Sensoleak Global, Inc. Employee Directory

Oil and GasUnited States51-200 Employees

A Game-changing Approach in the Leakage Detection:

Headquartered in Houston, Texas, SensoLeak offers an unparalleled solution for predicting and diagnosing evolving failures in pipelines and mechanical parts via its Early Leakage Detection System (ELDS).
ELDS is a remarkable solution - for the energy industry in general and the O&G industry in particular - that ensures real-time pipe/machine monitoring system based on proprietary machine learning algorithms which analyze online data provided by the pipeline systems. When the algorithm receives data from a customer’s existing sensors
(from various sensors, e.g., acoustic, seismic, electromagnetic, mechanical, chemical, or thermal), it calculates the “system health grade,” makes a decision concerning system normality and outputs alerts as necessary. These alerts come to the equipment's operators in any form specified or required by the client.

This solution ensures the highest level of reliability and efficiency as it provides not only real -time leakage detection but also prevention. The system reports on evolving failures much before the formation of the real one—up to 49 days to date, but SensoOLeak expects this to increase to provide even greater predictive results. 
The system initially trains the algorithm to recognize the “normal” state of operations and alerts about any deviation from the norm; essentially making it scalable as it learns with little human intervention. 
SensoLeak’s real-time analyzing software detects the sudden or smallest and growing initial
leakage immediately, even after only a few measurement cycles. 

ELDS leverages scalable software without the need to install additional equipment . It creates
value for operators by adapting to changes and does not require human intervention (in most
cases) while ensuring 24/7 online monitoring and no need for calibration, even after unreported
alterations in operational conditions. 

Resumes to: joinus@sensoleak.com

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