NOV. has been granted a patent for a method to monitor well states through intermittent sampling. The method involves measuring flow differentials and calculating expected volume differentials to identify significant changes in well conditions, prompting user intervention when discrepancies arise. GlobalData’s report on NOV 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 NOV, Fall risk prediction was a key innovation area identified from patents. NOV's grant share as of July 2024 was 60%. Grant share is based on the ratio of number of grants to total number of patents.
Method for monitoring well state using flow measurements
The granted patent US12071846B2 outlines a method for monitoring the state of a well through intermittent sampling, focusing on the measurement and analysis of fluid flow in and out of the wellbore. The method involves determining a measured volume differential by calculating the difference between the flow out and flow into the wellbore. Additionally, it establishes an expected volume differential by assessing the fluid volume of the wellbore system, the pressure difference, and the well system bulk modulus. If discrepancies arise between the expected and measured volume differentials, the system alerts the user to potential significant changes in the well state that may necessitate intervention.
Further claims expand on the initial method by incorporating additional measurements, such as wellbore pressure, and controlling this pressure through surface backpressure mechanisms. The patent specifies the use of devices like Coriolis flow meters for accurate volumetric flow rate measurements. It also details how changes in flow or pressure can trigger recalculations of the expected volume differential and wellbore storage volumes. A data acquisition and control system is integral to the method, providing real-time comparisons of actual and expected values, alerting users to deviations, and analyzing historical data to predict worst-case scenarios following influx events. This comprehensive approach aims to enhance well monitoring and management, ensuring timely responses to changes in well conditions.
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