Core and sediment physical property correlation of the second Ulleung Basin Gas Hydrate Drilling Expedition (UBGH2) results in the East Sea (Japan Sea)

Horozal, Senay; Kim, Gil Young; Bahk, Jang-Jun; Wilkens, Roy H; Yoo, Dong Geun; Ryu, Byong Jae; Kim, Seong Pil

doi:10.1016/j.marpetgeo.2014.09.019

Cited by 7 publications

(3 citation statements)

References 31 publications

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“…일례로, 국내 동해 울릉분지에 위 치한 가스하이드레이트 부존층(Ulleung basin gas hydrate, UBGH)의 경우 가스하이드레이트가 두꺼운 층을 이루는 형태가 아닌 퇴적층 내에 얇게 산재된 형태의 분포양상을 보이기 때문에 가스하이드레이트 매장량이 과대평가 혹은 과소평가 될 수 있는 우려가 있다 (Kim, 2012). Horozal et al(2015)은 코어 이미지를 바탕으로 가스하이드레이트가 사질층(muddy sand) 또는 머드층(sandy mud)에 0.5 m보 다 얇은 두께로 존재함을 확인하였다. Kim (Wyllie et al, 1958;Schlumberger, 1967;Gaymard and Poupon, 1968;Bateman, 1986;Lee and Collett, 2011) 검층 자료를 입력자료로 사용하여 q종류의 저류층 인자를 출력한다.…”

Section: 서 론unclassified

Generation of High-Resolution Well Log Data by Using a Deep-Learning Algorithm

Park¹,

Kwon²,

Ji³

et al. 2022

J. Korean Soc. Miner. Energy Resour. Eng.

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This study proposed a deep-learning-based approach that generates synthetic high-resolution log data from original-resolution log data for accurate reservoir characterization, where the resolution of the synthetic data is comparable to that of core data. The reliability of the proposed approach was tested with application to the Volve oil field in Norway using three deep-learning algorithms (i.e., deep neural network, convolutional neural network, and long short-term memory). These deep-learning algorithms were employed to generate high-resolution sonic log data from other log-type data. The overall performance of each algorithm was acceptable. In particular, the long short-term memory algorithm yields a coefficient of determination greater than 0.9 when the high-to-original-resolution ratios are two, five, and ten. We anticipate that the proposed model can be used to derive logging-based reservoir parameters with a resolution that is comparable to that of core-based reservoir parameters.

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Section: 서 론unclassified

Generation of High-Resolution Well Log Data by Using a Deep-Learning Algorithm

Park¹,

Kwon²,

Ji³

et al. 2022

J. Korean Soc. Miner. Energy Resour. Eng.

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“…Gas hydrates are widely distributed in the marine sediments and permafrost and formed in low-temperature and highpressure conditions (Kvenvolden, 1993;Sloan & Koh, 2007). Extensive gas hydrate drilling sites show that gas hydrates have different morphologies and high saturation within the coarse-grained sand reservoirs, which show the high amplitude reflections and the same polarity as the seafloor reflections (Boswell et al, 2016;Collett et al, 2019;Cook & Malinverno, 2013;Cook & Waite, 2018;Fujii et al, 2015;Horozal et al, 2015;Portnov et al, 2019). Sand-rich reservoirs with high saturations are widely identified in the thin or thick channel-levee systems, such as the Gulf of Mexico (Meazell et al, 2020;Santra et al, 2020), the Krishna-Godavari Basin (Collett et al, 2019), the Nankai Trough (Fujii et al, 2009(Fujii et al, , 2015, the Hikurangi margin, New Zealand (Cook et al, 2020;Pecher et al, 2018;Pan et al, 2022) and the Ulleung Basin (Horozal et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

“…Extensive gas hydrate drilling sites show that gas hydrates have different morphologies and high saturation within the coarse-grained sand reservoirs, which show the high amplitude reflections and the same polarity as the seafloor reflections (Boswell et al, 2016;Collett et al, 2019;Cook & Malinverno, 2013;Cook & Waite, 2018;Fujii et al, 2015;Horozal et al, 2015;Portnov et al, 2019). Sand-rich reservoirs with high saturations are widely identified in the thin or thick channel-levee systems, such as the Gulf of Mexico (Meazell et al, 2020;Santra et al, 2020), the Krishna-Godavari Basin (Collett et al, 2019), the Nankai Trough (Fujii et al, 2009(Fujii et al, , 2015, the Hikurangi margin, New Zealand (Cook et al, 2020;Pecher et al, 2018;Pan et al, 2022) and the Ulleung Basin (Horozal et al, 2015). Gas hydrates are identified from core samples and logging data showing the occurrences in the centimetre-thick thin sand reservoir with low-to-moderate saturation at Sites U1518 (Cook et al, 2020) and U1517 (Pecher et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Identification of interbedded gas hydrate and free gas using amplitude versus offset forward modelling

Liu

Wang

et al. 2023

Geophysical Prospecting

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The complex contacts between gas hydrate and free gas have been confirmed by gas hydrate pilot production in the Pearl River Mouth Basin, South China Sea. The laminated clay silt reservoirs have high amplitude reflections which may be filled with different saturations of gas hydrates, free gas and the coexistence between gas hydrate and free gas. To distinguish the variations of amplitude reflections caused by different reservoirs properties below the bottom simulating reflection, we combine the forward modelling, pre‐stack gathers with different incident angles and well log analysis to conduct the seismic responses. A number of geological models are established with variable saturations and different interfaces between gas hydrate and free gas. First, we analyse the seismic and well log responses at Sites W11, W01 and W17 near the production test area. Then, we perform the forward modelling to quantify the differences among seismic reflections with different saturations, thickness, incident angles and strata dips in free gas‐ or gas hydrate‐bearing geological models. We extract the seismic amplitudes along the bottom simulating reflection and other layers to compare with the amplitudes generated from forward modelling. The results indicate that the inclined intervals below the bottom simulating reflection have high amplitude, continuous reflection and polarity reversal which may be caused by thin gas reservoir and the interlayered gas hydrate and free gas with different saturations. The top interfaces of the gas hydrate‐ and free gas‐bearing layers show typical Class III amplitude versus offset and exhibit high amplitude reflections at seismic data with near, mid and far‐incident angles, which are easy to distinguish. Seismic response of far‐incident angle can be used to identify the coexistence of gas hydrate and free gas.

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Patterns of gas hydrate accumulation in mass transport deposits related to canyon activity: Example from Shenhu drilling area in the South China Sea

et al. 2019

Acta Oceanol. Sin.

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Core and sediment physical property correlation of the second Ulleung Basin Gas Hydrate Drilling Expedition (UBGH2) results in the East Sea (Japan Sea)

Cited by 7 publications

References 31 publications

Generation of High-Resolution Well Log Data by Using a Deep-Learning Algorithm

Generation of High-Resolution Well Log Data by Using a Deep-Learning Algorithm

Identification of interbedded gas hydrate and free gas using amplitude versus offset forward modelling

Patterns of gas hydrate accumulation in mass transport deposits related to canyon activity: Example from Shenhu drilling area in the South China Sea

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