Hydraulic fracturing pump health and performance monitoring using IoT sensor networks

Patent metadata

Field	Value
Publication number	US-12366242-B2
Application number	US-202117905589-A
Country	US
Kind code	B2
Filing date	Mar 3, 2021
Priority date	Mar 3, 2020
Publication date	Jul 22, 2025
Grant date	Jul 22, 2025

Abstract

A system for monitoring a piece of hydraulic fracturing equipment such as a positive displacement pump. The system includes a plurality of sensors configured to detect conditions of the hydraulic fracturing pump and a processor that is communicatively coupled to the plurality of sensors and configured to analyze data received from the plurality of sensors. The processor is also configured to predict faults in the hydraulic fracturing pump based on the data analysis. The system also includes a communication interface that is configured for transmitting predicted fault data to one or more devices.

First claim

What is claimed is:

1. A system for monitoring a hydraulic fracturing pump at a hydraulic fracturing site, comprising:
a plurality of Internet of Things (IoT) sensors, forming a fog network, coupled to the hydraulic fracturing pump and configured to measure operating parameters of the hydraulic fracturing pump, the plurality of IoT sensors including at least one sensor coupled to a fluid end of the hydraulic fracturing pump and at least one sensor coupled to a power end of the hydraulic fracturing pump;
a processor an edge computing node, in the fog network, configured to;
receive measurement data from the plurality of IoT sensors;
predict a fault in the hydraulic fracturing pump based on the measurement data; and
generate prediction fault data indicating the fault; and

a communication interface, in the fog network, configured to transmit, via a local wireless network at the hydraulic fracturing site, the prediction fault data to at least one user device located at the hydraulic fracturing site.

2. The system of claim 1 , wherein the measurement data includes at least one of operating conditions of the hydraulic fracturing pump or conditions of fluids passing through the hydraulic fracturing pump.

3. The system of claim 1 , wherein the edge computing node is configured to predict the fault in a component of the hydraulic fracturing pump.

4. The system of claim 1 , wherein the plurality of IoT sensors include mixed mode electronics.

5. The system of claim 1 , wherein the edge computing node, to predict the fault, is configured to analyze the measurement data based on a deterministic model.

6. The system of claim 1 , wherein the edge computing node, to predict the fault, is configured to identify precursors to emerging faults in the hydraulic fracturing pump based on a comparison of values of the measurement data to one or more predetermined combinations of sensor data values.

7. The system of claim 1 , wherein the communication interface is selected from the group consisting of a WiFi communication interface, a Bluetooth interface, a Bluetooth Low Energy interface, a Controller Area Network bus interface, a wireless local area network interface, a wireless wide area network interface, a cellular communication network interface, and a satellite communication network interface.

8. The system of claim 1 , further comprising one or more devices, in the fog network, configured to generate at least one of an alert, an alarm, or a warning message in response to receiving the prediction fault data.

9. The system of claim 1 , further comprising a remote central server in communication with the edge computing node and configured to receive the measurement data and the prediction fault data.

10. A method for monitoring a hydraulic fracturing pump, comprising:
receiving, by an edge computing node, measurement data from a plurality of sensors, forming a fog network, coupled to components of the hydraulic fracturing pump and configured to measure operating parameters of the hydraulic fracturing pump;
determining, by the edge computing node, whether the measurement data is indicative of a fault in the hydraulic fracturing pump;
generating, by the edge computing node, prediction fault data indicating the fault; and
transmitting, by the edge computing node via a communication interface using a local wireless network, the prediction fault data to at least one user device.

11. The method of claim 10 , wherein receiving the measurement data comprises receiving at least one of operating conditions of the hydraulic fracturing pump or conditions of fluids passing through the hydraulic fracturing pump.

12. The method of claim 10 , wherein determining whether the measurement data is indicative of the fault comprises predicting the fault in a component of the hydraulic fracturing pump.

13. The method of claim 10 , wherein determining whether the measurement data is indicative of the fault comprises analyzing the measurement data based on a deterministic model.

14. The method of claim 13 , wherein analyzing the measurement data comprises identifying precursors to emerging faults in the hydraulic fracturing pump based on a comparison of values of the measurement data to one or more predetermined combinations of sensor data values.

15. The method of claim 10 , further comprising generating at least one of an alert, an alarm, or a warning message in response to the prediction fault data.

16. The method of claim 10 , further comprising transmitting at least one of the measurement data, the prediction fault data, alarm data, alert data, or warning messages to a remote central server.

17. A system for monitoring a piece of hydraulic fracturing equipment, comprising:
a plurality of sensors, forming a fog network, coupled to the hydraulic fracturing equipment and configured to measure operating parameters of the hydraulic fracturing equipment;
an edge computing node, in the fog network, configured to;
receive measurement data from the plurality of sensors; and
determine a fault in the hydraulic fracturing equipment; and

a communication interface, in the fog network, configured to transmit, via a local wireless network, prediction fault data indicating the fault to at least one user device.

18. The system of claim 17 , wherein the measurement data includes at least one of operating conditions of the hydraulic fracturing equipment or conditions of fluids passing through the hydraulic fracturing equipment.

19. The system of claim 17 , wherein the edge computing node is configured to determine the fault in a component of the hydraulic fracturing equipment.

20. The system of claim 17 , wherein the plurality of sensors include mixed mode electronics.

21. The system of claim 17 , wherein the edge computing node, to determine the fault, is configured to analyze the measurement data based on a deterministic model.

22. The system of claim 17 , wherein the edge computing node, to determine the fault, is configured to identify precursors to emerging faults in the hydraulic fracturing equipment based on a comparison of values of the measurement data to one or more predetermined combinations of sensor data values.

23. The system of claim 17 , wherein the communication interface is selected from the group consisting of a WiFi communication interface, a Bluetooth interface, a Bluetooth Low Energy interface, a Controller Area Network bus interface, a wireless local area network interface, a wireless wide area network interface, a cellular communication network interface, and a satellite communication network interface.

24. The system of claim 17 , further comprising one or more devices, in the fog network, configured to generate at least one of an alert, an alarm, or a warning message in response to receiving the prediction fault data.

25. The system of claim 17 , further comprising a remote central server in communication with the edge computing node and configured to receive the measurement data and the prediction fault data.

26. The method of claim 10 , wherein the plurality of sensors include mixed mode electronics.

Assignees

• Spm Oil & Gas Inc

Inventors

• Harris Ralph E
• Davis Trevor
• Cheng Brian
• Fry Taylor

Classifications

• F04B2201/0404

  Lubricating oil condition · CPC title

• F04B2205/04

  Pressure in the outlet chamber · CPC title

• F04B2201/1201

  Rotational speed of the axis · CPC title

• F04B2205/02

  Pressure in the inlet chamber · CPC title

• F04B49/065

  and making use of computers · CPC title