Application of Descriptive Data Analytics: How to Properly Select the Best Ranges of Viscosity and Flow Rate for Optimal Hole Cleaning?
- Husam H. Alkinani (Missouri University of Science and Technology) | Abo Taleb T. Al-Hameedi (Missouri University of Science and Technology) | Shari Dunn-Norman (Missouri University of Science and Technology) | Mustafa A. Al-Alwani (Missouri University of Science and Technology) | David Lian (Missouri University of Science and Technology) | Waleed H. Al-Bazzaz (Kuwait Institute For Scientific Research)
- Document ID
- Society of Petroleum Engineers
- SPE Eastern Regional Meeting, 15-17 October, Charleston, West Virginia, USA
- Publication Date
- Document Type
- Conference Paper
- 2019. Society of Petroleum Engineers
- Data Collection, Oil & Gas Industry
- 1 in the last 30 days
- 69 since 2007
- Show more detail
- View rights & permissions
|SPE Member Price:||USD 5.00|
|SPE Non-Member Price:||USD 28.00|
It is not easy to obtain an optimal hole cleaning for the drilling operation because of the complicated relationship between the drilling parameters influencing hole cleaning. The two viscosity components (e.g. plastic viscosity (PV) and yield point (YP)) and the flow rate (Q) are essential parameters for effective hole cleaning. Thus, understanding the relationship between those parameters will contribute to efficient hole cleaning. The aim of this paper is to explore those relationships to provide optimal hole cleaning.
Descriptive data analytics was conducted for data of more than 2000 wells drilled in Southern Iraq. The data were first cleansed and outliers were removed using visual inspection and box plots. The Pearson correlation (PC), a widely used method to measure the linear relationship between two parameters, was utilized to access the relationships between PV and Q, YP and Q, and YP/PV and Q. Moreover, a 10% sensitivity analysis was escorted to quantify and comprehend those relationships.
The PCs were calculated to be 0.5, 0.076, and 0.22 for the relationships between YP, PV, and YP/PV with Q, respectively. YP had the highest direct relationship with Q, while PV had the lowest. When the YP increases, a sufficient Q has to be provided to initiate the flow and maintain the mud cycle. In addition, to prevent large solid particles from settling due to the slip velocity, sufficient annular and particle velocities have to be achieved. After initiating the flow, an increase in flow rate to overcome resistance due to PV will not be significant. Therefore, YP has more effect on Q than PV. To maximize hole cleaning, thickening ratio (YP/PV) should be increased. This requires an increase in flow rate, which can be quantified by using the sensitivity analysis provided to achieve the required Q for any increase in YP/PV.
|File Size||1 MB||Number of Pages||9|
Aldred, W.,Cook, J.,Bern, P.,Carpenter, B.,Huchinson, M.,Rezmer-Cooper, I., & Leder, P. C. (1998). Oilfield Review Winter 1998. Retrieved September 10, 2018, from www.slb.com/resources/oilfield_review/en/1998/or1998_win.aspx
Al-Hameedi AT,Alkinani HH,Dunn-Norman S,Flori RE,Hilgedick SA,Amer AS (2017a) Limiting Key Drilling Parameters to Avoid or Mitigate Mud Losses in the Hartha Formation, Rumaila Field, Iraq. J Pet Environ Biotechnol 8: 345. doi:10.4172/2157-7463.1000345.
Al-Hameedi, A. T. T.,Alkinani, H. H.,Dunn-Norman, S.,Flori, R. E.,Hilgedick, S. A.,Alkhamis, M. M.,Alsaba, M. T. (2018a, August 16). Predictive Data Mining Techniques for Mud Losses Mitigation. Society of Petroleum Engineers. doi:10.2118/192182-MS
Al-Hameedi, A. T. T.,Alkinani, H. H.,Dunn-Norman, S.,Flori, R. E.,Hilgedick, S. A.,Alsaba, M. T., & Amer, A. S. (2018b, November 12). Mud Losses Estimation Using Partial Least Squares Algorithm. Society of Petroleum Engineers. doi:10.2118/193266-MS
Al-Hameedi, A. T. T.,Alkinani, H. H.,Dunn-Norman, S.,Flori, R. E.,Hilgedick, S. A.,Amer, A. S., & Alsaba, M. T. (2018c, October 19). Using Machine Learning to Predict Lost Circulation in the Rumaila Field, Iraq. Society of Petroleum Engineers. doi:10.2118/191933-MS
Al-Hameedi, A. T. T.,Alkinani, H. H.,Dunn-Norman, S.,Flori, R. E.,Hilgedick, S. A.,Amer, A. S., & Alsaba, M., (2018d). Mud loss estimation using machine learning approach. Journal of Petroleum Exploration and Production Technology. https://doi.org/10.1007/s13202-018-0581-x
Al-Hameedi, A. T. T.,Alkinani, H. H.,Dunn-Norman, S., & Amer, A. S. (2019a, April 8). Insights into the Relationship between Equivalent Circulation Density and Drilling Fluid Rheological Properties. Society of Petroleum Engineers. doi:10.2118/194623-MS
Al-Hameedi, A.T.,Alkinani, H.H.,Dunn-Norman, S.,Al-Alwani, M.A.,Lian, D., (2019b). Equivalent Circulation Density Optimization: Can Flow Regimes Significantly Affect the Relationship Between Equivalent Circulation Density and Flow Rate? Paper SPE-196571-MS accepted, and it will be presented at the SPE Eastern Regional Meeting held in Charleston, West Virginia, 15–17 October 2019.
Al-Hameedi, A.T.,Dunn-Norman, S.,Alkinani, H.H.,Flori, R.E., and Hilgedick, S.A. (2017c). Limiting Drilling Parameters to Control Mud Losses in the Shuaiba Formation, South Rumaila Field, Iraq. Paper AADE-17- NTCE- 45 accepted, and it was presented at the 2017 AADE National Technical Conference and Exhibition held at the Hilton Houston.
Alkinani, H. H.,Al-Hameedi, A. T.,Flori, R. E.,Dunn-Norman, S.,Hilgedick, S. A., & Alsaba, M. T. (2018a, April 22). Updated Classification of Lost Circulation Treatments and Materials with an Integrated Analysis and their Applications. Society of Petroleum Engineers. doi:10.2118/190118-MS.
Alkinani, H.H.,Al-Hameedi, A.T.T.,Dunn-Norman, S.,Flori, R.E.,Hilgedick, S.A.,Al-Maliki, M.A.,Alshawi, Y.Q.,Alsaba, M.T., and Amer, A.S. 2018b. "Examination of the Relationship Between Rate of Penetration and Mud Weight Based on Unconfined Compressive Strength of the Rock." Journal of King Saud University - Science. https://doi.org/10.1016/j.jksus.2018.07.020.
Alkinani, H.H.,Al-Hameedi, A.T.T.,Dunn-Norman, S.,Flori, R.E.,Alsaba, M.T.,Amer, A.S., and Hilgedick, S.A. 2019. "Using Data Mining to Stop or Mitigate Lost Circulation." Journal of Petroleum Science and Engineering, vol. 173 (February 2019), 1097–1108. https://doi.org/10.1016/j.petrol.2018.10.078.
Bansal, R. K.,Brunnert, D. J.,Todd, R. J.,Bern, P. A.,Baker, R. V., & Richard, C., (2007, January 1). Demonstrating Managed-Pressure Drilling with the ECD Reduction Tool. Society of Petroleum Engineers. doi:10.2118/105599-MS
Bern, P. A.,Hosie, D.,Bansal, R. K.,Stewart, D., & Lee, B., (2003, January 1). A New Downhole Tool for ECD Reduction. Society of Petroleum Engineers. doi:10.2118/79821-MS
Hubert, M., & Vandervieren, E. (2008). An adjusted boxplot for skewed distributions. Computational Statistics & Data Analysis, 52(12), 5186–5201. https://doi.org/https://doi.org/10.1016/j.csda.2007.11.008
McCann, R. C.,Quigley, M. S.,Zamora, M., & Slater, K. S. (1995, June 1). Effects of High-Speed Pipe Rotation on Pressures in Narrow Annuli. Society of Petroleum Engineers. doi:10.2118/26343-PA.
Olson, D. L. (2017). Descriptive Data Mining. Springer Singapore. doi:10.1007/978-981-10-3340-7
Vajargah, A. K.,Sullivan, G., & Oort, E. van. (2016, September 14). Automated Fluid Rheology and ECD Management. Society of Petroleum Engineers. doi:10.2118/180331-MS.