Multi-Sensor Satellite Processing for the Monitoring of Geo-energies

Ground deformation related to geo-energy activities is often caused by subsurface fluid injection and extraction, making reliable monitoring essential for understanding reservoir behavior and managing associated risks. Interferometric Synthetic Aperture Radar (InSAR) enables wide-area observation of surface deformation at millimeter scale, but deformation time series derived from a single satellite mission can be affected by coherence loss, atmospheric disturbances, and temporal gaps, particularly in environmentally complex regions.

In this study, we present a multi-sensor InSAR framework that integrates Sentinel-1 and TerraSAR-X data to improve deformation monitoring in geo-energy settings. The approach combines the dense temporal coverage of Sentinel-1 with the higher spatial resolution and phase stability of TerraSAR-X, allowing deformation signals to be captured more robust than with either sensor alone. After aligning the datasets in space and time, interferometric observations from both sensors are jointly analyzed to derive a unified deformation time series.

Deformation is estimated using a least-squares inversion strategy that accommodates uneven temporal sampling and overlapping observations from different sensors. Model-based residual analysis is used to assess data quality and identify potential artefacts, such as atmospheric effects or unwrapping errors, providing additional confidence in the deformation signals derived.

The combined analysis of Sentinel-1 and TerraSAR-X demonstrates the potential of multi-sensor InSAR to enhance temporal sampling and provide complementary information on surface deformation. While the integrated time series reveals improved continuity in certain periods, the results also expose limitations related to sensor differences and processing assumptions. These observations highlight both the opportunities and the challenges of multi-sensor InSAR fusion, and motivate further refinement of processing strategies to support more reliable deformation monitoring in geo-energy applications.