This paper details a novel new system for real-time analysis of drilling muds. The system uses in-flow digital imaging to capture images of all particulates in drilling mud. Sophisticated image processing algorithms are used in real time to segment each particle from the background, and record over 30 size, shape and gray-scale measurements for each particle. Particle size and shape distributions are produced in real-time, and are used for trend analysis. This system can be integrated into any part of the drilling flow loop for analysis at any point in the process. Using a unique auto-dilution system, the concentration is automatically adjusted for optimum presentation of the particulates to the imaging system. Since every particle image and its measurements are saved by the system, it creates an ironclad audit trail for how particle size distributions are derived. While the basic system architecture is very robust and could be used in many different applications, the system presented here has been fully optimized for the analysis of particulates in drilling mud. Real-world data collected in the field is shown illustrating typical results from the system. A brief description is provided on how the system works in real-time, including how the particle images are acquired and measurements made. Finally the results of the analysis are shown, detailing how the system can be used to monitor particle size and shape distributions from any part of the flow loop. This resulting analytical data becomes an integral part of the real-time operation of the drilling platform, ensuring continuous optimization of the drilling mud particulate content. This optimization is critical to the performance of the drilling mud, for cooling and lubrication of the drill bit, interacting with the surrounding geology and maintaining proper rheological characteristics. This system represents a new way of proactively monitoring drilling mud content in real-time, and provides more information than prior systems because the system can measure particle size as well as shape. Particle shape information can be used by the system software to automatically classify particulates into different component types.


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