Details

Autor(en) / Beteiligte

• Staniewicz, Scott
• Chen, Jingyi
• Rathje, Ellen
• Olson, Jon

Titel

Automatic Detection of InSAR Deformation Signals Associated with Hydrocarbon Production and Wastewater Injection using Laplacian of Gaussian Filtering

Ist Teil von

• IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019, p.433-436

Ort / Verlag

IEEE

Erscheinungsjahr

2019

Quelle

IEEE Electronic Library (IEL)

Beschreibungen/Notizen

• Analyzing land surface deformation maps derived from Interferometric Synthetic Aperture Radar (InSAR) data often prompts the need to detect signals of unknown size, shape, and location. Here we developed an algorithm for automatic detection of InSAR deformation signals using multi-scale Laplacian-of-Gaussian (LoG) filters. We demonstrated the efficacy of the detection technique on synthetic deformations of different sizes and shapes. We then applied the algorithm to InSAR-derived land surface deformation images in West Texas, where there has been a rise in the level of seismic activity near areas of hydrocarbon production. The algorithm detected both uplift signals from wastewater injection and subsidence from oil and gas extraction without the need for manual inspection of signals. We achieved computational speedups and reduced long term disk storage requirements due to the ability to filter out areas with no signals.