The Project
In a major energy production company in Australia, engineers utilise satellites to maximise raw gas production from various wells in the surrounding gas fields. At one satellite, they relied on an Excel model to simulate plant operations, identifying capacity levels and breaches for specified scenarios. But, when considering the risks, Excel left the model open to accidental errors from cell edits, and the complex logic buried in multiple formulas made updates and error diagnoses difficult.
Technical Solutions
Using a customised Python-based digital twin model, our Data Analytics team modernised the process, combining a user-friendly web app interface created with Streamlit. This approach increased calculation efficiency and simplified the model’s logic, making updates easy and consistent. Engineers can now easily add or remove components like wells or other satellites, broadening the network. Automation allows entire scenario ranges to be modelled, quickly identifying optimal parameters. The model engine is abstracted away from the interface, preventing accidental errors being introduced and ensuring engineers focus their time on modelling.
Client Focus
The new web app interface retains all the input and output capabilities of the Excel model but adds powerful new features. Dynamic visualisations clearly highlight significant bottlenecks, with results displayed directly on the flowsheet for better insights. Additionally, deploying the model in a cloud environment like Snowflake enables integration with other satellite digital twins, optimising performance across the entire connected network.
It’s all part of working smarter.
Key Personnel
The Big Lake Digital Twin and Interface is included in the following sectors & services.
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