Quantifying Two-Dimensional Surface Displacements Using High-Resolution Cosmo-SkyMed, TerraSAR-X and Medium-Resolution Sentinel-1 SAR Interferometry: Case Study for the Tengiz Oilfield

The present study was aimed at comparing vertical and horizontal surface displacements derived from the Cosmo-SkyMED, TerraSAR-X and Sentinel-1 satellite missions for the detection of oil extraction-induced subsidence in the Tengiz oilfield during 2018–2021. The vertical and horizontal surface displacements were derived using the 2D decomposition of line-of-sight measurements from three satellite missions. Since the TerraSAR-X mission was only available from an ascending track, it was successfully decomposed by combining it with the Cosmo-SkyMED descending track. Vertical displacement velocities derived from 2D Decomposition showed a good agreement in similar ground motion patterns and an average regression coefficient of 0.98. The maximum average vertical subsidence obtained from the three satellite missions was observed to be −57 mm/year. Higher variations and deviations were observed for horizontal displacement velocities in terms of similar ground motion patterns and an average regression coefficient of 0.80. Fifteen wells and three facilities were observed to be located within the subsidence range between −55.6 mm/year and −42 mm/year. The spatial analyses in the present studies allowed us to suspect that the subsidence processes occurring in the Tengiz oilfield are controlled not solely by oil production activities since it was clearly observed from the detected horizontal movements. The natural tectonic factors related to two seismic faults crossing the oilfield, and terrain characteristics forming water flow towards the detected subsidence hotspot, should also be considered as ground deformation accelerating factors. The novelty of the present research for Kazakhstan’s Tengiz oilfield is based on the cross-validation of vertical and horizontal surface displacement measurements derived from three radar satellite missions, 2D Decomposition of Cosmo-SkyMED descending and TerraSAR-X ascending line-of-sight measurements and spatial analysis of man-made and natural factors triggering subsidence processes.

[1]  Zhenkai Zhou,et al.  Study of the Automatic Recognition of Landslides by Using InSAR Images and the Improved Mask R-CNN Model in the Eastern Tibet Plateau , 2022, Remote. Sens..

[2]  C. Serio,et al.  Change Detection Techniques with Synthetic Aperture Radar Images: Experiments with Random Forests and Sentinel-1 Observations , 2022, Remote. Sens..

[3]  M. Buchroithner,et al.  Multi-Temporal SAR Interferometry for Vertical Displacement Monitoring from Space of Tengiz Oil Reservoir Using SENTINEL-1 and COSMO-SKYMED Satellite Missions , 2022, Frontiers in Environmental Science.

[4]  H. Hashemi,et al.  An Integrated InSAR-Machine Learning Approach for Ground Deformation Rate Modeling in Arid Areas , 2022, Journal of Hydrology.

[5]  Manfred F. Buchroithner,et al.  Quantitative Assessment of Vertical and Horizontal Deformations Derived by 3D and 2D Decompositions of InSAR Line-of-Sight Measurements to Supplement Industry Surveillance Programs in the Tengiz Oilfield (Kazakhstan) , 2021, Remote. Sens..

[6]  John Richard Otukei,et al.  Estimation of Ground Vertical Displacement in Landslide Prone Areas Using PS-InSAR. A Case Study of Bududa, Uganda , 2021, International Journal of Geosciences.

[7]  W. Barnhart,et al.  Identification of Surface Deformation in InSAR Using Machine Learning , 2021, Geochemistry, Geophysics, Geosystems.

[8]  Thu Trang Lê,et al.  Quantifying Horizontal and Vertical Movements in Ho Chi Minh City by Sentinel-1 Radar Interferometry , 2020 .

[9]  Vera Rocca,et al.  Multidisciplinary Analysis of Ground Movements: An Underground Gas Storage Case Study , 2020, Remote. Sens..

[10]  R. Reedy,et al.  InSAR Reveals Complex Surface Deformation Patterns Over an 80,000 km2 Oil‐Producing Region in the Permian Basin , 2020, Geophysical Research Letters.

[11]  M. Buchroithner,et al.  Quantitative assessment of ground deformation risks, controlling factors and movement trends for onshore petroleum and gas industry using satellite Radar remote sensing and spatial statistics , 2020, Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards.

[12]  Y. Maghsoudi,et al.  Extreme subsidence in a populated city (Mashhad) detected by PSInSAR considering groundwater withdrawal and geotechnical properties , 2020, Scientific Reports.

[13]  David Bull,et al.  Detecting Ground Deformation in the Built Environment Using Sparse Satellite InSAR Data With a Convolutional Neural Network , 2020, IEEE Transactions on Geoscience and Remote Sensing.

[14]  Andrzej Borkowski,et al.  Integration of DInSAR and SBAS Techniques to Determine Mining-Related Deformations Using Sentinel-1 Data: The Case Study of Rydułtowy Mine in Poland , 2020, Remote. Sens..

[15]  Ioannis Papoutsis,et al.  Multi-Temporal InSAR Analysis for Monitoring Ground Deformation in Amorgos Island, Greece † , 2020, Sensors.

[16]  Thomas Fuhrmann,et al.  Surface Deformation from Sentinel-1A InSAR: Relation to Seasonal Groundwater Extraction and Rainfall in Central Taiwan , 2019, Remote. Sens..

[17]  N. Anantrasirichai,et al.  The Application of Convolutional Neural Networks to Detect Slow, Sustained Deformation in InSAR Time Series , 2019, Geophysical Research Letters.

[18]  Andrew Sowter,et al.  Delineating ground deformation over the Tengiz oil field, Kazakhstan, using the Intermittent SBAS (ISBAS) DInSAR algorithm , 2019, Int. J. Appl. Earth Obs. Geoinformation.

[19]  Ruiqi Sun,et al.  Ground Deformation Revealed by Sentinel-1 MSBAS-InSAR Time-Series over Karamay Oilfield, China , 2019, Remote. Sens..

[20]  Deodato Tapete,et al.  COSMO-SkyMed SAR for Detection and Monitoring of Archaeological and Cultural Heritage Sites , 2019, Remote. Sens..

[21]  Gokhan Aslan.  MONITORING OF SURFACE DEFORMATION IN NORTHWEST TURKEY FROM HIGH-RESOLUTION INSAR : FOCUS ON TECTONIC ASEISMIC SLIP AND SUBSIDENCE , 2019 .

[22]  Thomas Fuhrmann,et al.  Resolving Three-Dimensional Surface Motion with InSAR: Constraints from Multi-Geometry Data Fusion , 2019, Remote. Sens..

[23]  Gokhan Aslan,et al.  Investigating Subsidence in the Bursa Plain, Turkey, Using Ascending and Descending Sentinel-1 Satellite Data , 2019, Remote. Sens..

[24]  Li Zhou,et al.  Study of subsidence monitoring in Nanjing City with small-baseline InSAR approach , 2019, Geomatics, Natural Hazards and Risk.

[25]  Yang Liu,et al.  InSAR Monitoring and Analysis of Ground Deformation Due to Fluid or Gas Injection in Fengcheng Oil Field, Xinjiang, China , 2018, Journal of the Indian Society of Remote Sensing.

[26]  Y. S. Rao,et al.  TIME SERIES ANALYSIS OF SURFACE DEFORMATION OF BENGALURU CITY USING SENTINEL-1 IMAGES , 2018, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences.

[27]  H. Hassan,et al.  Compaction and Subsidence Assessment to Optimize Field Development Planning for an Oil Field in Sultanate of Oman , 2018, Day 3 Wed, November 14, 2018.

[28]  Lorenzo Bruzzone,et al.  Sentinel-1 and Ground-Based Sensors for Continuous Monitoring of the Corvara Landslide (South Tyrol, Italy) , 2018, Remote. Sens..

[29]  K. Tiampo,et al.  Modeling the two- and three-dimensional displacement field in Lorca, Spain, subsidence and the global implications , 2018, Scientific Reports.

[30]  I. Cheng,et al.  CNN-based InSAR Coherence Classification , 2018, 2018 IEEE SENSORS.

[31]  Joseph A. C. Delaney.  Sensitivity analysis , 2018, The African Continental Free Trade Area: Economic and Distributional Effects.

[32]  Vasit Sagan,et al.  SBAS Analysis of Induced Ground Surface Deformation from Wastewater Injection in East Central Oklahoma, USA , 2018, Remote. Sens..

[33]  Wen Liu,et al.  Monitoring of Land-Surface Deformation in the Karamay Oilfield, Xinjiang, China, Using SAR Interferometry , 2017 .

[34]  Magaly Koch,et al.  Minimizing the Residual Topography Effect on Interferograms to Improve DInSAR Results: Estimating Land Subsidence in Port-Said City, Egypt , 2017, Remote. Sens..

[35]  M. Allan,et al.  InSAR: Pro-Active Technology for Monitoring Environmental Safety and for Reservoir Management , 2017 .

[36]  S. Roessner,et al.  Quantifying groundwater exploitation induced subsidence in the Rafsanjan plain, southeastern Iran, using InSAR time-series and in situ measurements , 2017 .

[37]  Stuart Marsh,et al.  Monitoring land motion due to natural gas extraction: Validation of the Intermittent SBAS (ISBAS) DInSAR algorithm over gas fields of North Holland, the Netherlands , 2016 .

[38]  A. McCardle,et al.  Operational mine monitoring with InSAR , 2016 .

[39]  C. Janna,et al.  Efficient global optimization of reservoir geomechanical parameters based on synthetic aperture radar-derived ground displacements , 2016 .

[40]  Mehrez Zribi,et al.  Signal Level Comparison Between TerraSAR-X and COSMO-SkyMed SAR Sensors , 2015, IEEE Geoscience and Remote Sensing Letters.

[41]  A. Ferretti,et al.  Advanced InSAR Technology for Reservoir Monitoring and Geomechanical Model Calibration , 2013 .

[42]  Zhumabek Zhantayev.  USING OF SAR DATA AND PSINSAR TECHNIQUE FOR MONITORING OF GROUND DEFORMATION IN WESTERN KAZAKHSTAN , 2013 .

[43]  Emanuele Santi,et al.  The Intercomparison of X-Band SAR Images from COSMO-SkyMed and TerraSAR-X Satellites: Case Studies , 2013, Remote. Sens..

[44]  Fabio Rocca,et al.  Advanced InSAR interferometry for reservoir monitoring , 2013 .

[45]  P. Fokker,et al.  Inversion of surface subsidence data to quantify reservoir compartmentalization: A field study , 2012 .

[46]  Fabrizio Novali,et al.  Retrieving surface deformation by PSInSAR™ technology: A powerful tool in reservoir monitoring , 2009 .

[47]  Andrew Hooper,et al.  Phase unwrapping in three dimensions with application to InSAR time series. , 2007, Journal of the Optical Society of America. A, Optics, image science, and vision.

[48]  Sam Holloway,et al.  Natural emissions of CO2 from the geosphere and their bearing on the geological storage of carbon dioxide , 2007 .

[49]  Paolo Berardino,et al.  Surface deformation of Long Valley caldera and Mono Basin, California, investigated with the SBAS-InSAR approach , 2007 .

[50]  Yuri Fialko,et al.  Interseismic strain accumulation and the earthquake potential on the southern San Andreas fault system , 2006, Nature.

[51]  Urs Wegmüller,et al.  Interferometric point target analysis of RADARSAT-1 data for deformation monitoring at the Belridge/Lost Hills oil fields , 2004, IGARSS 2004. 2004 IEEE International Geoscience and Remote Sensing Symposium.

[52]  Michele Manunta,et al.  A small-baseline approach for investigating deformations on full-resolution differential SAR interferograms , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[53]  Gianfranco Fornaro,et al.  A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms , 2002, IEEE Trans. Geosci. Remote. Sens..

[54]  W. Keydel,et al.  Shuttle Radar Topography Mission , 2000 .

[55]  O. Merkulov,et al.  Tengiz oilfield: geological model based on hydrodynamic data , 1998, Petroleum Geoscience.

[56]  Markus Even,et al.  Complex Surface Displacements above the Storage Cavern Field at Epe, NW-Germany, Observed by Multi-Temporal SAR-Interferometry , 2020, Remote. Sens..

[57]  Fatih Kahraman,et al.  Ground Deformation Analysis of Bolvadin (W. Turkey) by Means of Multi-Temporal InSAR Techniques and Sentinel-1 Data , 2019, Remote. Sens..

[58]  A. Ferretti,et al.  Impact of high resolution radar imagery on reservoir monitoring , 2011 .

[59]  W. T. Peake,et al.  Tengiz Reservoir Uncertainty Characterization and Modeling , 2010 .

[60]  Wendy Zhou,et al.  InSAR Application in Detection of Oilfield Subsidence on Alaska North Slope , 2006 .

[61]  R. Reulke,et al.  Remote Sensing and Spatial Information Sciences , 2005 .

[62]  N. Nagel.  Compaction and subsidence issues within the petroleum industry: From wilmington to ekofisk and beyond , 2001 .