A Novel Efficient Borehole Cleaning Model for Optimizing Drilling Performance in Real Time
<p>The flowchart outlining the various topics discussed and the systematic order in which they are presented.</p> "> Figure 2
<p>Parameters and their effect on borehole cleaning.</p> "> Figure 3
<p>Influence of rotation on cuttings bed; (<b>a</b>) low RPM; (<b>b</b>) medium RPM; (<b>c</b>) at 120 RPM.</p> "> Figure 4
<p>Read of maximum ROP based on the TI values and the borehole angle. Chart is based on Luo’s chart [<a href="#B37-applsci-13-07751" class="html-bibr">37</a>].</p> "> Figure 5
<p>Graphical chart for the <span class="html-italic">RF</span> in borehole size 17–12″. Chart is based on Luo’s chart [<a href="#B38-applsci-13-07751" class="html-bibr">38</a>].</p> "> Figure 6
<p>The interpolation of AF based on the borehole angle.</p> "> Figure 7
<p>The measured, calculated, and output of the novel model <span class="html-italic">TI<sub>m</sub></span>, which is a real-time automated assessment for evaluating borehole cleaning conditions.</p> "> Figure 8
<p>The performance of TI<sub>m</sub> in relation to three key parameters: (<b>a</b>) MW<sub>eff</sub>, (<b>b</b>) ECD, and (<b>c</b>) modified LC<sub>m</sub>.</p> "> Figure 9
<p>The performance of TI<sub>m</sub> in relation to three key parameters: (<b>a</b>) LSYP, (<b>b</b>) LSYP/YP, (<b>c</b>) modified n<sub>em</sub>, and (<b>d</b>) modified k<sub>em</sub>.</p> "> Figure 10
<p>Flowchart to estimate the novel TI<sub>m</sub> model in real time.</p> "> Figure 11
<p>Application of TI<sub>m</sub> in offshore Well-A with proper borehole cleaning (<b>a</b>) and Well-B with poor borehole cleaning (<b>b</b>).</p> "> Figure 12
<p>The changes in drilling parameters for Well-A with proper borehole cleaning and Well-B with poor borehole cleaning: (<b>a</b>) WOB, (<b>b</b>) SPP, (<b>c</b>) TRQ, and (<b>d</b>) ROP.</p> "> Figure 13
<p>Application of TI<sub>m</sub> in Well C in the case of a stuck pipe: (<b>a</b>) Well-C with poor borehole cleaning, (<b>b</b>) ROP, and (<b>c</b>) TRQ.</p> "> Figure 14
<p>The automated process of using field data to evaluate the status of hole cleaning using TI<sub>m</sub> for optimizing the drilling performance efficiency.</p> ">
Abstract
:1. Introduction
2. The Influence of Factors on Borehole Cleaning
The Main Models to Evaluate the Borehole Cleaning Efficiency
3. Mathematical Development of the Model for the TIm
4. Results and Discussion
4.1. Methodology
4.2. Effects of Parameters of the Drilling Fluids on the Novel Model TIm
4.3. Field Applications Using the Novel Model TIm
5. The Importance of Using the Novel TIm Model in Real-Time
6. Conclusions
- (1)
- The modified TIm model presented introduces novel approaches to consider the mud weight (MW) in both static and dynamic conditions (ECD) and accounts for various factors, including hydraulic velocities, rheological properties of drilling fluids (considering low shear yield point and a novel model for k and n factors considering taking into account CCAm), flow regime, cuttings properties, and equivalent circulating density. Additionally, in this paper, two novel models were developed: a model for calculating the modified angle factor through interpolation at any borehole angle and a novel model for the rheology factor (RF). Overall, the modified TIm provides a comprehensive and improved approach for evaluating and automating borehole cleaning conditions to enhance drilling efficiency.
- (2)
- The TIm model performed well in all drilling fluid types and different types of profile wells, providing accurate real-time information. The evaluation of the TIm model based on drilling fluid parameters and well profiles provides important insights into its effectiveness in various drilling conditions, enabling drilling operators to make informed decisions about the use of TIm in different drilling operations to optimize borehole cleaning. More importantly, the novel model can determine the optimum values of parameters, including the hydraulic, mechanical, and drilling fluid parameters.
- (3)
- By implementing the novel TIm model, the ROP in Well-A improved by a noteworthy 56% compared to Well-B. This improvement in ROP can be credited to the successful removal of cuttings from the borehole achieved through the application of the TIm model. Moreover, the torque in Well-A was reduced by 44%, indicating that the drilling operations in Well-A were more successful and efficient than those in Well-B.
- (4)
- These results highlight the potential benefits of using advanced novel models such as the TIm model to optimize the drilling performance and improve its efficiency and effectiveness. By achieving better borehole cleaning, drilling operators can improve ROP, reduce torque, and prevent costly issues such as stuck pipes.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Nomenclature
modified angle factor | |
novel model transport ratio, % | |
mud weight affecting the speed of slipping | |
effective mud weight, pcf | |
apparent viscosity, cP | |
rheology factor based on the consistency index of rheological properties of power law model | |
rheology factor based on the consistency index of rheological properties of power law model with the affecting factors of temperatures | |
average rheology factor | |
annular area, inches | |
cutting Fraction | |
outer diameter of drill collar | |
the drilling fluid flow rate, gal/min | |
time for making the connection, min | |
volumetric rate of cuttings entering the annulus, ft/min | |
cuttings slip velocity, ft/min | |
the slip velocity with considering the flow regime, ft/min | |
the new average slip velocity with considering the mud weight, ft/min | |
weigh of the cuttings, lb/cf | |
the consistency index of rheological properties of power law model by including the cuttings concentration in an annulus, cP | |
modified consistency factor, cP | |
the behavior factor of rheological properties of power law model by including the cuttings concentration in an annulus | |
modified flow behavior index | |
effective viscosity, cP | |
AF | angle factor |
CCA or | concentration of cuttings in the annulus |
CCI | cutting carrying index |
CD | drag coefficient |
CTR | cutting transport ratio |
dcm | modified cutting diameter, inch |
ECD | equivalent circulating density, pcf |
ECDm | modified equivalent circulating density, pcf |
GF | ultimate strength of gelation |
GI | initial strength of gelation |
GPM | pump flow rate, gal/min |
Hcrit | the critical height of the free region above the cuttings bed |
Hr | the height of the free region above the cuttings bed in the annulus |
consistency factor, cP | |
LC | original lifting capacity |
LCm | modified original lifting capacity |
LWD | logging while drilling |
MW | mud weight, pcf |
MWD | measurement while drilling |
flow behavior index | |
OD | drill pipe’s outer diameter, inch |
OH | borehole diameter, inch |
PV | plastic viscosity, cP |
PVm | modified plastic viscosity, cP |
R3 | 3 reading revolutions per minutes, cP |
R300 | 300 reading revolutions per minutes, cP |
R6 | 6 reading revolutions per minutes, cP |
R600 | 600 reading revolutions per minutes, cP |
ROP | rate of penetration, ft/hr |
RPM | revolution per minute, rev/min |
RSS | rotary steerable system |
SPP | stand pipe pressure, psi |
TIm | novel transport index indicator |
TRQ | torque, kIbs-ft |
Vann | annular velocity, ft/min |
Vann.m | modified annular velocity, ft/min |
Vs1 and Vs2 | velocity with consideration for the effective viscosity and apparent viscosity of a fluid, as well as the weight and diameter of the cuttings present in the fluid, ft/min |
Vsc | velocity of cutting slip due to ROP, ft/min |
WOB | weight on bit, KIb |
x | revolution per gallon ratio |
YP | yield point, cP |
YPm | modified yield point, cP |
β | borehole azimuth, degrees |
borehole angle of inclinations, degrees |
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№ | Name of Model | Equations | Definition | Ref. |
---|---|---|---|---|
1 | Hole cleaning ration (HCR) | The HCR is a ratio between the free height of the drilling fluid in the annulus and the critical height of the cuttings bed, and it is commonly utilized to assess the risk of a pipe becoming stuck during drilling operations. | [27] | |
2 | ) | is used to indicate the borehole cleaning efficiency in vertical borehole sections. | [13] | |
3 | is commonly utilized to assess the cessation of circulating during connections and the circulation which occurs prior to a connection. | [35] | ||
4 | The is commonly utilized to assess the steady state lifting solids in the vertical tube. | [8] | ||
5 | ) | is used to evaluate the efficiency with which cuttings are removed from the wellbore. | [36] | |
6 | ) | is utilized to evaluate the borehole cleaning attributes for optimal cuttings lifting ability and cuttings lifting coefficient, both of which provide requirements for cutting lifting in a wellbore. | [17] | |
7 | ) | is used to evaluate the effectiveness of the drilling fluid in removing cuttings and maintaining a clean wellbore. | [37] |
AF by Luo [38] | AF by Unegbu [21] | ||
---|---|---|---|
Borehole Angle | Angle Factor | Borehole Angle | Angle Factor |
0 | - | 0 | 2.03 |
25 | 1.51 | 25 | 1.51 |
30 | 1.39 | 30 | 1.39 |
35 | 1.31 | 35 | 1.31 |
40 | 1.24 | 40 | 1.24 |
45 | 1.18 | 45 | 1.18 |
50 | 1.14 | 50 | 1.14 |
55 | 1.1 | 55 | 1.1 |
60 | 1.07 | 60 | 1.07 |
65 | 1.05 | 65 | 1.05 |
70–80 | 1.02 | 70 | 1.02 |
80–90 | 1 | 80 | 1 |
Parameter | The Drilling Fluids Range Properties |
---|---|
The density of oil-based drilling fluid density | 80 lb/ft3 for Well-A and Well-B 88-lb/ft3 for Well C |
The ratio of oil | (0.7–0.8) |
The ratio of water | (0.2–0.3) |
The value of electrical stability | (500–1000) V |
Percent of low gravity solids | (2–6) (%) |
Percent of high gravity solids | (9–16) (%) |
March funnel viscosity | (55–80) (s) |
Percent of solid content | (10–15) (%) |
Mud solid control | 0.4–0.55 |
Main Parameters | Minimum | Maximum | Average |
---|---|---|---|
α | 30 | 90 | 60 |
β | 69 | 110 | 90 |
MW | 80 | 80 | 80 |
PV | 31 | 32 | 31.5 |
YP | 23 | 24 | 23.5 |
R3 | 12 | 13 | 13.5 |
R6 | 13 | 14 | 13.5 |
WOB | 10 | 40 | 24.5 |
RPM | 49 | 177 | 153.6 |
GPM | 590 | 1033 | 958 |
SPP | 898 | 2729 | 2411 |
Main Parameters | Minimum | Maximum | Average |
---|---|---|---|
α | 30 | 90 | 60 |
β | 55 | 145 | 98.3 |
MW | 80 | 80 | 80 |
PV | 30 | 30 | 30 |
YP | 23 | 23 | 23 |
R3 | 11 | 11 | 11 |
R6 | 8 | 8 | 8 |
WOB | 22 | 40 | 30 |
RPM | 50 | 190 | 170 |
GPM | 642.2 | 688.78 | 686 |
SPP | 1500 | 3004 | 2740 |
Main Parameters | Minimum | Maximum | Average |
---|---|---|---|
α | 22.9 | 90 | 75.5 |
β | 88 | 120 | 110 |
MW | 88 | 88 | 88 |
PV | 19 | 29 | 24.5 |
YP | 20 | 24 | 20.7 |
R3 | 7 | 9 | 8.5 |
R6 | 9 | 11 | 9.8 |
WOB | 0 | 38 | 27 |
RPM | 42 | 103 | 78.5 |
GPM | 272 | 778 | 565 |
SPP | 1060 | 4420 | 3934 |
Model on the Performance of Well-A | |||||
---|---|---|---|---|---|
№ | Items (Output) | Minimum | Maximum | Average | Statement |
1 | TIm | 1.4 | 4 | 2.4 | Effective borehole cleaning |
2 | ROP | 120 | 280 | 209 | Optimized ROP by 56% due to the effective borehole cleaning |
3 | TRQ | 5 | 18 | 9.6 | Decreased TRQ by 44% due to the effective borehole cleaning |
Effect of Using the Novel Model on the Performance of Well-B | |||||
№ | Items (output) | Minimum | Maximum | Average | Statement |
1 | TIm | 0.47 | 1.4 | 0.79 | Insufficient borehole cleaning |
2 | ROP | 105 | 258 | 134 | Lower ROP due to the insufficient borehole cleaning |
3 | TRQ | 13 | 22 | 17 | Higher TRQ due to the insufficient borehole cleaning and cutting accumulation |
Model on the Performance of Well-C | |||||
---|---|---|---|---|---|
№ | Items (Output) | Minimum | Maximum | Average | Statement |
1 | TIm | 0.25 | 1.8 | 0.56 | Insufficient borehole cleaning |
2 | ROP | 4.92 | 166 | 93.3 | Lower ROP due to insufficient borehole cleaning |
3 | TRQ | 7.24 | 16 | 12.5 | Higher TRQ due to the cutting accumulation resulted in stuck pipe incident |
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Al-Rubaii, M.; Al-Shargabi, M.; Al-Shehri, D.; Alyami, A.; Minaev, K.M. A Novel Efficient Borehole Cleaning Model for Optimizing Drilling Performance in Real Time. Appl. Sci. 2023, 13, 7751. https://doi.org/10.3390/app13137751
Al-Rubaii M, Al-Shargabi M, Al-Shehri D, Alyami A, Minaev KM. A Novel Efficient Borehole Cleaning Model for Optimizing Drilling Performance in Real Time. Applied Sciences. 2023; 13(13):7751. https://doi.org/10.3390/app13137751
Chicago/Turabian StyleAl-Rubaii, Mohammed, Mohammed Al-Shargabi, Dhafer Al-Shehri, Abdullah Alyami, and Konstantin M. Minaev. 2023. "A Novel Efficient Borehole Cleaning Model for Optimizing Drilling Performance in Real Time" Applied Sciences 13, no. 13: 7751. https://doi.org/10.3390/app13137751