Terminal settling velocity of a single sphere in drilling fluid

Rushd, Sayeed; Hassan, Ibrahim; Sultan, Rasel A.; Kelessidis, Vassilios C.; Rahman, Mohammad Azizur; Hasan, Hussain S.; Hasan, Anwarul

doi:10.1080/02726351.2018.1472162

Cited by 22 publications

(9 citation statements)

References 34 publications

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“…Based on the Stokes law, many empirical and semi-empirical correlations have been developed afterward. For example, the C D -Re p correlation proposed by Cheng was found to perform better compared to seven (7) other similar models [4]. All of these models were developed for spherical particles in Newtonian fluids.…”

Section: Introductionmentioning

confidence: 99%

“…Although applying this kind of correlation is comparatively easier for a Newtonian fluid, a similar application to a non-Newtonian fluid is not convenient at all. Modeling complex non-Newtonian rheology is a difficult task [2,5,7,8,12,16,[19][20][21][23][24][25][26][27]. Nevertheless, a C D -Re p correlation can be used to predict V s in a non-Newtonian fluid by replacing Re p with a generalized particle Reynolds number (Re G ) [6,7,12,16,19,20].…”

Section: Introductionmentioning

confidence: 99%

“…Modeling complex non-Newtonian rheology is a difficult task [2,5,7,8,12,16,[19][20][21][23][24][25][26][27]. Nevertheless, a C D -Re p correlation can be used to predict V s in a non-Newtonian fluid by replacing Re p with a generalized particle Reynolds number (Re G ) [6,7,12,16,19,20]. The equivalent viscosity used to define Re G is usually measured or estimated at a shear rate ( .…”

Section: Introductionmentioning

confidence: 99%

“…The non-Newtonian rheology of an HB fluid is defined with Equation (5). It can be transformed into proper models for other rheologies such as Newtonian (τ = K Re G , the modified formula requires validation and further modification before applying to predict the V s in a non-Newtonian fluid (see, for example, [2,7,19,20]). This is because the uncertainty associated with the values predicted using the original C D -Re G correlation can be unacceptable.…”

Section: Introductionmentioning

confidence: 99%

“…Explicit models are, in general, convenient to apply. However, this kind of correlation has some noteworthy limitations, such as rheology specificity, higher uncertainty, constrained range of Re G , and limited capability of addressing the effect of τ o [1,2,6,7,11,16,19,20].…”

Section: Introductionmentioning

confidence: 99%

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Modeling the Settling Velocity of a Sphere in Newtonian and Non-Newtonian Fluids with Machine-Learning Algorithms

et al. 2021

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The traditional procedure of predicting the settling velocity of a spherical particle is inconvenient as it involves iterations, complex correlations, and an unpredictable degree of uncertainty. The limitations can be addressed efficiently with artificial intelligence-based machine-learning algorithms (MLAs). The limited number of isolated studies conducted to date were constricted to specific fluid rheology, a particular MLA, and insufficient data. In the current study, the generalized application of ML was comprehensively investigated for Newtonian and three varieties of non-Newtonian fluids such as Power-law, Bingham, and Herschel Bulkley. A diverse set of nine MLAs were trained and tested using a large dataset of 967 samples. The ranges of generalized particle Reynolds number (ReG) and drag coefficient (CD) for the dataset were 10−3 < ReG (-) < 104 and 10−1 < CD (-) < 105, respectively. The performances of the models were statistically evaluated using an evaluation metric of the coefficient-of-determination (R2), root-mean-square-error (RMSE), mean-squared-error (MSE), and mean-absolute-error (MAE). The support vector regression with polynomial kernel demonstrated the optimum performance with R2 = 0.92, RMSE = 0.066, MSE = 0.0044, and MAE = 0.044. Its generalization capability was validated using the ten-fold-cross-validation technique, leave-one-feature-out experiment, and leave-one-data-set-out validation. The outcome of the current investigation was a generalized approach to modeling the settling velocity.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Modeling the Settling Velocity of a Sphere in Newtonian and Non-Newtonian Fluids with Machine-Learning Algorithms

et al. 2021

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Effects of salinity on solid particle settling velocity in non-Newtonian Herschel–Bulkley fluids

Moukhametov

Srivastava

Akhter

et al. 2021

J Petrol Explor Prod Technol

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Settling velocity or depositional velocity is considered a key parameter to account for in the drilling technology of oil and gas wells as well as hydrocarbon processing since an accurate estimation of this parameter allows the transport of cuttings efficiently, avoids non-productive time, and helps avoid costly problems. Understanding the settling velocity in fluid with high salinity will help for the better separation of oil and natural gas streams in processing facilities. Although a great amount of effort was given to rheology and settling velocity measurements for power-law fluid and Bingham fluids, there are limited studies available in the literature for Herschel–Bulkley (H–B) fluid with salinity. The present study analyzes the fluid rheology of non-Newtonian fluids with, and without, salinity. Moreover, experiments have been conducted to measure the settling velocity of different diameters of solid particles through Herschel–Bulkley fluids with various salinity conditions. For the rheology analysis, it is found that higher weight percentages of NaCl lead to low values of shear stresses. As well, higher weight percentages of CaCl2 concentration result in a slight increase in shear stresses per a given shear rate. On the other hand, higher percentages of salt concentration cause an increase in the terminal velocity.

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Predicting wall drag coefficient and settling velocity of particle in parallel plates filled with Newtonian fluids

Zhu

Song

et al. 2021

Particuology

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Terminal settling velocity of a single sphere in drilling fluid

Cited by 22 publications

References 34 publications

Modeling the Settling Velocity of a Sphere in Newtonian and Non-Newtonian Fluids with Machine-Learning Algorithms

Modeling the Settling Velocity of a Sphere in Newtonian and Non-Newtonian Fluids with Machine-Learning Algorithms

Effects of salinity on solid particle settling velocity in non-Newtonian Herschel–Bulkley fluids

Predicting wall drag coefficient and settling velocity of particle in parallel plates filled with Newtonian fluids

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