Real-time determination of meter drift via loss qualification and quantification

1. A method comprising:

receiving, from a sensor in operable communication with a fuel storage facility, data characterizing the fuel storage facility;

determining, based on the received data, an estimate of meter drift of a flow meter of a fuel dispenser in fluid communication with the fuel storage facility and separate from the fuel storage facility, the determining further based on at least one predictive model that predicts whether a calibration parameter characterizing a calibration of the flow meter has deviated from a predetermined flow meter calibration parameter; and

providing the estimate of meter drift.

2. The method of claim 1 , wherein the at least one predictive model includes a predetermined calibration parameter for the fuel storage facility, a physics model for the fuel storage facility, and an error model indicative of at least one degree of error in the data.

3. The method of claim 2 , further comprising:

determining a meter drift loss quantity prediction for the fuel storage facility, the determining of the meter drift loss quantity prediction based on the received data, the predetermined calibration parameter for the fuel storage facility, the physics model, and an optimization of the error model.

4. The method of claim 3 , wherein the estimate of meter drift is provided to a graphical user interface of a display, the graphical user interface configured to present a visual characterization of the meter drift loss quantity prediction on the display.

5. The method of claim 2 , wherein the physics model is a fluid balance model.

6. The method of claim 2 , wherein the determining further includes maximizing or minimizing a function characterized by the physics model.

7. The method of claim 1 , wherein the sensor includes one or more of a dipstick, an automated tank gauge, a fuel leak detection sensor, a magnetostrictive probe, a point of sale device, a forecourt controller, a back office system, and/or a fuel dispenser.

8. The method of claim 1 , wherein the data characterizing the fuel storage facility includes one or more of an indication of leakage and/or a rate of leakage per unit time of fuel from the fuel storage facility to the surrounding environment, environmental parameters of the fuel storage facility, an amount of fuel added to the fuel storage facility as a result of a delivery of fuel from a fuel supplier to the fuel storage facility, and/or an amount of fuel removed from the fuel storage facility as a result of a sale of fuel to a customer.

9. The method of claim 1 , wherein the estimate of meter drift is provided to a graphical user interface of a display, the graphical user interface configured to present a visual characterization of the estimate of meter drift on the display.

10. The method of claim 1 , further comprising determining the estimate of meter drift at a repeatable time interval.

11. A system comprising:

at least one data processor; and

memory storing instructions configured to cause the at least one data processor to perform operations comprising:

receiving, from a sensor in operable communication with a fuel storage facility, data characterizing the fuel storage facility;

determining, based on the received data, an estimate of meter drift of a flow meter of a fuel dispenser in fluid communication with the fuel storage facility and separate from the fuel storage facility, the determining further based on at least one predictive model that predicts whether a calibration parameter characterizing a calibration of the flow meter has deviated from a predetermined flow meter calibration parameter; and

providing the estimate of meter drift.

12. The system of claim 11 , wherein the at least one predictive model includes a predetermined calibration parameter for the fuel storage facility, a physics model for the fuel storage facility, and an error model indicative of at least one degree of error in the data.

13. The system of claim 12 , wherein the operations further comprise:

determining a meter drift loss quantity prediction for the fuel storage facility, the determining of the meter drift loss quantity prediction based on the received data, the predetermined calibration parameter for the fuel storage facility, the physics model, and an optimization of the error model.

14. The system of claim 13 , wherein the estimate of meter drift is provided to a graphical user interface of a display, the graphical user interface configured to present a visual characterization of the meter drift loss quantity prediction on the display.

15. The system of claim 12 , wherein the physics model is a fluid balance model.

16. The system of claim 12 , wherein the determining further includes maximizing or minimizing a function characterized by the physics model.

17. The system of claim 11 , wherein the sensor includes one or more of a dipstick, an automated tank gauge, a fuel leak detection sensor, a magnetostrictive probe, a point of sale device, a forecourt controller, a back office system, and/or a fuel dispenser.

18. The system of claim 11 , wherein the data characterizing the fuel storage facility includes one or more of an indication of leakage and/or a rate of leakage per unit time of fuel from the fuel storage facility to the surrounding environment, environmental parameters of the fuel storage facility, an amount of fuel added to the fuel storage facility as a result of a delivery of fuel from a fuel supplier to the fuel storage facility, and/or an amount of fuel removed from the fuel storage facility as a result of a sale of fuel to a customer.

19. The system of claim 11 , wherein the operations further comprise determining the estimate of meter drift at a repeatable time interval.

20. A non-transitory computer program product storing instructions which, when executed by at least one data processor forming part of at least one computing system, cause the at least one data processor to implement operations comprising:

receiving, from a sensor in operable communication with a fuel storage facility, data characterizing the fuel storage facility;

determining, based on the received data, an estimate of meter drift of a flow meter of a fuel dispenser in fluid communication with the fuel storage facility and separate from the fuel storage facility, the determining further based on at least one predictive model that predicts whether a calibration parameter characterizing a calibration of the flow meter has deviated from a predetermined flow meter calibration parameter; and

providing the estimate of meter drift.