (6) distribution of water-saturated sands, (7) distribution of gas-saturated sands, (8) direction of lateral accretion of point bar, (9) distribution of diagenetic layers and nodules, and (10) texture and fabric change within reservoir sand body.

• Geophysics and Geophysical Exploration
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• v.22 no.1
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• pp.1-11
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• 2019

Well logging technologies are used to measure the physical properties of reservoirs through boreholes. These technologies have been utilized to understand reservoir characteristics, such as porosity, fluid saturation, etc., using equations based on rock physics models. The analysis of well logs is performed by selecting a reliable rock physics model adequate for reservoir conditions or characteristics, comparing the results using the Archie's equation or simandoux method, and determining the most feasible reservoir properties. In this study, we developed a joint inversion algorithm to estimate physical properties in shaly sandstone reservoirs based on the pre-existing algorithm for sandstone reservoirs. For this purpose, we proposed a rock physics model with respect to shale volume, constructed the Jacobian matrix, and performed the sensitivity analysis for understanding the relationship between well-logging data and rock properties. The joint inversion algorithm was implemented by adopting the least-squares method using probabilistic approach. The developed algorithm was applied to the well-logging data obtained from the Colony gas sandstone reservoir. The results were compared with the simandox method and the joint inversion algorithms of sand stone reservoirs.

• Geophysics and Geophysical Exploration
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• v.26 no.4
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• pp.199-210
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• 2023

The physical properties of rocks in reservoirs change after CO₂ injection, we modeled a reservoir with a transition zone within which the physical properties change linearly. The function of the Wolf reflection coefficient consists of the velocity ratio of the upper and lower layers, the frequency, and the thickness of the transition zone. This function can be used to estimate the thickness of a reservoir or seafloor transition zone. In this study, we propose a method for predicting the thickness of the transition zone using deep learning. To apply deep learning, we modeled the thickness-dependent Wolf reflection coefficient on an artificial transition zone formation model consisting of sandstone reservoir and shale cap rock and generated time-frequency spectral images using the continuous wavelet transform. Although thickness estimation performed by comparing spectral images according to different thicknesses and a spectral image from a trace of the seismic stack did not always provide accurate thicknesses, it can be applied to field data by obtaining training data in various environments and thus improving its accuracy.