Sensing Technologies

Smart Gas Infrastructure Sensing of Wells and Pipeline Connections Performance

Task Description – As part of the larger OpenSRA project, this research task aims inform the California infrastructure owners about the rapidly growing state-of-the-art instrumentation and monitoring, that then can be implemented to make natural gas infrastructure safer for both the environment and consumers. In the last two decades, the fields of electrical engineering and computer science have produced many new sensing technologies that can be applied to monitoring natural gas infrastructure. In addition, many of the new technologies can make a meaningful change to the way these systems are operated and maintained.

In addition to the obvious reason for monitoring infrastructure, to detect damage, the future of risk quantification lies in leveraging measured data to update current risk models. Similarly to the advancement in sensing technologies, prediction models for estimating events such as liquefaction and landslides have also progressed. These models take in information about site conditions and possible earthquakes to predict the likelihood of a hazardous event. That information is then coupled with the response of the system to quantify the risk to natural gas infrastructure. The outputs of OpenSRA are predicted deformation of the natural gas subsystems and the likelihood that they will experience a loss of containment (LOC).

The models are broken down into categories for buried pipelines, storage wells, and surface facilities. Each set of models have their own inputs, intermediate variables and outputs. Fusing monitoring with these models means that the measured data must interact at all stages. First, the input data can be measured and verified to estimate starting conditions with minimized uncertainty. Next, the intermediate variables can be compared with measured data to ensure that the models are capturing the real behavior. Finally, the outputs of the models need to be verified with real measurable data to quantify their uncertainty for implementations when measurements may not be possible due to budget constraints.

This project’s goal is to identify the technologies that can inform the risk models at the input, intermediate and final output stages while providing a guide to the state-of-the-art monitoring technologies that natural gas infrastructure owners can understand and implement quickly.

Overall, this team

  • Identified appropriate sensing technologies for well and pipeline monitoring

  • Tested specific sensing technologies alongside the shake table testing (Surficial Infrastructure)

  • Outlined sensing technologies availability and assessed feasibility with gas infrastructure

  • Provided a guide to the state-of-the-art monitoring technologies to help users understand and implement

Lead Investigator: Kenichi Soga (University of California, Berkeley)

Team Members: Peter Hubbard (University of California, Berkeley), Chien-Chih “James” Wang (University of California, Berkeley), Tianchen Xu (University of California, Berkeley)


Wang, Chien-Chih; Peter Hubbard; Tianchen Xu; Kenichi Soga. 2022. Performance-Based Earthquake Engineering Assessment Tool for Natural Gas Storage and Pipeline Systems, Task 4E Final Report – Sensor and Monitoring Technologies. California Energy Commission. July 2022