TMCnet News
Rheidiant Announces Participation in Chevron Technology Ventures' Catalyst ProgramRheidiant, Inc. today announced its participation in Chevron (News - Alert) Technology Ventures' new Catalyst Program. Rheidiant is a part of the first group of companies admitted to the CTV Catalyst Program. CTV introduced this program to support startup companies that bring innovative products that may have positive impact on the oil and gas industry. The Smart Sign leak detection system is a ground-breaking solution to new and old hazardous liquid pipelines, monitoring these assets for small and large leaks before they result in big environmental spills. The technology relies on proprietary acoustic sensors that are deployed near the pipeline without excavation or trenching. "Deploying external real-time monitoring systems are essential in safeguarding pipelines against large environmental spills. Today, however, there are over half a million miles of pipelinesthat were deployed without external monitoring. The Smart Sign system offers the world's first economic retrofit solution to the operators of these pipelines and helps them protect the environment, the neighboring communities and their bottom line against spill events," said Murat Ocalan, the President and CEO of Rheidiant. "Product spills from old hazardous liquid pipelines is a serious challenge facing the industry. Chevron has taken a leadership position to apply new technology to address this challenge and we are excited to work with them under the Catalyst program," said Hossam Elbadawy, Rheidiant's Chairman. Based in Houston, Rheidiant applies industrial internet of things (IIoT) and machine learning technologies to solve big problems in the oil and gas industry. Its Smart Sign integrity management system is a unique product offering that allows operators to pin point small, normally undetectable leaks on their existing pipelines before they turn into large environmental spills. The system is deployed in the field without requiring excavation or direct contact with the pipe. Leaks on the asset are detected by the use of proprietary edge analytics and central machine learning algorithms. As a result, operators of these aging assets are able to accurately quantify their environmental risk and respond to events in time. View source version on businesswire.com: http://www.businesswire.com/news/home/20170822006244/en/ |
