ConocoPhillips had three patents in artificial intelligence during Q1 2024. ConocoPhillips has developed systems and methods for resource development from reservoirs by obtaining NMR log data for wells, quantifying fluid producibility parameters using automated unsupervised machine learning, and generating a production characterization for reservoir development. GlobalData’s report on ConocoPhillips gives a 360-degree view of the company including its patenting strategy. Buy the report here.
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ConocoPhillips grant share with artificial intelligence as a theme is 33% in Q1 2024. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Integrated reservoir characterization using nmr t1-t2 measurements (Patent ID: US20240053503A1)
The patent filed by ConocoPhillips describes systems and methods for developing resources from a reservoir using nuclear magnetic resonance (NMR) log data obtained from wells. The NMR data is processed using automated unsupervised machine learning to quantify fluid producibility parameters, which are then used to generate a production characterization of the reservoir. This characterization informs the development of the reservoir, including decisions on drilling lateral or horizontal wells, identifying landing points, and extracting resources based on the interpreted NMR log.
The method outlined in the patent involves utilizing NMR log data to determine fluid producibility parameters such as fluid porosity, saturation, and producible oil volume. By processing this data with machine learning, a detailed production characterization of the reservoir is created, aiding in decision-making for resource extraction. Additionally, the patent includes claims for computer-executable instructions stored on tangible media to perform the process and a system utilizing a non-relational database to store NMR data and generate interpreted NMR logs for reservoir development based on fluid producibility parameters.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. 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.
