@article{scholars16545,
             doi = {10.1016/j.jngse.2022.104660},
          volume = {104},
           title = {Development of pressure gradient correlation for slurry flow using dimensional analysis},
            note = {cited By 3},
       publisher = {Elsevier B.V.},
            year = {2022},
         journal = {Journal of Natural Gas Science and Engineering},
            issn = {18755100},
        abstract = {Accurate and speedy determination of pressure drop during cuttings transport is an important aspect of a drilling operation. However, the literature suggests that there is a lack of a simple, ready to use, and accurate model that can predict pressure drop for settling solid-liquid flow during the drilling operation. Therefore, this study aims to develop a non-dimensional model that can be used for quick and real-time pressure drop prediction during cuttings transport through the annulus for a wide range of hydrodynamic (viscosity, surface tension, density) and operating (drill pipe rotation, eccentricity, inclination, liquid flow rate) parameters. The model development strategy includes the development of non-dimensional parameters using the Buckingham Pi approach. Experimental data points were extracted from the original experiments and 5 different works of literature for model optimization and validation to increase the range of the model and make it system independent. The results of this study showed that the developed model has a higher accuracy as compared to the SK correlation and Turian model and shows a Mean Absolute Percentage Error (MAPE) of 16.83 for the original experimental data and 20.09 for the entire data set. Model shrinkage was done using power-law minimization which showed that the cuttings transport system needs to have an optimum of 7{\^a}??8 non-dimensional parameters, which was supported by using statistical analysis. The developed model can be used for real-time hole cleaning monitoring on drilling rigs and can help minimize hole cleaning issues related to pressure loss. {\^A}{\copyright} 2022 Elsevier B.V.},
          author = {Barooah, A. and Khan, M. S. and Khaled, M. S. and Manikonda, K. and Rahman, M. A. and Hassan, I. and Hasan, R. and Maheshwari, P. and Hascakir, B.},
        keywords = {Cleaning; Drops; Infill drilling; Pressure gradient, Cuttings transport; Developed model; Dimensional analysis; Drilling operation; Experimental pressure gradient; Hole cleaning; Non-dimensional correlation; Non-dimensional parameters; Pressure drop correlation; Real- time, Pressure drop},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85131716488&doi=10.1016\%2fj.jngse.2022.104660&partnerID=40&md5=216e746971e6b6faa926b10d82668396}
}