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.

References

1.
Ozbayoglu
,
M. E.
,
Saasen
,
A.
,
Sorgun
,
M.
, and
Svanes
,
K.
,
2007
, “
Estimating Critical Velocity to Prevent Bed Development for Horizontal-Inclined Wellbores
,”
SPE/IADC Middle East Drilling Technology Conference and Exhibition
, Cairo, Egypt, Oct. 22–24, Paper No.
SPE/IADC
108005.
2.
Saasen
,
A.
,
Eriksen
,
N. H.
,
Han
,
L.
,
Labes
,
P.
, and
Marken
,
D.
,
1998
, “
Is Annular Friction Loss the Key Parameter?
Oil Gas Eur. Mag.
,
24
(
1
), pp.
22
24
.
3.
Sorgun
,
M.
,
2013
, “
Simple Correlations and Analysis of Cuttings Transport With Newtonian and Non-Newtonian Fluids in Horizontal and Deviated Wells
,”
ASME J. Energy Resour. Technol.
,
135
(
3
), p.
032903
.
4.
Ozbayoglu
,
M. E.
, and
Sorgun
,
M.
,
2010
, “
Frictional Pressure Loss Estimation of Water-Based Drilling Fluids at Horizontal and Inclined Drilling With Pipe Rotation and Presence of Cuttings
,”
SPE Oil and Gas India Conference and Exhibition in Mumbai
, India, Jan. 20–22,
SPE
Paper No. 127300.
5.
Sorgun
,
M.
,
Aydin
,
I.
, and
Ozbayoglu
,
M. E.
,
2011
, “
Friction Factors for Hydraulic Calculations Considering Presence of Cuttings and Pipe Rotation in Horizontal/Highly-Inclined Wellbores
,”
J. Pet. Sci. Eng.
,
78
(
2
), pp.
407
414
.
6.
Alizadehdakhel
,
A.
,
Rahimi
,
M.
,
Sanjari
,
J.
, and
Alsairafi
,
A. A.
,
2009
, “
CFD and Artificial Neural Network Modeling of Two-Phase Flow Pressure Drop
,”
Int. Commun. Heat Mass Transfer
,
36
(
8
), pp.
850
856
.
7.
Sun
,
X.
,
Wang
,
K.
,
Yan
,
T.
,
Shao
,
S.
, and
Jiao
,
J.
,
2014
, “
Effect of Drillpipe Rotation on Cuttings Transport Using Computational Fluid Dynamics (CFD) in Complex Structure Wells
,”
J. Pet. Explor. Prod. Technol.
,
4
(
3
), pp.
255
261
.
8.
Rooki
,
R.
,
2015
, “
Estimation of Pressure Loss of Herschel–Bulkley Drilling Fluids During Horizontal Annulus Using Artificial Neural Network
,”
J. Dispersion Sci. Technol.
,
36
(
2
), pp.
161
169
.
9.
Sorgun
,
M.
,
Ozbayoglu
,
M. A.
, and
Ozbayoglu
,
E. M.
,
2014
, “
Support Vector Regression and Computational Fluid Dynamics Modeling of Newtonian and Non-Newtonian Fluids in Annulus With Pipe Rotation
,”
ASME J. Energy Resour. Technol.
,
137
(
3
), p.
032901
.
10.
Akhshik
,
S.
,
Behzad
,
M.
, and
Rajabi
,
M.
,
2015
, “
CFD–DEM Approach to Investigate the Effect of Drill Pipe Rotation on Cuttings Transport Behavior
,”
J. Pet. Sci. Eng.
,
127
, pp.
229
244
.
11.
Fu
,
T. K.
,
Osgouei
,
R. E.
, and
Ozbayoglu
,
E. M.
,
2013
, “
CFD Simulation of Solids Carrying Capacity of a Newtonian Fluid Through Horizontal Eccentric Annular
,”
ASME
Paper No. FEDSM2013-16204.
12.
van Wachem
,
B. G. M.
, and
Almstedt
,
A. E.
,
2003
, “
Methods for Multiphase Computational Fluid Dynamics
,”
Chem. Eng. J.
,
96
(
1–3
), pp.
81
98
.
13.
Eesa
,
M.
, and
Barigou
,
M.
,
2009
, “
CFD Investigation of the Pipe Transport of Coarse Solids in Laminar Power Law Fluids
,”
Chem. Eng. Sci.
,
64
(
2
), pp.
322
333
.
14.
Enwald
,
H.
,
Peirano
,
E.
, and
Almstedt
,
A.
,
1996
, “
Eulerian Two-Phase Flow Theory Applied to Fluidization
,”
Int. J. Multiphase Flow
,
22
(
Suppl.
), pp.
21
66
.
15.
ANSYS
,
2009
,
ANSYS Workbench CFX
, Version 12.1,
ANSYS
, Inc., Canonsburg, PA.
16.
Ozbayoglu
,
E. M.
, and
Ozbayoglu
,
M. A.
,
2009
, “
Estimating Flow Patterns and Frictional Pressure Losses of Two-Phase Fluids in Horizontal Wellbores Using Artificial Neural Networks
,”
Pet. Sci. Technol.
,
27
(
2
), pp.
135
149
.
17.
Mohaghegh
,
S.
,
2000
, “
Virtual-Intelligence Applications in Petroleum Engineering: Part 1—Artificial Neural Networks
,”
SPE J.
,
52
(
9
), pp.
64
73
.
18.
Kolmogorov
,
A. N.
,
1957
, “
On the Representation of Continuous Functions of Several Variables by Superposition of Continuous Functions of One Variable and Addition
,”
Dokl. Akad. Nauk SSSR
,
114
, pp.
359
373
.
You do not currently have access to this content.