BP has been granted a patent for a method that utilizes neural networks and modeling modules to predict geological characteristics of a reservoir. The approach involves creating three-dimensional static and dynamic models based on geophysical data, enhancing wellbore drilling recommendations through advanced connectivity and saturation analysis. GlobalData’s report on BP 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 BP, Selective catalytic ammoxidation was a key innovation area identified from patents. BP's grant share as of July 2024 was 72%. Grant share is based on the ratio of number of grants to total number of patents.

Geological modeling using neural networks and dynamic simulations

Source: United States Patent and Trademark Office (USPTO). Credit: BP Plc

The granted patent US12055673B2 outlines a method and system for modeling geological characteristics of a specific volume, particularly in the context of well trajectories. The method employs a static modeling module that utilizes trained neural networks to generate a three-dimensional static model based on geophysical characteristics derived from randomly generated coordinates surrounding a well. These characteristics are influenced by distance vectors relative to measured data at known coordinates along the well trajectory. The process includes clustering portions of the volume, determining connectivity values between these clusters, and assigning saturation values, ultimately leading to the creation of a dynamic model that reflects changes over time.

Additionally, the patent details various enhancements to the modeling process, such as predicting geophysical characteristics using neural networks, adjusting models based on anticipated changes in saturation and pressure values, and evaluating the models through a fuzzy inference engine. This engine can provide recommendations for drilling operations based on predefined rules. The system is designed to quantify uncertainty through multiple static model realizations and is capable of defining fault planes within the geological volume, which can impact permeability. Overall, the patent presents a comprehensive approach to geological modeling that integrates advanced computational techniques with practical applications in resource extraction.

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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.