SYSTEMS AND METHODS OF FAILURE AND LIFE CYCLE PREDICTION AND MANAGEMENT
Systems and methods provided herein relate to a well site or other plant. Systems and methods are employed to determine faults and/or life cycle. A failure prediction engine can be used. The failure prediction engine includes a data quality engine, a features engine, condition detectors, failure models, and an alarm configurator.
1 . A pump system for a pump disposed within a well, the pump system comprising:
a controller comprising a failure prediction engine configured to predict life cycle and failure, wherein the failure prediction engine comprises a data quality (DQ) engine configured to identify receive real-time streaming data associated with the well and provide data quality flags and a features engine configured to extract patterns, wherein the features engine is configured to receive the data quality flags from data quality engine and the real-time streaming.
2 . The pump system of claim 1 , wherein the data quality flags indicate missing parameters or readings, or outlier parameters or readings.
3 . The pump system of claim 1 , wherein the data quality engine is configured as an application.
4 . The pump system of claim 1 , wherein the features engine is configured to denoise the real-time streaming data and generate key performance statistics.
5 . The pump system of claim 4 , wherein the key performance statistics comprise averages, rate of change, and certainty.
6 . The pump system of claim 1 , wherein the failure prediction engine is configured to automatically enable/disable condition detectors in response to the data quality flags.
7 . The pump system of claim 1 , wherein the features engine uses advanced multivariate unsupervised machine-learning techniques to detect the patterns and shifts in the patterns across multiple-signals and at multiple-timescales.
8 . A failure prediction engine for energy resource processing, comprising:
a data quality engine configured to identify receive real-time streaming data associated with the energy resource processing and provide data quality flags;
a features engine configured to extract patterns, wherein the features engine is configured to receive the data quality flags from the data quality engine and the real-time streaming; and
a plurality of condition detectors, wherein each condition detector is configured to detect a condition, wherein the failure prediction engine is configured to automatically enable/disable at least one of the condition detectors in response to the data quality flags.
9 . The failure prediction engine of claim 8 , further comprising:
models comprising a risk of failure model and remaining useful life model.
10 . The failure prediction engine of claim 9 , further comprising:
an alarm configurator configured to provide various options for users to set conditions to trigger alarms in response at a risk of failure, remaining life, confidence level, or run time.
11 . The failure prediction engine of claim 8 , wherein the failure prediction engine is configured to automatically enable/disable condition detectors in response to the data quality flags.
12 . The failure prediction engine of claim 8 , wherein the features engine is configured to denoise the real-time streaming data and generate key performance statistics.
13 . The failure prediction engine of claim 12 , wherein the key performance statistics comprise averages, rate of change, and certainty.
14 . The failure prediction engine of claim 8 , wherein the failure prediction engine is configured to automatically enable/disable condition detectors in response to the data quality flags.
15 . The failure prediction engine of claim 8 , wherein the features engine uses advanced multivariate unsupervised machine-learning techniques to detect the patterns and shifts in the patterns across multiple-signals and at multiple-timescales.
16 . A well site including a pump system for a pump disposed within a well, the well site comprising:
a failure prediction engine, comprising:
a data quality engine;
a features engine;
condition detectors;
failure models; and
an alarm generator, wherein the failure prediction engine is configured to provide tuning for the alarm configurator and the failure models, tuning for the condition detectors, and tuning a feature engine.
17 . The well site of claim 16 , wherein the failure prediction engine is configured to provide tuning for the data quality engine.
18 . The well site of claim 16 , wherein the failure prediction engine is configured to update the failure models and the detectors based upon a specific population failure type or a specific use case requirement.
19 . The well site of claim 16 , wherein the failure prediction engine is configured tune the detectors based upon performance drift.
20 . The well site of claim 16 , wherein the failure prediction engine is configured to modify the feature engine in response to new sensors.