{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T19:59:49Z","timestamp":1782417589784,"version":"3.54.5"},"reference-count":18,"publisher":"STEF92 Technology","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,12,27]]},"abstract":"<jats:p>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 \ufffd ultrasonic sensors, inline viscometers, optical flow analyzers, and microfluidic sensors\ufffdfor 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\ufffd150\ufffdC, 0.1\ufffd10 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\ufffd &gt; 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 (&gt;150\ufffdC, &gt;10 MPa), and integrate deep learning for predictive fluid modeling, aligning with recent AI-driven advancements.<\/jats:p>","DOI":"10.5593\/sgem2025v\/4.2\/s06.23","type":"proceedings-article","created":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T16:06:24Z","timestamp":1773763584000},"page":"211-220","source":"Crossref","is-referenced-by-count":0,"title":["APPLICATION OF SENSOR TECHNOLOGIES FOR AUTOMATED DETERMINATION OF RHEOLOGICAL PROPERTIES OF DRILLING FLUIDS"],"prefix":"10.5593","volume":"25","author":[{"given":"Aidar","family":"Kuttybayev","sequence":"first","affiliation":[{"name":"Satpayev University Republic of Kazakhstan","place":["Kazakhstan"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3607-5106","authenticated-orcid":true,"given":"Volodymyr","family":"Khomenko","sequence":"additional","affiliation":[{"name":"Dnipro University of Technology","place":["Ukraine"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3296-996X","authenticated-orcid":true,"given":"Oleksandr","family":"Pashchenko","sequence":"additional","affiliation":[{"name":"Dnipro University of Technology","place":["Ukraine"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Valerii","family":"Rastsvietaiev","sequence":"additional","affiliation":[{"name":"Dnipro University of Technology","place":["Ukraine"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2695-6823","authenticated-orcid":true,"given":"Makhiram","family":"Arshidinova","sequence":"additional","affiliation":[{"name":"Caspian University","place":["Kazakhstan"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"3602","reference":[{"key":"ref=2","unstructured":"[2] Biletsky M.T., Ratov B.T., Kozhevnykov A.?., Baiboz A.R., Delikesheva D.N., Updating the theoretic model of rock destruction in the course of drilling, News of the National Academy of Sciences of the Republic of Kazakhstan, Series of Geology and Technical Sciences, vol. 2(428), pp 63\ufffd71, 2018."},{"key":"ref=3","doi-asserted-by":"crossref","unstructured":"[3] Vytyaz O., Chernova O., Stavychnyi Y., Martyniuk R., Ziaja J., Increasing the reliability of oil and gas well fastening with polycomponent plugging systems, Mining of Mineral Deposits, 18(3), 82-93, 2024. https:\/\/doi.org\/10.33271\/mining18.03.082","DOI":"10.33271\/mining18.03.082"},{"key":"ref=4","doi-asserted-by":"crossref","unstructured":"[4] Biletsky M., Nifontov I., Ratov B., Delikesheva D., The problem of drilling mud parameters continuous monitoring and its solution at the example of automatic measurement of its density, NEWS of National Academy of Sciences of the Republic of Kazakhstan, vol. 6, pp 46\ufffd53, 2019. https:\/\/doi.org\/10.32014\/2019.2518-170x.154","DOI":"10.32014\/2019.2518-170X.154"},{"key":"ref=5","doi-asserted-by":"crossref","unstructured":"[5] Vynnykov Y., Kharchenko M., Manhura S., Aniskin A., Manhura, A. 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