Oil & Gas service provider: tank level forecasting

Oil & Gas service provider: tank level forecasting

Challenge-1

Challenge

  • Inaccurate tank levels lead to inefficiencies in device maintenance and operational planning
  • Need for accurate forecasts to minimize leaks, spillage, and downtimes
  • Identify equipment failure as well as maintenance issues before shutdowns

Solution-1

Solution

  • Built predictive model to forecast tank levels using onsite sensor reading and historical data. Tank forecasts leveraged to schedule tank pickups and minimize downtime at site
  • Leveraged Azure machine for rapid parallel model testing and development. Tested different advanced machine learning algorithms (Neural Network Regression, Poisson Regression, Decision Forest Regression) enable accurate prediction
  • Build Power BI dashboards available on PCs and mobile devices to monitor oil wells and other assets in the field. Based on data it can generate real-time alerts.

Result-1

Results

  • Power BI dashboard to analyze field assets, plan activities and monitor for failures
  • The minimized time needed for resolution across device maintenance issues
  • Schedule jobs/trucks/maintenance optimally, reducing cost and increasing revenue