PMID- 35962004 OWN - NLM STAT- PubMed-not-MEDLINE LR - 20220816 IS - 2045-2322 (Electronic) IS - 2045-2322 (Linking) VI - 12 IP - 1 DP - 2022 Aug 12 TI - Probabilistic analysis of water-sealed performance in underground oil storage considering spatial variability of hydraulic conductivity. PG - 13782 LID - 10.1038/s41598-022-16960-3 [doi] LID - 13782 AB - For underground water-sealed oil storage, the spatial variability of the surrounding rock has a significant impact on the water-sealed effect of a water curtain system. This study presents a methodology for the probabilistic analysis of water curtain performance in underground oil storage, considering the spatial variability of hydraulic conductivity of the surrounding rock based on field data. Anisotropic random fields representing the spatial variability of hydraulic conductivity were established through spatial statistical analysis of field data and introduced into the finite element model of underground oil storage for water-sealed reliability analysis. The water-sealed performance of different water curtain system schemes was studied using Monte Carlo simulation (MCS). The results showed that the difference between the horizontal spatial correlation and the vertical spatial correlation of the surrounding rock has a significant impact on the water-sealed effect of the water curtain system. An excessively large pressure of water curtain boreholes provided a small contribution to improving water curtain performance. The distance between the water curtain holes and the caverns had the less significant affecting the water-sealed reliability of the storage cavern. Finally, the optimal design of the water curtain system is discussed. This study provides valuable insights and a theoretical basis for the optimisation of water curtain system design parameters for underground water-sealed oil storage. CI - (c) 2022. The Author(s). FAU - Zhang, Huijie AU - Zhang H AD - School of Engineering and Technology, China University of Geosciences (Beijing), Beijing, 100083, People's Republic of China. FAU - Zhang, Bin AU - Zhang B AD - School of Engineering and Technology, China University of Geosciences (Beijing), Beijing, 100083, People's Republic of China. sc_zhb@cugb.edu.cn. FAU - Li, Yajun AU - Li Y AD - School of Engineering and Technology, China University of Geosciences (Beijing), Beijing, 100083, People's Republic of China. FAU - Wang, Lei AU - Wang L AD - Department of Civil Engineering, University of the District of Columbia, Washington, DC, 20008, USA. FAU - Li, Yutao AU - Li Y AD - School of Engineering and Technology, China University of Geosciences (Beijing), Beijing, 100083, People's Republic of China. FAU - Shi, Lei AU - Shi L AD - School of Engineering and Technology, China University of Geosciences (Beijing), Beijing, 100083, People's Republic of China. FAU - Wang, Hanxun AU - Wang H AD - School of Engineering and Technology, China University of Geosciences (Beijing), Beijing, 100083, People's Republic of China. LA - eng GR - No. 41972300, No. 41572301 and No. 40902086/National Natural Science Foundation of China/ GR - No. 2-65-2019-225, No. 2-65-2019-226/Fundamental Research Funds for the Central Universities of China/ PT - Journal Article DEP - 20220812 PL - England TA - Sci Rep JT - Scientific reports JID - 101563288 SB - IM PMC - PMC9374700 COIS- The authors declare no competing interests. EDAT- 2022/08/13 06:00 MHDA- 2022/08/13 06:01 PMCR- 2022/08/12 CRDT- 2022/08/12 23:18 PHST- 2022/02/25 00:00 [received] PHST- 2022/07/19 00:00 [accepted] PHST- 2022/08/12 23:18 [entrez] PHST- 2022/08/13 06:00 [pubmed] PHST- 2022/08/13 06:01 [medline] PHST- 2022/08/12 00:00 [pmc-release] AID - 10.1038/s41598-022-16960-3 [pii] AID - 16960 [pii] AID - 10.1038/s41598-022-16960-3 [doi] PST - epublish SO - Sci Rep. 2022 Aug 12;12(1):13782. doi: 10.1038/s41598-022-16960-3.