Automated Particle Size and Shape Determination Methods: Application to Proppant Optimization

Abstract

The performance of proppants is critical to the effectiveness of reservoir hydraulic fracturing. Traditional methods such as sieving and visual inspection are commonly used in proppant production lines, at fracturing sites, and in research institutions to assess particle size and shape. However, these methods are highly subjective, inefficient, and prone to significant random errors. To address these issues, an automated particle size and shape detection method based on image processing algorithms was developed, leading to the design of a proppant parameter detection system. The system’s detection results on the Krumbein–Sloss chart closely align with standard templates, with a maximum error of only 3%. This method enables precise particle extraction and analysis from images, accurately determining particle size and shape parameters. Comparative experiments conducted on commonly used quartz sand samples in 20/40 mesh, 30/50 mesh, and 40/70 mesh specifications demonstrated that the new method can evaluate the particle size without damaging the particles; the detection process does not create proppant waste, has environmental benefits, and can reduce the cost of professional inspection personnel, with the detection efficiency improved by over 200 times compared to traditional sieving and visual inspection methods, with repeatability errors within 1.9%. This study introduces a novel approach to particle size and shape detection, providing technical references for optimizing proppant selection, enhancing material quality control for hydraulic fracturing, and reducing costs while improving efficiency.