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Time-lapse seismic imaging, used to detect changes in strata and physical properties beneath the seafloor, plays a crucial role in traditional resource development for reservoir monitoring. It can also be used for carbon capture and storage (CCS) monitoring in the field of carbon reduction. Continuous research and development are underway in this domain. However, the application of time-lapse seismic imaging techniques to shallow strata in coastal waters near the land remains underexplored. Despite its potential in various fields, there is a lack of sufficient demonstrations and reviews of monitoring technology using downsized data acquisition techniques. This paper introduces a portable ultra-high-resolution (UHR) 3D seismic survey system designed to monitor shallow strata in coastal waters. The field applicability of this system is examined, particularly in terms of its seismic repeatability. In this study, we developed a 3D seismic survey system suitable for the operation of ships weighing 40 tons or less. The survey was conducted with a one-year time lag in waters near Pohang, Korea, close to the shore (minimum distance 1.3 km) and with low water depths (9.5 to 25.2 m). This study employed traditional time-domain processing workflows and 4D processing techniques to generate baseline and 4D processed monitoring cube. Repeatability analyses are conducted from various perspectives. Our findings demonstrate the efficient application of the proposed UHR 3D seismic survey technique for monitoring shallow media beneath the seafloor in coastal areas where diverse engineering activities and marine geology research are conducted.
Wydawca
Czasopismo
Rocznik
Tom
Strony
479--493
Opis fizyczny
Bibliogr. 41 poz.
Twórcy
autor
- Korea Institute of Geoscience and Mineral Resources, Pohang, Republic of Korea
autor
- Korea Institute of Geoscience and Mineral Resources, Pohang, Republic of Korea
autor
- Department of Geology, Kyungpook National University, 80, Daehak-Ro, Buk-Gu, Daegu, Republic of Korea
Bibliografia
- 1. Alali A, Kazei V, Sun B, Alkhalifah T (2022) Time-lapse data matching using a recurrent neural network approach. Geophysics 87:V405-V417. https://doi.Org/10.1190/geo2021-0487.1
- 2. Almutlaq M, Margrave GF (2011) Short note: shaping / matching filters. CREWES Res Rep 23:1-11
- 3. Bellwald B, Planke S, Piasecka ED, Matar MA, Andreassen K (2018) Ice-stream dynamics of the SW Barents Sea revealed by high-resolution 3D seismic imaging of glacial deposits in the Hoop area. Mar Geol 402:165-183. https://doi.org/10.1016/j.margeo.2018.03.002
- 4. Brookshire BN, Landers FP, Stein JA (2015) Applicability of ultrahigh-resolution 3D seismic data for geohazard identification at mid-slope depths in the Gulf of Mexico: Initial results. Underw Technol 32:271-278. https://doi.org/10.3723/ut.32.271
- 5. Chadwick RA, Marchant BP, Williams GA (2014) CO2 storage monitoring: leakage detection and measurement in subsurface volumes from 3D seismic data at Sleipner. Energy Procedia 63:4224-4239. https://doi.org/10.1016/j.egypro.2014.11.458
- 6. Cho Y, Jun H (2021) Estimation and uncertainty analysis of the CO2 storage volume in the sleipner field via 4D reversible-jump markov-chain Monte Carlo. J Petrol Sci Eng 200:108333. https://doi.org/10.1016/j.petrol.2020.108333
- 7. Clare M, Chaytor J, Dabson O, Gamboa D, Georgiopoulou A, Eady H, Hunt J, Jackson C, Katz O, Krastel S, León R, Micallef A, Moernaut J, Moriconi R, Moscardelli L, Mueller C, Normandeau A, Patacci M, Steventon M, Urlaub M, Volker D, Wood L, Jobe Z (2018) A consistent global approach for the morphometric characterization of subaqueous landslides. 8th Intern Symp Submar Mass Mov thier Conseq 2018:455-477. https://doi.org/10.1144/SP477.15
- 8. Dragoset B (2000) Introduction to air guns and air-gun arrays. Leading Edge (tulsa, OK) 19:892-897. https://doi.org/10.1190/1.1438741
- 9. Faggetter MJ, Vardy ME, Dix JK, Bull JM, Henstock TJ (2020) Timelapse imaging using 3D ultra-high-frequency marine seismic reflection data. Geophysics 85:P13-P25. https://doi.org/10.1190/geo2019-0258.1
- 10. Fayemendy C, Espedal PI, Andersen M, Lygren M (2012) Time-lapse seismic surveying: a multi-disciplinary tool for reservoir management on Snorre. First Break 30:10. https://doi.org/10.3997/1365-2397.2012017
- 11. Furre AK, Eiken O, Alnes H, Vevatne JN, Kiær AF (2017) 20 Years of monitoring CO2-injection at Sleipner. Energy Procedia 114:3916-3926. https://doi.org/10.1016/j.egypro.2017.03.1523
- 12. Grochau MH, Benac PM, De Magalhaes Alvim L, Sansonowski RC, Da Motta Pires PR, Villaudy F (2014) Brazilian carbonate reservoir: a successful seismic time-lapse monitoring study. Leading Edge 33:164-170. https://doi.org/10.1190/tle33020164.1
- 13. Hauptvogel, D., Sisson, V., 2023. Chapter 9: Geological Structures and Mapping, In: The Story of Earth: An Observational Guide 265-289.
- 14. Hlebnikov V, Elboth T, Vinje V, Gelius LJ (2021) Noise types and their attenuation in towed marine seismic: a tutorial. Geophysics 86:W1-W19. https://doi.org/10.1190/geo2019-0808.1
- 15. Jun H, Cho Y (2022) Repeatability enhancement of time-lapse seismic data via a convolutional autoencoder. Geophys J Int 228:1150-1170. https://doi.org/10.1093/gji/ggab397
- 16. Kang, N.K., Hwang, I.G., An, T.W., Chio, J.Y., Lee, T.H., Lee, H.S., 2019. Overview of reservoir characterization of onshore shallow gas system in Daejam-dong in Pohang, In: 2019 joint conference of the geological science & technology Korea 11
- 17. Kim, H., Kim, C., Kim, W., Shin, J., 2017. Characteristics of Airgun used in Marine Seismic Survey, In: Spring conference of the korean society of marine engineering Korean
- 18. Kragh, E., Christie, P., 2002. Seismic repeatability, normalized rms, and predictability. The Laeding Edge.
- 19. Landr0, M., Amundsen, L., 2020. Marine Seismic Sources Part I [WWW Document]. URL https://geoexpro.com/marine-seismic-sources-part-i/
- 20. Lee H-Y, Koo N-H, Kim B-Y, Kang M, Park K-P (2019) Status of Marine seismic exploration technology. J Korean Soc Miner Energy Res Eng 56:86-106. https://doi.org/10.32390/ksmer.2019.56.1.086
- 21. Meckel TA, Mulcahy FJ (2016) Use of novel high-resolution 3D marine seismic technology to evaluate Quaternary fluvial valley development and geologic controls on shallow gas distribution, inner shelf Gulf of Mexico. , Interpretation 4:SC35-SC49. https://doi.org/10.1190/INT-2015-0092.1
- 22. Missiaen T (2005) VHR marine 3D seismics for shallow water investigations: some practical guidelines. Mar Geophys Res 26:145-155. https://doi.org/10.1007/s11001-005-3708-7
- 23. Monrigal O, De Jong I, Duarte H (2017) An ultra-high-resolution 3D marine seismic system for detailed site investigation. Near Surf Geophys 15:335-345. https://doi.org/10.3997/1873-0604.2017025
- 24. Nguyen PKT, Nam MJ, Park C (2015) A review on time-lapse seismic data processing and interpretation. Geosci J 19:375-392. https://doi.org/10.1007/s12303-014-0054-2
- 25. Park M-H, Lee CS, Kim B-Y, Kim J-H, Kim KJ, Shinn YJ (2018) Preliminary results of the pre-injection monitoring survey at an offshore CO2 injection site in the Youngil bay. J Eng Geol 28:247-258. https://doi.org/10.9720/kseg.2018.2.247
- 26. Planke S, Eriksen FN, Berndt C, Mienert J, Masson D (2009) P-cable high-resolution seismic. Oceanography. https://doi.org/10.5670/oceanog.2009.09
- 27. Roach LAN, White DJ, Roberts B (2015) Assessment of 4D seismic repeatability and CO2 detection limits using a sparse permanent land array at the Aquistore CO2 storage site. Geophysics 80:WA1-WA13. https://doi.org/10.1190/GEO2014-0201.1
- 28. Robinson EA, Treitel S (2000) Geophysical signal analysis. IEEE Transac Acoust Speech, Signal Process 29:457-457. https://doi.org/10.1109/TASSP.1981.1163567
- 29. Sambo C, Iferobia CC, Babasafari AA, Rezaei S, Akanni OA (2020) The role of time lapse(4D) seismic technology as reservoir monitoring and surveillance tool: a comprehensive review. J Nat Gas Sci Eng 80:103312. https://doi.org/10.1016/j.jngse.2020.103312
- 30. Scheidhauer M, Marillier F, Dupuy D (2005) Development of a system for 3D high-resolution seismic reflection profiling on lakes. Mar Geophys Res 26:183-195. https://doi.org/10.1007/s11001-005-3717-6
- 31. Sengupta M, Mavko G, Mukerji T (2003) Quantifying subresolution saturation scales from time-lapse seismic data: a reservoir moni¬toring case study. Geophysics 68:803-814. https://doi.org/10.1190/1.1581033
- 32. Shin J, Ha J, Kang N-K, Kim H-D, Kim C-S (2021) Development of a portable 3D seismic survey system for nearshore surveys and the first case study offshore Pohang South Korea. , Mar Geophy Res 1:16. https://doi.org/10.1007/s11001-021-09453-x
- 33. Shin J, Ha J, Lim K (2024) Application of broadcast RTK for automated static correction in 3D sub-bottom profiling. Acta Geophys. https://doi.org/10.1007/s11600-024-01371-x
- 34. Shin J, Kim H, Kim W, Kang D, Kim C, Park C, Jeong J (2020) Seismic imaging offshore pohang using small-boat ultra-high-resolution 3d seismic survey. J Seism Explor 29:125-138
- 35. Smith P, Mattox B (2020) A time-lapse seismic repeatability test using the P-Cable high-resolution 3D marine acquisition system. Lead Edge 39:480-487. https://doi.org/10.1190/tle39070480.1
- 36. Synerex, 2023. Broadcast RTK [WWW Document]. URL https://www.synerex.kr/broadcast-rtk
- 37. Um ES, Alumbaugh D, Lin Y, Feng S (2024) Real-time deep-learning inversion of seismic full waveform data for CO2 saturation and uncertainty in geological carbon storage monitoring. Geophys Prospect 72:199-212
- 38. Vendanti, N., Pathak, A., Srivastava, R.P., Dimri, V.P., 2009. Time Lapse (4D) Seismic: Some Case Studies. Earth Science India 2.
- 39. Waage M, Bunz S, Landr0 M, Plaza-Faverola A, Waghorn KA (2019) Repeatability of high-resolution 3D seismic data. Geophysics 84:B75-B94. https://doi.org/10.1190/geo2018-0099.1
- 40. Yilmaz, O., 2001. Seismic data analysis.
- 41. Yuan C, Zhang X, Jia X, Zhang J (2020) Time-lapse velocity imaging via deep learning. Geophys J Int 220:1228-1241. https://doi.org/10.1093/gji/ggz511
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-e01c37f6-e56c-4d5c-ae20-6d924374862c
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