Integrated modeling and monitoring of formation and well performance
US-2016312552-A1 · Oct 27, 2016 · US
US10520937B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-10520937-B2 |
| Application number | US-201715429515-A |
| Country | US |
| Kind code | B2 |
| Filing date | Feb 10, 2017 |
| Priority date | Feb 10, 2017 |
| Publication date | Dec 31, 2019 |
| Grant date | Dec 31, 2019 |
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Official abstract text for this publication.
According to some embodiments, system and methods are provided, comprising an installed product, including a plurality of components; a computer programmed with a damage metric model for the installed product, the damage metric model for providing an estimate of an extent of damage on one or more components; the computer programmed with a dynamic process control model for providing a dynamic response of the installed product with respect to its one or more operating parameters; the computer further programmed with a true-up model for providing a control action to reduce an uncertainty of the estimate provided by the damage metric model; the computer including a processor and a memory in communication with the processor, the memory storing the damage metric model and the true-up model; the memory storing additional program instructions, the processor operative with the additional program instructions to perform functions as follows: receiving an estimate output of the damage metric model, wherein the output includes the estimate of the extent of damage on the one or more components; generating, via the dynamic process control model, an operating response of the installed product to the received estimate output; in response to receipt of the estimate output, executing the true-up model; and generating, via execution of the true-up model, the plan to reduce uncertainty of the estimate output. Numerous other aspects are provided.
Opening claim text (preview).
The invention claimed is: 1. A system comprising: an installed product, including a plurality of components; a computer programmed with a damage metric model for the installed product, the damage metric model for providing an estimate of an extent of damage on one or more components; the computer programmed with a dynamic process control model for providing a dynamic response of the installed product based on one or more operating parameters of the installed product; the computer further programmed with a true-up model for providing a control action to reduce an uncertainty of the estimate provided by the damage metric model; the computer including a processor and a memory in communication with the processor, the memory storing the damage metric model and the true-up model; the memory storing additional program instructions, the processor operative with the additional program instructions to perform functions as follows: receiving an estimate output of the damage metric model, wherein the output includes the estimate of the extent of damage on the one or more components; determining an uncertainty value associated with the output estimate of the extent of damage on the one or more components; generating, via the dynamic process control model, an operating response of the installed product to the received estimate output; in response to receipt of the estimate output, executing the true-up model; and generating, via execution of the true-up model, a plan to reduce the determined uncertainty value of the output estimate of the extent of damage on the one or more components; wherein the control action is an automated perturbation of the installed product. 2. The system of claim 1 , wherein the computer is programmed with a performance metric model for generating an estimate of system-level operating performance on at least one of one or more asset and one or more coupled systems; and wherein the computer is further programmed with the true-up model for generating the plan to reduce an uncertainty of the estimate of system-level operating performance provided by the performance metric model. 3. The system of claim 1 , wherein the processor is further operative with the additional program instructions to perform functions as follows: executing the control action. 4. The system of claim 1 , wherein the control action includes execution of an in-operation test sequence associated with the one or more components, or execution of an in-operation data burst associated with the one or more components, wherein each of the in-operation test sequence and the in-operation data burst is executed while the one or more components are in operation. 5. The system of claim 1 , wherein a sequence and use of true-up modalities are computed to maximize a specificity required for operational control at a desired confidence interval at one or more intervals of time. 6. The system of claim 1 , wherein the estimate of the extent of damage is for one or more sub-components of the one or more components. 7. The system of claim 1 , wherein the estimate of the extent of damage is for one or more assets in a process or system. 8. The system of claim 1 , wherein the processor is further operative with the additional program instructions to perform functions as follows: determining that the uncertainty value is too high prior to executing the true-up model. 9. The system of claim 6 , wherein the processor is further operative with the additional program instructions to perform functions as follows: determining a first uncertainty associated with the estimate output for each of the one or more sub-components; and identifying one or more estimate outputs to reduce uncertainty via execution of the true-up model. 10. The system of claim 9 , wherein the processor is further operative with the additional program instructions to perform functions as follows: quantifying an amount of uncertainty reduction for each of the identified one or more estimate outputs. 11. The system of claim 10 , wherein execution of the control action further comprises, generating an in-operation test sequence method or an in-operation data burst method; and determining a second uncertainty associated with the in-operation test sequence method or the in-operation data burst method. 12. The system of claim 11 , wherein generating the control action to reduce the uncertainty of the estimate output is based on the determined second uncertainty. 13. The system of claim 8 , wherein determining the uncertainty is too high is based on a non-damage related metric. 14. The system of claim 13 , wherein the determined uncertainty is based on an aggregate of two or more uncertainties, each associated with the estimate of the extent of damage associated with the component. 15. The system of claim 14 , further comprising: determining an effect of each of two or more uncertainties on the aggregate uncertainty. 16. The system of claim 15 , further comprising: based on a determination that a first one of the two or more uncertainties affects the aggregate uncertainty more than at least a second one of the two or more uncertainties, executing the true-up model to true-up the estimate output associated with the first uncertainty.
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 title
Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS] · CPC title
Cross-Sectional Technologies · mapped topic
Management or planning · CPC title
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