Statistic Reability Test of Nozzle Geometry for Oil Well Hole Cleaning from Produced Sand

Abdullah Rizky Agusman; Eko Prastio; Citra Wahyuningrum

doi:10.29017/scog.v49i3.2121

Authors

Abdullah Rizky Agusman Universitas Bhayangkara Jakarta Raya (Ubhara Jaya) https://orcid.org/0000-0001-9793-6443
Eko Prastio Universitas Bhayangkara Jakarta Raya (Ubhara Jaya)
Citra Wahyuningrum Universitas Bhayangkara Jakarta Raya (Ubhara Jaya)

DOI:

https://doi.org/10.29017/scog.v49i3.2121

Keywords:

produced sand, jetting technology, nozzle engineering, wellbore cleanout, non-productive time, sand management

Abstract

Sand production is a major operational challenge in the upstream oil and gas industry, leading to perforation blockage, equipment erosion, and increased non-productive time (NPT). This study investigates the optimization of upward-facing nozzle jetting technology to improve sand cleanout efficiency in oil wells. The research experimental model was designed using the Buckingham Pi Theorem and Reynolds number similarity by scaling field conditions into a laboratory prototype. The study concludes that upward-facing nozzle engineering significantly enhances sand lifting efficiency and accelerates wellbore cleanout operations.Furthermore, numerical simulations and statistical analyses—including ANOVA, Shapiro-Wilk normality tests, and coefficient of determination (R²) evaluations—are systematically applied to validate the performance of the re-engineered jetting tool under varied operational parameters such as injection pressure, fluid flow rate, and sand mesh size. The results demonstrate that the proposed sequential dual-function protocol—comprising initial downward disaggregation followed by upward-facing nozzle activation—significantly enhances upward transport velocity and sand-lifting efficiency. Ultimately, this study concludes that upward-facing nozzle engineering significantly enhances sand lifting efficiency, reduces casing erosion risks, and accelerates wellbore cleanout operations, offering an effective alternative for sand management in mature oil fields.

References

Asfha, D. T., Latiff, A. H. A., Otchere, D. A., Tackie-Otoo, B. N., Babikir, I., Rafi, M., Riyadi, Z. A., Putra, A. D., & Adeniyi, B. A. (2024). Mechanisms of sand production, prediction a review and the potential for fiber optic technology and machine learning in monitoring. Journal of Petroleum Exploration and Production Technology, 14(10), 2577–2616. https://doi.org/10.1007/s13202-024-01860-1

Azevedo, R., & Fonseca, M. (2014). Empirical and statistical analysis of sand cleanout operations using coiled tubing in high-angle wells. SPE Deepwater Technical Conference and Exhibition. SPE-168123-MS. https://doi.org/10.2118/168123-MS

Bideci, A. A. (2020). International Research in Engineering Sciences. Platanus. https://doi.org/10.5281/zenodo.7744436

Khan, J. A., Irawan, S., Padmanabhan, E., Al-Kayiem, H. H., & Rai, S. (2020). Optimization of coiled tubing nozzle for sand removal from wellbore. Journal of Petroleum Exploration and Production Technology, 10(1), 53–66. https://doi.org/10.1007/s13202-019-0714-x

Khatibi, S., & Aghajanpour, A. (2020). Machine learning: A useful tool in geomechanical studies, a case study from an offshore gas field. Energies, 13(14), 3528. https://doi.org/10.3390/en13143528

Li, J., & Walker, S. (2001). Sensitivity analysis of hole cleaning in horizontal and deviated wells. SPE Middle East Oil Show. SPE-67202-MS. https://doi.org/10.2118/67202-MS

Li, J., Airhtar, M., & Walker, S. (2002). Solid cleanout in horizontal wells: A state-of-the-art review. SPE Western Regional/AAPG Pacific Section Joint Meeting. SPE-74470-MS. https://doi.org/10.2118/74470-MS

Li, J., Misselbrook, J., & Sach, M. (2010). Sand cleanouts with coiled tubing: Choice of process, tools and fluids. Journal of Canadian Petroleum Technology, 49(8), 69–82. https://doi.org/10.2118/113267-PA

Menter, F. R. (1994). Two-equation eddy-viscosity turbulence models for engineering applications. AIAA Journal, 32(8), 1598–1605. https://doi.org/10.2514/3.12149

Momber, A. W. (2003). An SEM-study of high-speed hydrodynamic erosion of cementitious composites. Composites Part B: Engineering, 34(2), 135–142. https://doi.org/10.1016/S1359-8368(02)00082-3.

Pradipta, A., Alvin D. W., Janico. S. M, and Muhammad. I. P. (2020). Thru Tubing Fracturing Experience in Tight Sand Reservoir. Offshore North West Java., Scientific Contributions Oil and Gas, 42(1), 41-49. https://doi.org/10.29017/SCOG.43.1.393

Razmjoo, A., Ehyaei, M. A., Ahmadi, A., Pazhoohesh, M., Marzband, M., Mansouri Khosravi, M., Shahhoseini, A., & Davarpanah, A. (2024). Implementation of energy sustainability using hybrid power systems, a case study. Energy Sources, Part A: Recovery, Utilization and Environmental Effects, 46(1), 2525–2538. https://doi.org/10.1080/15567036.2019.1687623

Research on hydraulic parameters and field tests of horizontal wells sand-flushing with rotating jets. (2013). Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 35(16), 1566–1573. https://doi.org/10.1080/15567036.2010.527912

Rolon, L., Waltrich, P. J., & Miska, S. (2009). Development of empirical models for sand cleanout in complex well geometries. SPE/ICoTA Coiled Tubing and Well Intervention Conference and Exhibition. SPE-121817-MS. https://doi.org/10.2118/121817-MS

Shabdirova, A., Kozhagulova, A., Samenov, Y., Minh, N., & Zhao, Y. (2024). Sand production prediction with machine learning using input variables from geological and operational conditions in the Karazhanbas oilfield, Kazakhstan. Natural Resources Research, 33(6), 2789–2805. https://doi.org/10.1007/s11053-024-10389-3

Shabdirova, A., Minh, N. H., & Zhao, Y. (2019). A sand production prediction model for weak sandstone reservoir in Kazakhstan. Journal of Rock Mechanics and Geotechnical Engineering, 11(4), 760–769. https://doi.org/10.1016/j.jrmge.2018.12.015

Singh, S., Gupta, V., & Sankar, M. R. (2020). Abrasive water jet machining. In Abrasive Water Jet Machining (pp. 71–96). Springer. https://doi.org/10.1007/978-3-030-43312-3_4.

Tamburrino, A., & Niño, Y. (2025). The Universal Presence of the Reynolds Number. Fluids, 10(5), 117. https://doi.org/10.3390/fluids10050117

Walton, I. C. (1995). Computer simulator of coiled tubing wellbore cleanouts in deviated wells recommends optimum pump rate and fluid viscosity. SPE Production Operations Symposium. SPE-29491-MS. https://doi.org/10.2118/29491-MS

Zhu, X.-H., Li, J.-N., & Tong, H. (2013). Mechanism analysis and process optimization of sand and plug removal with rotating jet in horizontal well. Journal of Central South University, 20(6), 1631–1637. https://doi.org/10.1007/s11771-013-1656-y