Halliburton has patented a method using machine learning to predict material loss in a pipe string within a borehole. The method involves measuring wall thickness, training a well model, and generating a visual representation of material loss on a display based on user-defined categories. GlobalData’s report on Halliburton gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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According to GlobalData’s company profile on Halliburton, Oil well fracking was a key innovation area identified from patents. Halliburton's grant share as of May 2024 was 44%. Grant share is based on the ratio of number of grants to total number of patents.
Predicting material loss in pipe strings using machine learning
A recently granted patent (Publication Number: US12000976B2) outlines a method for training a well model to predict material loss for a pipe string within a borehole. The method involves measuring the wall thickness of the pipe string at different locations over time, training a machine learning-based well model to predict material loss, categorizing locations based on actual material loss, and generating a visual representation of material loss on a graphical user interface. The system includes a logging tool, a processor for data analysis, and user input for defining color-coded categories based on material loss levels.
Furthermore, the patent describes additional steps such as determining when to plug and abandon the borehole based on the well model, associating locations with specific tubular sections, comparing predicted and actual material loss to assess model accuracy, and retraining the model based on new data. It also introduces the concept of training a field model using multiple well models to predict the impact of operating conditions on pipe strings in a field, potentially aiding in decisions regarding rework or abandonment of boreholes. The patent covers a comprehensive approach to monitoring material loss in pipe strings and utilizing predictive models for maintenance and decision-making in oil and gas operations.
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GlobalData’s Patent Analytics tracks patent filings and grants from official offices around the world. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
