Settling velocity of drill cuttings in drilling fluids: A review of experimental, numerical simulations and artificial intelligence studies

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@Article{AGWU:2018:PT,

• author = "Okorie E. Agwu and Julius U. Akpabio and Sunday B. Alabi and Adewale Dosunmu",
• title = "Settling velocity of drill cuttings in drilling fluids: A review of experimental, numerical simulations and artificial intelligence studies",
• journal = "Powder Technology",
• volume = "339",
• pages = "728--746",
• year = "2018",
• keywords = "genetic algorithms, genetic programming, Artificial Intelligence, Drill cuttings, Numerical simulations, Settling velocity",
• ISSN = "0032-5910",
• DOI = "doi:10.1016/j.powtec.2018.08.064",
• URL = "http://www.sciencedirect.com/science/article/pii/S0032591018307022",
• abstract = "In this paper, a comprehensive review of experimental, numerical and artificial intelligence studies on the subject of cuttings settling velocity in drilling muds made by researchers over the last seven decades is brought to the fore. In this respect, 91 experimental, 13 numerical simulations and 7 artificial intelligence researches were isolated, reviewed, tabulated and discussed. A comparison of the three methods and the challenges facing each of these methods were also reviewed. The major outcomes of this review include: (1) the unanimity among experimental researchers that mud rheology, particle size and shape and wall effect are major parameters affecting the settling velocity of cuttings in wellbores; (2) the prevalence of cuttings settling velocity experiments done with the mud in static conditions and the wellbore in the vertical configuration; (3) the extensive use of rigid particles of spherical shape to represent drill cuttings due to their usefulness in experimental visualization, particle tracking, and numerical implementation; (4) the existence of an artificial intelligence technique - multi-gene genetic programming (MGGP) which can provide an explicit equation that can help in predicting settling velocity; (5) the limited number of experimental studies factoring in the effect of pipe rotation and well inclination effects on the settling velocity of cuttings and (6) the most applied numerical method for determining settling velocity is the finite element method. Despite these facts, there is need to perform more experiments with real drill cuttings and factor in the effects of conditions such as drillstring rotation and well inclination and use data emanating therefrom to develop explicit models that would include the effects of these. It should be noted however, that the aim of this paper is not to create an encyclopaedia of particle settling velocity research, but to provide to the researcher with a basic, theoretical, experimental and numerical overview of what has so far been achieved in the area of cuttings settling velocity in drilling muds",
• keywords = "genetic algorithms, genetic programming, Artificial Intelligence, Drill cuttings, Numerical simulations, Settling velocity",

}

Genetic Programming entries for Okorie Ekwe Agwu Julius Udoh Akpabio Sunday B Alabi Adewale Dosunmu

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