Аннотация
Accurate, real-time characterization of drilling fluid rheological properties, such as plastic viscosity, yield stress, and gel strength, is vital for optimizing oil and gas drilling operations and advancing sustainable exploration. This study assesses advanced sensor technologies � ultrasonic sensors, inline viscometers, optical flow analyzers, and microfluidic sensors�for automated, real-time measurement of these properties in water-based, oil-based, and synthetic-based muds. Experiments utilized a closed-loop flow rig mimicking field conditions (25�150�C, 0.1�10 MPa), with API-standard fluids for calibration. Inline viscometers achieved the highest accuracy (MAE = 0.2 cP for viscosity, = 0.1 Pa for yield stress) and reliability (R� > 0.98) against the Fann 35 viscometer, with response times of 0.5 s. Ultrasonic sensors performed robustly (MAE = 0.4 cP), while optical and microfluidic sensors struggled with opaque fluids (MAE up to 1.0 cP) and low-shear conditions (errors up to 15%). Limitations, including sensor fouling and high-pressure interference, were addressed with proposed automated cleaning and adaptive calibration. These systems reduce human error and enhance efficiency. Future work will improve optical/microfluidic sensors, test extreme conditions (>150�C, >10 MPa), and integrate deep learning for predictive fluid modeling, aligning with recent AI-driven advancements.