Satellite Data Analytics for Natural Disaster Assessment and Application to Pipeline Safety

Abstract

Understanding where, when, and how conditions are changing along the extent of an energy pipeline system, which can be vast, is a challenging task. The challenge can be even greater when natural disasters1 create a condition where access to affected pipelines, qualified personnel, and equipment is limited. To address these challenges, pipeline operators are working directly with experts in satellite technology to develop innovative applications incorporating the use of satellite technology and analytical processes to improve natural disaster monitoring and response. Through recent experiences following Hurricane Harvey in the Gulf Coast region of the United States in August-September 2017 and the wildfires and mudslides in Southern California that occurred in December 2017 to January 2018, space-borne Synthetic Aperture Radar (SAR) satellite data was shown to be a useful tool for wide-area monitoring. Satellite-based SAR imagery has the unique advantage of penetrating through cloud cover and smoke and is capable of providing an early view of the extent of damage in both conditions. Satellite data and continuous improvements to their derived analytical products have resulted in significant benefits for pipeline operators preparing for and responding to the effects of potentially damaging natural processes, including river scour, erosion, avulsion, mudslides, and other threats to pipeline integrity and public safety. SAR change detection algorithms and processes can provide effective results in identifying areas affected by natural disasters that are not readily available by other means. These methods also provide timely information for allocating and directing resources to the most critical locations in support of post-disaster assessment and analysis. SAR satellite data and Amplitude Change Detection (ACD) algorithms provided the basis for confirming where flooding near pipeline infrastructure was most substantial following Hurricane Harvey. In the case of the Southern Californian forest fires and mudslides in Ventura and Santa Barbara counties, recent investigations into ACD and Coherence Change Detection (CCD) algorithms showed promising results, providing a detailed view of damaged areas in near-real time. This paper describes the process of collecting, analyzing, and applying satellite data for assessing the impacts of natural disasters on pipeline infrastructure, and the methods applied, consisting primarily of multiple change detection algorithms, that are used to process the large volume of satellite archive images to extract relevant changes. This paper also describes how these tools and products were practically applied to support decisions by pipeline operators to protect and ensure the integrity and safety of pipelines in the affected areas.