Subsidence rate monitoring of Aghajari oil field based on Differential SAR Interferometry

Moghaddam, Negin Fouladi; Sahebi, Mahmod Reza; Matkan, A A; Roostaei, Mahasa

doi:10.1016/j.asr.2013.01.023

Cited by 11 publications

(4 citation statements)

References 7 publications

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“…In recent years, land subsidence caused by the extraction of natural resources such as groundwater [ 1 , 2 ], oil [ 3 ] and coal [ 4 , 5 ] has created severe and widespread hazards in China, resulting in new ecological and environmental issues such as soil degradation and loss of biodiversity. Nitrogen is necessary for all known forms of life on Earth, being present in the environment in a wide variety of chemical forms including organic nitrogen, ammonium, nitrite and nitrate.…”

Section: Introductionmentioning

confidence: 99%

Hyperspectral Analysis of Soil Total Nitrogen in Subsided Land Using the Local Correlation Maximization-Complementary Superiority (LCMCS) Method

Lin

Wang

Teng

et al. 2015

Sensors

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The measurement of soil total nitrogen (TN) by hyperspectral remote sensing provides an important tool for soil restoration programs in areas with subsided land caused by the extraction of natural resources. This study used the local correlation maximization-complementary superiority method (LCMCS) to establish TN prediction models by considering the relationship between spectral reflectance (measured by an ASD FieldSpec 3 spectroradiometer) and TN based on spectral reflectance curves of soil samples collected from subsided land which is determined by synthetic aperture radar interferometry (InSAR) technology. Based on the 1655 selected effective bands of the optimal spectrum (OSP) of the first derivate differential of reciprocal logarithm ([log{1/R}]′), (correlation coefficients, p < 0.01), the optimal model of LCMCS method was obtained to determine the final model, which produced lower prediction errors (root mean square error of validation [RMSEV] = 0.89, mean relative error of validation [MREV] = 5.93%) when compared with models built by the local correlation maximization (LCM), complementary superiority (CS) and partial least squares regression (PLS) methods. The predictive effect of LCMCS model was optional in Cangzhou, Renqiu and Fengfeng District. Results indicate that the LCMCS method has great potential to monitor TN in subsided lands caused by the extraction of natural resources including groundwater, oil and coal.

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Section: Introductionmentioning

confidence: 99%

Hyperspectral Analysis of Soil Total Nitrogen in Subsided Land Using the Local Correlation Maximization-Complementary Superiority (LCMCS) Method

Lin

Wang

Teng

et al. 2015

Sensors

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“…Supported by accessible satellite datasets and by the flourishing of software packages, subsidence monitoring is feasible worldwide (Cian et al, 2019) covering a wide range of scenarios: deltaic environment (Parcharidis et al, 2013), tunnel excavation advancement (Roccheggiani et al, 2019;Strozzi et al, 2017), land reclamation (Sun et al, 2018), peat settlement (Marshall et al, 2018), natural gas (Gee et al, 2016) and oil extraction (Moghaddam et al, 2013) and civil infrastructures analysis Corsetti et al, 2018;Luo et al, 2017).…”

Section: Monitoringmentioning

confidence: 99%

Review of satellite radar interferometry for subsidence analysis

Raspini

Caleca²,

Soldato³

et al. 2022

Earth-Science Reviews

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“…MT-InSAR has been successfully and extensively used in monitoring the deformations Remote Sens. 2017, 9, 1129 2 of 22 induced by exploitation of underground fluids, such as groundwater [7,[14][15][16][17][18][19][20][21], oil [22][23][24][25][26][27][28][29][30][31], natural gas [14,30,[32][33][34][35][36][37], and geothermal [38][39][40][41][42][43][44][45], because of its low cost, wide spatial coverage, high measurement precision, and fine spatial resolution. However, MT-InSAR can capture only one-dimensional (1-D) time-series deformation that includes the sum of projections on the line-of-sight (LOS) direction of actual 3-D time series ground deformations.…”

Section: Introductionmentioning

confidence: 99%

Deriving 3-D Time-Series Ground Deformations Induced by Underground Fluid Flows with InSAR: Case Study of Sebei Gas Fields, China

Liu

Sun

et al. 2017

Remote Sensing

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Multi-temporal Interferometric Synthetic Aperture Radar (MT-InSAR) technique has proven to be a powerful tool for the monitoring of time-series ground deformations along the line-of-sight (LOS) direction. However, the one-dimensional (1-D) measurements cannot provide comprehensive information for interpreting the related geo-hazards. Recently, a novel method has been proposed to map the three-dimensional (3-D) deformation associated with underground fluid flows based on single-track InSAR LOS measurements and the deformation modeling associated with the Green's function. In this study, the method is extended in temporal domain by exploiting the MT-InSAR measurements, and applied for the first time to investigate the 3-D time series deformation over Sebei gas field in Qinghai, Northwest China with 37 Sentinel-1 images acquired during October 2014-July 2017. The estimated 3-D time series deformations provide a more complete view of ongoing deformation processes as compared to the 1-D time series deformations or the 3-D deformation velocities, which is of great importance for assessing the possible geohazards. In addition, the extended method allows for the retrieval of time series of fluid volume changes due to the gas extraction in the Sebei field, which agrees well with those from the PetroChina Qinghai Oilfield Company Yearbooks (PQOCYs). This provides a new way to study the variations of subsurface fluids at unprecedented resolution.

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Subsidence rate monitoring of Aghajari oil field based on Differential SAR Interferometry

Cited by 11 publications

References 7 publications

Hyperspectral Analysis of Soil Total Nitrogen in Subsided Land Using the Local Correlation Maximization-Complementary Superiority (LCMCS) Method

Hyperspectral Analysis of Soil Total Nitrogen in Subsided Land Using the Local Correlation Maximization-Complementary Superiority (LCMCS) Method

Review of satellite radar interferometry for subsidence analysis

Deriving 3-D Time-Series Ground Deformations Induced by Underground Fluid Flows with InSAR: Case Study of Sebei Gas Fields, China

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