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IIoT Solution for Oil and Gas Industry

About Project

We created an intelligent IIoT Solution with GE Automation for the client to facilitate significant improvement in their operational efficiency. Through the solution, we enabled a seamless flow of data from hardware and sensors to the cloud, and from the cloud to interactive dashboards. The entire data system was moved to a single platform which then streamed live data from different assets using fields. It gives real-time monitoring of data and also helps in data prediction which helps in the maximization of oil production.
tank
IIoT Solution for Oil and Gas Industry
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Duration

Duration

1.5 Year

Release date

Release date

May 2019

working (1)

Working Hours

160+Hours

Duration

Duration

1.5 Year

Release date

Release date

May 2019

working (1)

Working Hours

160+ Hours

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Business Challenge

The client was looking for an IT partner for their automation solution focused on the Oil & Gas industry. Their automation solution needed a systematized data flow from their hardware & sensors to the cloud, and then from the cloud to the interactive dashboards. These dashboards were utilized for achieving production optimization and performing predictive analytics for business-critical decision-making. 

Business Solution

Taking care of the challenges on the IT side of the end-to-end solution, Zehntech implemented the IIoT with our US-based customer and GE Automation in the Oil and Gas domain. The Asset-Monitoring Module, Alert Module, and Reporting Module (which included oil wells, gas pipelines, oil tanks, and compressors) were moved into a single platform using GE Predix cloud and GE IIoT field devices.

Currently, the field devices stream live data with intervals of 10 seconds from 8 different assets with 5-6 different data matrices, like oil flow, oil level, tank temperature, gas pressure, vibrations, alerts, etc.

The goal was to build a single IIOT app (using NodeJS, AngularJS, and Google Polymer) and deploy the GE Predix cloud for real-time monitoring, alerts, and predictive analytics. Right now, we are implementing a machine learning predictive module to predict tank level, machine failure, and optimized gas injection for maximizing oil production.

During the project, we configured field agents to use MQTT to transfer sensor data to the Predix Time series database. Next, we aggregated the data to calculate actionable information.

For example: Based on the oil flow rate, tank number 4 will be full in 1 hour and 39 Minutes. Based on the gas pressure, we can predict if the gas compressor is going down.

Applied Technologies

Angular
GE Digital
Polymer
NodeJS

Our Role in Client Success

We, at Zehntech, focus on providing our clients with tangible results. By partnering with us on this project, the end client was able to improve overall operational efficiency by a whopping 30%. Moreover, they can now also predict compressor downtime which will help them prepare and arrange for compressor maintenance in advance.  

Our Client Says

Group 133162

“A company from the UK that provides visitor reception software and follows the highest standers of customers supports.The team has great experience in creating management software for the event business companies. ”









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