Linking land subsidence over the Yellow River delta, China, to hydrocarbon exploitation using multi-temporal InSAR

Yilin Liu (), Haijun Huang, Yanxia Liu and Haibo Bi
Additional contact information
Yilin Liu: Chinese Academy of Sciences
Haijun Huang: Chinese Academy of Sciences
Yanxia Liu: Chinese Academy of Sciences
Haibo Bi: Chinese Academy of Sciences

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2016, vol. 84, issue 1, No 16, 291 pages

Abstract: Abstract The Yellow River delta, the second largest oil and gas base of China, has been subsiding due to the combination effects of human and natural factors. Increasing anthropogenic activities, like hydrocarbon exploitation, accelerate the subsidence, gradually threatening the stability of infrastructures and causing the inhabitants more vulnerable to natural hazards. Interferometric synthetic aperture radar (InSAR) techniques can measure ground movements in high resolution. The purpose of this study is to map the spatial and temporal variations in surface deformation over the Yellow River delta using a Small Baseline Subset InSAR technique and to assess the role of hydrocarbon exploitation in subsidence. The Stanford Method for Persistent Scatterers/Multi-Temporal InSAR (StaMPS/MTI) package is employed to process ENVISAT ASAR images collected from 2007 to 2010. InSAR-derived surface deformation measurements are then compared to geological and petroleum geologic data, oil field data and hydrocarbon reservoir inversion information to address the causes of the observed subsidence. Spirit leveling data and standard deviation maps are used to verify the InSAR results and measurement accuracy. Consistent results of the two descending tracks indicate subsidence up to 40 mm/yr over oil field. The time-series deformation manifests that subsidence area and peak broaden over time and subsidence rate are approximately constant in Shikou oil field, while the rate decreases in Dongying oil field since 2009. Moreover, our results indicate that the land subsidence pattern is concentrated in hydrocarbon exploration field and has a good consistency with faults distributions. In addition, a multiple finite prolate ellipsoid sources model is implemented to model the InSAR-derived deformation in Shikou oil field. The model manifests that land subsidence and hydrocarbon exploitation can be quantitatively linked to each other. The intimate connection of surface deformation with reservoir change suggests that land subsidence over oil field in the Yellow River delta is primarily caused by hydrocarbon exploitation. The results provide new insights into the land subsidence mechanism in the Yellow River delta.

Keywords: Deltaic land subsidence; Small baseline subset–interferometric synthetic aperture radar; Oil field; Multiple finite prolate ellipsoid sources model; The Yellow River delta (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://link.springer.com/10.1007/s11069-016-2427-5 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:nathaz:v:84:y:2016:i:1:d:10.1007_s11069-016-2427-5

Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/11069

DOI: 10.1007/s11069-016-2427-5

Access Statistics for this article

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards is currently edited by Thomas Glade, Tad S. Murty and Vladimír Schenk

More articles in Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards from Springer, International Society for the Prevention and Mitigation of Natural Hazards
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().