Ground Deformation Monitoring at Natural Gas Production Sites using - - PowerPoint PPT Presentation

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Ground Deformation Monitoring at Natural Gas Production Sites using - - PowerPoint PPT Presentation

Ground Deformation Monitoring at Natural Gas Production Sites using Interferometric SAR By: Kanika Goel, Robert Shau, Fernando Rodriguez Gonzalez, Nico Adam Remote Sensing Technology Institute (IMF), German Aerospace Center (DLR), Germany


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Ground Deformation Monitoring at Natural Gas Production Sites using Interferometric SAR

By: Kanika Goel, Robert Shau, Fernando Rodriguez Gonzalez, Nico Adam Remote Sensing Technology Institute (IMF), German Aerospace Center (DLR), Germany

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Introduction

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Natural gas production has increased significantly to meet energy demands

Extraction leads to decreased reservoir pressure and may cause subsidence

Monitoring this subsidence important for geological and hazard analysis

Motivation

Ground deformation illustration

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Small volumes produced as compared internationally

In 2007, 17% domestic consumption from domenstic production

Lower-Saxony accounted for 93% of German natural gas production

BGR, Germany, collaborating with DLR for monitoring subsidence due to natural gas extraction

Natural Gas in Germany

Source: BGR, Germany

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Powerful remote sensing technique for detecting ground deformation

Deformation estimation using 2 SAR images and Digital Elevation Model (DEM)

Interferogram phase contributions:

Interferometric SAR (InSAR)

Deformation

m s

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Medium resolution of 25 m

5.6 cm wavelength

100 km swath width

C-Band SAR

ERS

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High resolution of up to 1 m

3.1 cm wavelength

High sensitivity to even millimetric displacements

X-Band SAR

TerraSAR-X (TSX)

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Methodology

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Persistent Scatterer Interferometry (PSI)

Coherent InSAR stacking technique

Permanently coherent PSs exploited

Differential interferograms wrt a single master image used

Model-based deformation estimation

PS

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DLR‘s Integrated Wide Area Processor (IWAP)

Highly automated, efficient and robust multi-sensor PSI-GENESIS software

Successful demonstration and validation during ESA's Terrafirma project

Greece Turkey Source: Rodriguez Gonzalez et al., 2013

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PSI Algorithm

PSs Detection PSs Reference Network Estimation Atmospheric Phase Screen (APS) Estimation and Removal PSs Final Network Estimation

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PSI Algorithm

PSs Detection PSs Reference Network Estimation Atmospheric Phase Screen (APS) Estimation and Removal PSs Final Network Estimation

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PSs Reference Network Estimation- Block Processing

Division of scene into overlapping blocks

Blockwise creation of reference network (arcs connecting the PSs)

Blockwise estimation of relative deformation and residual DEM for the arcs using LAMBDA estimator

Blockwise network inversion to estimate deformation and residual DEM for the PSs using least squares

Merging of independently estimated blocks via least squares adjustment

Illustration of block adjustment network Developed by: Werner Liebhart

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PSs Reference Network Estimation- Single Network

Creation of reference network (arcs connecting the PSs)

Estimation of relative deformation and residual DEM for the arcs using LAMBDA estimator

Single network inversion to estimate deformation and residual DEM for the PSs using least squares Mitigates error propagation High computational load and memory consumption

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Sinlge network inversion- Strategies:

Solve A x = B => AT A x = AT B

AT A is symmetric positive definite square matrix

Exploit sparsity of A => AT A

Use QR or LU decomposition for fast inversion, instead of SVD decomposition

Use a parallelizable solver

Estimate deformation, residual DEM and standard deviation of estimates

PSs Reference Network Estimation- Single Network

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PSs Reference Network Estimation- Single Network

Example matrix A dimensions:

TerraSAR-X Stripmap: Size(A) = (30000, 600000)

ERS: Size(A) = (90000, 1800000)

Sentinel-1: Size(A) = (450000, 9000000)

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PSs Reference Network Estimation- Single Network

Example matrix A dimensions:

TerraSAR-X Stripmap: Size(A) = (30000, 600000)

ERS: Size(A) = (90000, 1800000)

Sentinel-1: Size(A) = (450000, 9000000) Example matrix ATA dimensions:

TerraSAR-X Stripmap: Size(ATA) = (30000, 30000)

ERS: Size(ATA) = (90000, 90000)

Sentinel-1: Size(ATA) = (450000, 450000)

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Application Test Case and Results

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TSX Data- Ascending Stripmap Stack

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Time – Baseline Plot

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Master Amplitude Image

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Interferogram Examples

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Deformation Estimation Results

  • 5 [mm/Jahr] +5
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Area A

Deformation Time Series Example

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PSs Reference Network Estimation- Block Processing

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PSs Reference Network Estimation- Block Processing

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PSs Reference Network Estimation- Block Processing

Residual topography Deformation

  • 20

+20

  • 5

+5 mm mm/yr

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PSs Reference Network Estimation- Single Network

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+20

  • 5

+5 mm mm/yr Residual topography Deformation

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PSs Reference Network Estimation- Difference

  • 20

+20

  • 5

+5 mm mm/yr Residual topography Deformation

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PSs Reference Network Estimation- Deformation Variance

0.01 0.1 (mm/yr)2 (mm/yr)2 Block processing Single network

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Summary

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Conclusion and Outlook

PSI powerful and cost-effective tool for monitoring the impact of hydrocarbon reservoirs

Single reference network inversion has potential to improve the deformation velocity maps

Comparison with GPS data would be performed in the future to validate the pilot study

Sentinel-1 data would be acquired for large area monitoring

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Thank you… Any questions? Sentinel-1

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PSs Reference Network Estimation- Scatter Plot

Residual topography Deformation

  • > Block processing
  • > Single Network
  • > Block processing
  • > Single Network
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PSs Reference Network Estimation- Scatter Plot

Residual topography Deformation

  • > Block processing
  • > Single Network
  • > Block processing
  • > Single Network