Automated Daily Production Optimization Process with PIPESIM and PIPESIM Python Toolkit

With digital in mind, especially in this current downturn business climate, we may be aware of a word called 'Automation'. Meanwhile, production network optimization has been proven to be an effective method to maximize the production potential of a field with low capital. But as it stands, it is a heavy process to start along with its several challenges such as data quality issues, tedious plus repetitive work processes to deploy and re-use a complete network model.

With technologies from PIPESIM flow assurance simulator, its Python Toolkit API, and complemented with a commercial visualization dashboard, I created a daily data acquisition and model update from production database (last well test data for each well, equipment parameters) and the internet (Ambient temperature) in order to run daily gas lift wells production optimization process inside PIPESIM. The simulation results are extracted and prepared with Python script to be delivered into a dedicated table inside our Production Data Management System (PDMS). It will then be available in a personalized network surveillance dashboard accessible for engineers to create rapid decisions.

This workflow can be automated by simply trigger the python script created to be run every morning so that results will be delivered to us without our fingertips