Land subsidence over oilfields in the Yellow River Delta

Liu, P., Li, Q., Li, Z., Hoey, T. , Liu, Y. and Wang, C. (2015) Land subsidence over oilfields in the Yellow River Delta. Remote Sensing, 7(2), pp. 1540-1564. (doi: 10.3390/rs70201540)

Abstract

Subsidence in river deltas is a complex process that has both natural and human causes. Increasing human activities like aquaculture and petroleum extraction are affecting the Yellow River delta, and one consequence is subsidence. The purpose of this study is to measure the surface displacements in the Yellow River delta region and to investigate the corresponding subsidence source. In this paper, the Stanford Method for Persistent Scatterers (StaMPS) package was employed to process Envisat ASAR images collected between 2007 and 2010. Consistent results between two descending tracks show subsidence with a mean rate up to 30 mm/yr in the radar line of sight direction in Gudao Town (oilfield), Gudong oilfield and Xianhe Town of the delta, each of which is within the delta, and also show that subsidence is not uniform across the delta. Field investigation shows a connection between areas of non-uniform subsidence and of petroleum extraction. In a 9 km2 area of the Gudao Oilfield, a poroelastic disk reservoir model is used to model the InSAR derived displacements. In general, good fits between InSAR observations and modeled displacements are seen. The subsidence observed in the vicinity of the oilfield is thus suggested to be caused by fluid extraction.

• Item Type: Articles
• Keywords: Remote Sensing; InSAR; subsidence
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Li, Dr Zhenhong and Hoey, Professor Trevor
• Authors: Liu, P., Li, Q., Li, Z., Hoey, T., Liu, Y., and Wang, C.
• Subjects: G Geography. Anthropology. Recreation > GE Environmental Sciences; Q Science > QE Geology
• College/School: College of Science and Engineering > School of Geographical and Earth Sciences > Earth Sciences
• Journal Name: Remote Sensing
• Publisher: MDPI AG
• ISSN: 2072-4292
• ISSN (Online): 2072-4292
• Copyright Holders: Copyright © 2015 The Authors
• First Published: First published in Remote Sensing 7(2):1540-1564
• Publisher Policy: Reproduced under a Creative Commons License