ML Model Selection Based on Feature Merging, Spatial Location
Summary
USPTO granted patent US12608442B2 to inventor Jiazuo Zhang for a method of selecting machine learning models in wellbore operations using feature merging across multiple time windows. The patent covers receiving sensor data from subsurface formations in wellbores, merging with previously cached historical datasets that spatially overlap, and selecting appropriate ML models based on merged datasets.
What changed
USPTO granted patent US12608442B2 to inventor Jiazuo Zhang for a method of selecting machine learning models in wellbore operations using feature merging across time windows. The patent covers receiving sensor data from wellbores, merging with cached historical data, and selecting appropriate ML models based on merged datasets. For companies developing ML-based solutions for oil and gas operations, this patent could affect freedom-to-operate analyses.
Oil and gas companies, technology firms developing ML solutions for subsurface sensing, and manufacturers of downhole sensing equipment should consider this patent in freedom-to-operate analyses for ML-based wellbore monitoring systems.
Archived snapshot
Apr 21, 2026GovPing captured this document from the original source. If the source has since changed or been removed, this is the text as it existed at that time.
Machine learning model selection based on feature merging for a spatial location across multiple time windows
Grant US12608442B2 Kind: B2 Apr 21, 2026
Inventors
Jiazuo Zhang
Abstract
A method comprises receiving a current dataset for a current time window from at least one sensor in a wellbore created in a subsurface formation, wherein the current dataset comprises values of a number of current features of the subsurface formation at a spatial location in the wellbore. The method includes selecting at least one previous time window from a number of previous time windows that includes a previously cached dataset that was detected by the at least one sensor or a different sensor in the wellbore and that spatially overlaps with the spatial location for the current dataset. The method includes merging the current dataset with the previously cached dataset to create a merged dataset. The method includes selecting a machine learning model from a plurality of machine learning models for the spatial location in the wellbore based on the merged dataset.
CPC Classifications
E21B 2200/02 E21B 2200/20 E21B 49/00 E21B 47/00 G06F 18/211 G06F 18/22 G06F 18/25 G06F 18/285 G06N 20/00 G06V 10/751
Filing Date
2021-08-31
Application No.
17446537
Claims
20
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