Unlock instant, AI-driven research and patent intelligence for your innovation.

Rod pump fault prediction based on well site machine learning

A fault prediction and well-site technology, applied in machine learning, machines/engines, pumps with flexible working elements, etc., can solve problems such as time-consuming, dangerous on-site personnel, and high cost

Pending Publication Date: 2022-04-26
SCHNEIDER ELECTRIC SYST USA INC
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This can be a costly and time-consuming endeavor, resulting in lost productivity and profitability for well owners and operators, and can also be dangerous to field personnel
[0006] Therefore, while many advances have been made in the field of oil and gas production, it is easy to understand that there is a need for continuous improvement

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Rod pump fault prediction based on well site machine learning
  • Rod pump fault prediction based on well site machine learning
  • Rod pump fault prediction based on well site machine learning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0056] While the description and drawings illustrate exemplary embodiments of the disclosure and are not to be considered limiting, the scope of the disclosure is defined by the claims, including their equivalents. Various mechanical, compositional, structural, electrical and operational changes may be made, including equivalents, without departing from the scope of the description and claims. In some instances, well-known structures and techniques have not been shown or described in detail to avoid obscuring the disclosure. Furthermore, elements and related aspects thereof described in detail with reference to one embodiment may be included in other embodiments where they are not specifically shown or described, whenever feasible. For example, if an element is described in detail with reference to one embodiment and not described with reference to a second embodiment, that element may still be required to be included in the second embodiment.

[0057] It should be noted that...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

Systems and methods for real-time monitoring and control of well operations at a wellsite use machine learning (ML)-based analysis at a wellsite. The system and method performs ML-based analysis on data from a wellsite directly at the wellsite through an edge device to detect operations beyond an expected specification and automatically respond to such abnormal operations. The edge device may issue an alert regarding abnormal operation and take predefined steps to reduce potential damage caused by such abnormal operation. The edge device may also predict a fault and a fault time by performing ML-based analysis on operational data from the wellsite using normal operational data. This helps to reduce downtime, minimize productivity and cost loss, and reduce health and safety risks of field personnel.

Description

[0001] Cross References to Related Applications [0002] This application claims the benefit and priority of U.S. Provisional Application No. 62 / 899,737, filed September 12, 2019, and U.S. Provisional Application No. 63 / 059,702, filed July 31, 2020, which are hereby incorporated by reference in their entirety . technical field [0003] The present disclosure relates to monitoring oil and gas wells to ensure proper well operation, and more particularly to methods and systems for real-time monitoring and control of well operations at the wellsite using machine learning (ML) based analytics to detect abnormal operating conditions. Background technique [0004] Oil and gas wells are commonly used to extract hydrocarbons from underground formations. A typical well site includes a wellbore that has been drilled into the formation and a section of tubing or casing that is cemented in place within the wellbore to stabilize and protect the wellbore. The casing is perforated at a ta...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G05B23/02G06K9/62G06N5/04G06N20/00
CPCG05B23/0243G06N20/00G06N5/04G05B2219/24065G06F18/2415E21B41/00E21B43/127E21B47/009E21B2200/22F04B49/10F04B47/00F04B47/02F04B49/065F04B49/20
Inventor F.萨吉尔X.帕斯博B.博古斯拉夫斯基M.布琼尼尔L.比苏埃尔-博韦斯
Owner SCHNEIDER ELECTRIC SYST USA INC