Rheidiant Announces Participation in Chevron Technology Ventures’ Catalyst Program

HOUSTON–(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.

Contacts

Rheidiant
Murat Ocalan, +1-832-390-4928
[email protected]