Senex’s Customer story – Cloud Foundations and Data Analytics Platform

Betfair Logo

Senex is an established and growing Australian natural gas producer, providing gas for industries that support local communities, manufacturing, jobs and a cleaner energy future. Senex’s primary focus is on developing further opportunities to expand production, earnings and cash flow while balancing commitments around safety, environment, community and sustainability

Betfair Main Image

At a Glance

Like many organisations in the mining and energy sector, Senex has many data assets scattered across many sites and servers. A strategic review provided requirements for a new data & analytics operating model, leveraging the cloud to bring data together and scale data capabilities without traditional constraints. Servian with Google Cloud responded to and won a tender to help Senex build their platform.

The Challenge

The first delivery phase of this program of work established the Google Cloud environment for Senex. Senex had been relying solely on historical data which meant inherently acted reactively to issues that occurred end-to-end throughout gas production. This dependency was not sustainable and could have detrimental impacts on Senex’s bottom line.

Senex identified and prioritised a key use case in order to overcome these challenges. They focused on productionising a torque spike model, which helps predict failures and faults.

A Torque spike is a strong predictor of pump failure. A spike indicates the pump is suddenly working harder, which could be because of solids contaminating the outputs or some other cause. The pumps are costly, and it is even more expensive to take the well offline and forego sales while replacing them.

The Solution

Servian, working in conjunction with Senex and supported by Google Cloud, refactored an existing machine learning (ML) model to leverage Google cloud capabilities and re-deploy it rapidly to Google Cloud.

The new Google Cloud data platform hosts the Torque Spike ML model that uses key supervisory control and data acquisition (SCADA) measures, from sensors at the wells, to identify wells at risk of torque spikes. 

A data pipeline ingests live data from the SCADA Historian into Google BigQuery tables – which then feeds into the Tensorflow Machine Learning model to predict torque events for each window of 15-minute data. 

A front end application (hosted in a VM on Google Cloud) visualises the raw data. It predicts torque events in several ways, allowing engineers to quickly identify and diagnose underlying causes associated with a particular torque event.

Highlight

“As a gas producer, we don’t have an in-house team of data engineers and architects to build a data lake from scratch. Servian provided us with the local resources and analytics expertise to deliver value from digital technologies on Google Cloud in six short months.” 

– Timothy Cochrane

General Manager for Digital, Senex

The Result

Foundations for success:

Conducting the model on Google Cloud offers a significant improvement to the previous torque model implementation, which only functioned for a small number of wells and could not cope with live SCADA data.

Reduced downtime through AI/ML:

And deploying predictive maintenance, Senex can expect to mitigate potential unexpected downtime caused by costly pump failures and safety incidents.

Improved Data Resolution:

The resolution of the torque spike ML model improves from 60 minutes to 15 minutes when the model is running on Google Cloud. This is crucial for Senex to identify and respond to torque spike events in a timely manner to minimise any impact on their production line.

Learn more about what Servian can do for you

Get in contact with our team to explore new opportunities

Why Servian

We drive a competitive advantage for our customers by enabling them to become truly data driven. We help organisations design and implement robust enterprise data management strategies and data platforms that ensure the security, accuracy, and reliability of their data. Our services in data and analytics span across advisory, consulting and managed services.

Book a free consultation to learn more