Methods and systems for industrial internet of things data collection for process adjustment in an upstream oil and gas environment

• US 10,754,334 B2
• Filed: 05/07/2018
• Issued: 08/25/2020
• Est. Priority Date: 05/09/2016
• Status: Active Grant

• Current Assignee: Strong Force IoT Portfolio 2016, LLC (Strong Force Intellectual Capital, LLC)
• Original Assignee: Strong Force IoT Portfolio 2016, LLC (Strong Force Intellectual Capital, LLC)
• Inventors: Cella, Charles Howard, Duffy, Jr., Gerald William, McGuckin, Jeffrey P., Desai, Mehul
• Primary Examiner(s): Tran, Vicent H
• Application Number:
  US15/973,205
• Publication Number:
  US 20180284742A1
• Time in Patent Office: 841 Days
• CPC Class Codes: B62D 15/0215 by measuring on the steering column
• CPC Class Codes: B62D 5/0463 calculating assisting torque from the motor based on driver input
• CPC Class Codes: G01M 13/028 Acoustic or vibration analysis
• CPC Class Codes: G01M 13/04 Bearings
• CPC Class Codes: G01M 13/045 Acoustic or vibration analysis
• CPC Class Codes: G05B 13/028 using expert systems only
• CPC Class Codes: G05B 19/042 using digital processors G05B19/05 takes precedence
• CPC Class Codes: G05B 19/4183 characterised by data acquisition, e.g. workpiece identification
• CPC Class Codes: G05B 19/4184 characterised by fault tolerance, reliability of production system
• CPC Class Codes: G05B 19/41845 characterised by system universality, reconfigurability, modularity
• CPC Class Codes: G05B 19/4185 characterised by the network communication
• CPC Class Codes: G05B 19/41865 characterised by job scheduling, process planning, material flow
• CPC Class Codes: G05B 19/41875 characterised by quality surveillance of production
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• CPC Class Codes: G05B 2219/35001 Data input, data handling, programming, monitoring of nc
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• CPC Class Codes: G05B 2219/37351 Detect vibration, ultrasound
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• CPC Class Codes: G05B 23/02 : Electric testing or monitoring
• CPC Class Codes: G05B 23/0208 : characterized by the configuration of the monitoring system
• CPC Class Codes: G05B 23/0221 : Preprocessing measurements, e.g. data collection rate adjustment; Standardization of measurements; Time series or signal analysis, e.g. frequency analysis or wavelets; Trustworthiness of measurements; Indexes therefor; Measurements using easily measured parameters to estimate parameters difficult to measure; Virtual sensor creation; De-noising; Sensor fusion; Unconventional preprocessing inherently present in specific fault detection methods like PCA-based methods
• CPC Class Codes: G05B 23/0229 : knowledge based, e.g. expert systems; genetic algorithms
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• CPC Class Codes: G05B 23/0264 : Control of logging system, e.g. decision on which data to store; time-stamping measurements
• CPC Class Codes: G05B 23/0283 : Predictive maintenance, e.g. involving the monitoring of a system and, based on the monitoring results, taking decisions on the maintenance schedule of the monitored system; Estimating remaining useful life [RUL] preventive maintenance, i.e. planning maintenance according to the available resources without monitoring the system G06Q10/06
• CPC Class Codes: G05B 23/0286 : Modifications to the monitored process, e.g. stopping operation or adapting control
• CPC Class Codes: G05B 23/0289 : Reconfiguration to prevent failure, e.g. usually as a reaction to incipient failure detection
• CPC Class Codes: G05B 23/0291 : Switching into safety or degraded mode, e.g. protection and supervision after failure
• CPC Class Codes: G05B 23/0294 : Optimizing process, e.g. process efficiency, product quality
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• CPC Class Codes: G06F 16/2477 : Temporal data queries
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• CPC Class Codes: G06Q 10/0639 : Performance analysis of employees; Performance analysis of enterprise or organisation operations
• CPC Class Codes: G06Q 30/02 : Marketing; Price estimation or determination; Fundraising
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• CPC Class Codes: G06Q 30/06 : Buying, selling or leasing transactions
• CPC Class Codes: G06Q 50/00 : Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism healthcare informatics G16H
• CPC Class Codes: G06V 10/7784 : based on feedback from supervisors
• CPC Class Codes: G06V 10/82 : using neural networks
• CPC Class Codes: G16Z 99/00 : Subject matter not provided for in other main groups of this subclass
• CPC Class Codes: H02M 1/12 : Arrangements for reducing harmonics from ac input or output
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• CPC Class Codes: H04B 17/23 : Indication means, e.g. displays, alarms, audible means
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• CPC Class Codes: H04B 17/309 : Measuring or estimating channel quality parameters
• CPC Class Codes: H04B 17/318 : Received signal strength
• CPC Class Codes: H04B 17/345 : Interference values signal-to-interference ratio [SIR] or carrier-to-interference ratio [CIR] H04B17/336
• CPC Class Codes: H04B 17/40 : of relay systems
• CPC Class Codes: H04L 1/0002 : by adapting the transmission rate
• CPC Class Codes: H04L 1/0009 : by adapting the channel coding H04L1/1812 takes precedence
• CPC Class Codes: H04L 1/0041 : Arrangements at the transmitter end
• CPC Class Codes: H04L 1/18 : Automatic repetition systems, e.g. Van Duuren systems
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• CPC Class Codes: H04L 67/1097 : for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
• CPC Class Codes: H04L 67/12 : specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
• CPC Class Codes: H04L 67/306 : User profiles
• CPC Class Codes: H04W 4/38 : for collecting sensor information
• CPC Class Codes: H04W 4/70 : Services for machine-to-machine communication [M2M] or machine type communication [MTC]
• CPC Class Codes: Y02P 80/10 : Efficient use of energy, e.g. using compressed air or pressurized fluid as energy carrier
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• CPC Class Codes: Y02P 90/80 : Management or planning
• CPC Class Codes: Y04S 50/00 : Market activities related to the operation of systems integrating technologies related to power network operation or related to communication or information technologies
• CPC Class Codes: Y04S 50/12 : Billing, invoicing, buying or selling transactions or other related activities, e.g. cost or usage evaluation
• CPC Class Codes: Y10S 707/99939 : Privileged access

Abstract

In embodiments of the present invention improved capabilities are described for a system for process monitoring through data collection in an industrial drilling environment comprising a data collector communicatively coupled to a plurality of input channels, each input channel connected to a monitoring point from which data is collected, the collected data providing a plurality of process parameter values for the industrial drilling environment; a data storage structured to store collected data from the plurality of input channels; a data acquisition circuit structured to interpret the plurality of process parameter values from the collected data; and a data analysis circuit structured to analyze the plurality of process parameter values to detect a process condition associated with the industrial drilling environment, wherein an operational process for the industrial drilling environment is altered based on the analysis of the plurality of process parameter values.

Claims

1. A system for process monitoring through data collection in an industrial drilling environment, the system comprising:

a data collector communicatively coupled to a plurality of input channels, each input channel connected to a monitoring point from which data is collected, the collected data providing a plurality of process parameter values for the industrial drilling environment;

a data storage structured to store collected data from the plurality of input channels;

a data acquisition circuit structured to interpret the plurality of process parameter values from the collected data; and

a data analysis circuit structured to analyze the plurality of process parameter values to detect a process condition associated with the industrial drilling environment,

wherein an operational process for the industrial drilling environment is altered based on the analysis of the plurality of process parameter values,

wherein the data storage further stores a plurality of collector routes,

wherein the plurality of collector routes each comprise a different data collection routine, and

wherein a selected collector route is switched from a first collector route to a second collector route based on the analysis of the plurality of process parameter values.

2. The system of claim 1, wherein the operational process is a rate of material flow in the industrial drilling environment.

3. The system of claim 1, wherein the operational process is a rotational rate of a drilling rig component in the industrial drilling environment.

4. The system of claim 1, wherein the selected collector route is switched in response to the data analysis circuit detecting a change in an operating stage of the industrial drilling environment.

5. The system of claim 1, wherein the monitoring point provides a continuously monitored alarm having a pre-determined trigger condition, and the data analysis circuit detects the pre-determined trigger condition.

6. The system of claim 1, wherein the process condition is a failure condition or an off-nominal condition for an industrial drilling component, wherein the operational process is altered to decrease a safety risk.

7. The system of claim 1, wherein the operational process is altered to increase productivity in the industrial drilling environment.

8. The system of claim 1, wherein the data analysis circuit utilizes a neural network to analyze the plurality of process parameter values.

9. The system of claim 8, wherein the neural network is a probabilistic neural network to predict the process condition as a fault condition.

10. The system of claim 8, wherein the neural network is a convolutional neural network to make a recommendation based on the analysis of the plurality of process parameter values.

11. The system of claim 8, wherein the neural network is switched between a first neural network to a second neural network by an expert system in response to determining that the system is varying dynamically.

12. The system of claim 1, wherein the data analysis circuit compares the plurality of process parameter values to a stored vibration fingerprint to detect the process condition.

13. The system of claim 1, wherein the data analysis circuit utilizes a noise pattern analysis to detect the process condition.

14. A computer-implemented method for process monitoring through data collection in an industrial drilling environment, the method comprising:

providing a data collector communicatively coupled to a plurality of input channels, each input channel connected to a monitoring point from which data is collected, the collected data providing a plurality of process parameter values for the industrial drilling environment;

providing a data storage structured to store collected data from the plurality of input channels;

providing a data acquisition circuit structured to interpret the plurality of process parameter values from the collected data; and

providing a data analysis circuit structured to analyze the plurality of process parameter values to detect a process condition associated with the industrial drilling environment,

wherein an operational process for the industrial drilling environment is altered based on the analysis of the plurality of process parameter values,

wherein the data storage further stores a plurality of collector routes,

wherein the plurality of collector routes each comprise a different data collection routine, and

wherein the collector route is switched from a first collector route to a second collector route based on the analysis of the plurality of process parameter values.

15. The method of claim 14, wherein the operational process is a rotational rate of a drilling rig component in the industrial drilling environment.

16. An apparatus for process monitoring through data collection in an industrial drilling environment, the apparatus comprising:

a data collector component communicatively coupled to a plurality of input channels, each input channel connected to a monitoring point from which data is collected, the collected data providing a plurality of process parameter values for the industrial drilling environment;

a data storage component structured to store collected data from the plurality of input channels;

a data acquisition component structured to interpret the plurality of process parameter values from the collected data; and

a data analysis component structured to analyze the plurality of process parameter values to detect a process condition associated with the industrial drilling environment,

wherein an operational process for the industrial drilling environment is altered based on the analysis of the plurality of process parameter values,

wherein the data storage component further stores a plurality of collector routes,

wherein the plurality of collector routes each comprise a different data collection routine, and

wherein the collector route is switched from a first collector route to a second collector route based on the analysis of the plurality of process parameter values.

17. The apparatus of claim 16, wherein the operational process is a rotational rate of a drilling rig component in the industrial drilling environment.