Research Papers: Petroleum Engineering

Modeling and Experimental Study of Solid–Liquid Two-Phase Pressure Drop in Horizontal Wellbores With Pipe Rotation

[+] Author and Article Information
Mehmet Sorgun

Department of Civil Engineering,
Izmir Katip Celebi University,
Izmir 35620, Turkey
e-mail: mehmetsorgun@gmail.com

Erman Ulker

Department of Mechanical Engineering,
Izmir Katip Celebi University,
Izmir 35620, Turkey

1Corresponding author.

Contributed by the Petroleum Division of ASME for publication in the JOURNAL OF ENERGY RESOURCES TECHNOLOGY. Manuscript received March 12, 2015; final manuscript received September 29, 2015; published online October 20, 2015. Assoc. Editor: Egidio Marotta.

J. Energy Resour. Technol 138(2), 022902 (Oct 20, 2015) (5 pages) Paper No: JERT-15-1115; doi: 10.1115/1.4031743 History: Received March 12, 2015; Revised September 29, 2015

Determining pressure loss for cuttings-liquid system is very complicated task since drillstring is usually rotating during drilling operations and cuttings are present inside wells. While pipe rotation is increasing the pressure loss of Newtonian fluids without cuttings in an eccentric annulus, a reduction in the pressure loss for cuttings-liquid system is observed due to the bed erosion. In this study, cuttings transport experiments for different flow rates, pipe rotation speeds, and rate of penetrations (ROPs) are conducted. Pressure loss within the test section and stationary and/or moving bed thickness are recorded. This study aims to predict frictional pressure loss for solid (cuttings)–liquid flow inside horizontal wells using computational fluid dynamics (CFD) and artificial neural networks (ANNs). For this purpose, numerous ANN structures and CFD models are developed and tested using experimental data. Among the ANN structures, TrainGdx–Tansig structure gave more accurate results. The results show that the ANN showed better performance than the CFD. However, both could be used to estimate solid–liquid two-phase pressure drop in horizontal wellbores with pipe rotation.

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Fig. 2

The basic model of ANN [16]

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Fig. 1

Cuttings transport flow loop [5]

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Fig. 3

Comparison of CFD and ANN simulations with experimental data for pipe rotation (rpm) = 0 and rates of penetration = 15 ft/hr

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Fig. 4

Comparison of CFD and ANN simulations with experimental data for pipe rotation (rpm) = 60 and rates of penetration = 80 ft/hr

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Fig. 5

Comparison of CFD and ANN simulations with experimental data for pipe rotation (rpm) = 80 and rates of penetration = 80 ft/hr

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Fig. 6

Comparison of CFD simulation with experimental data for pipe rotation (rpm) = 120 and rates of penetration = 45 ft/hr

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Fig. 7

Comparison of measured and estimated pressure gradient values using CFD

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Fig. 8

Comparison of measured and estimated pressure gradient values using ANN



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