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US 2023/0274153 A1Published application
System and method for asphaltene anomaly prediction
AssigneeChevron U.S.A. Inc.
InventorMustafa Can Kara
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Abstract
An unsupervised machine-learning model is trained using historical operation characteristics of a well. Operation characteristics of the well for a duration of time is reconstructed by the unsupervised machine-learning model. Whether an asphaltene anomaly will occur in the future at the well is predicted based on the difference between the operation characteristics of the well and the reconstructed operation characteristics of the well.
Claims15
A system for predicting asphaltene anomalies, the system comprising:
- one or more physical processors configured by machine-readable instructions to:
- obtain well operation information, the well operation information characterizing operation characteristics of a well for a duration of time;
- determine reconstructed operation characteristics of the well for the duration of time using an unsupervised machine-learning model, wherein the unsupervised machine-learning model is trained using historical well operation information, the historical well operation information characterizing the operation characteristics of the well for a period of time preceding the duration of time;
- and
- predict a future occurrence of an asphaltene anomaly at the well based on the operation characteristics of the well for the duration of time and the reconstructed operation characteristics of the well for the duration of time.
2 more elements
A method for predicting asphaltene anomalies, the method comprising:
- obtaining well operation information, the well operation information characterizing operation characteristics of a well for a duration of time;
- determining reconstructed operation characteristics of the well for the duration of time using an unsupervised machine-learning model, wherein the unsupervised machine-learning model is trained using historical well operation information, the historical well operation information characterizing the operation characteristics of the well for a period of time preceding the duration of time;
- and
- predicting a future occurrence of an asphaltene anomaly at the well based on the operation characteristics of the well for the duration of time and the reconstructed operation characteristics of the well for the duration of time.
1 more element
Dependencies are inferred from the claim text.