Rheidiant Announces Participation in Chevron Technology Ventures’ Catalyst Program
August 22 2017 - 10:56PM
Business Wire
Rheidiant, Inc. today announced its participation in Chevron
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 pipelines
that 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.
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RheidiantMurat Ocalan, +1-832-390-4928pr@rheidiant.com