Drilling of the First Horizontal Well in Western Turkmenistan
Abstract - 0
PDF

Keywords

Well design
Horizontal wells
Economic analysis
Drilling technology

Abstract

Currently, the study of early horizontal drilling operations in Western Turkmenistan is of renewed interest, as it represents one of the first technological milestones in the region’s petroleum engineering history. The development and analysis of horizontal well drilling techniques in the early 1990s provided valuable insights into the practical implementation of new directional drilling technologies under complex geological and pressure conditions.

This study presents a detailed technical and historical analysis of the first horizontal wells drilled in the Koturdepe field between 1990 and 1992. The paper examines the well design, drilling assemblies, drilling fluids, and directional control systems used, and evaluates their technical performance and economic impact. Unlike a purely historical report, this work emphasizes the scientific and engineering lessons learned from these early operations and discusses their relevance to modern drilling practices in Turkmenistan. The research also includes an economic comparison between horizontal and vertical wells, demonstrating how the initial cost premium of horizontal drilling was offset by significantly higher productivity.

The results are of practical importance for optimizing drilling technologies in fields with abnormally high reservoir pressures and for applying these lessons to modern digital drilling systems.

https://doi.org/10.15377/2409-787X.2025.12.6
PDF

References

Deryaev AR. Engineering aspects and improvement of well drilling technologies at the Altyguyi field. Mach Energy. 2024; 2(15): 9-20. https://doi.org/10.31548/machinery/2.2024.09

Deryaev AR. Development of effective production strategies for gas condensate fields based on analysis of operating conditions. Int J Eng Trends Technol. 2024; 72(12): 247-84. https://doi.org/10.14445/22315381/IJETT-V72I12P122

Deryaev AR. Drilling of directional wells in the fields of Western Turkmenistan. Grassroots J Nat Resour. 2024; 7(2): 347-69. https://doi.org/10.33002/nr2581.6853.070218

Deryaev AR. Features of the construction of directed deep wells in Turkmenistan. Ital J Eng Geol Environ. 2024; (1): O-03. http://doi.org/10.4808/IJEGE.2024-01.O-03

Leusheva E, Alikhanov N, Morenov V. Barite-free muds for drilling in the formations with abnormally high pressure. Fluids. 2022; 7(8): 268. https://doi.org/10.3390/fluids7080268

Peng C, Pang J, Fu J, Cao Q, Zhang J, Li Q, et al. Predicting rate of penetration in ultra-deep wells based on deep learning method. Arab J Sci Eng. 2023; 1-16. https://doi.org/10.1007/s13369-023-08043-w

Sircar A, Yadav K, Rayavarapu K, Bist N, Oza H. Application of machine learning and artificial intelligence in oil and gas industry. Pet Res. 2021; 6(4): 379-91. https://doi.org/10.1016/j.ptlrs.2021.05.009

Berova IG, Filippov AA. Evaluation of the effectiveness of modern innovative drilling technologies in the oil and gas industry. Innov Oil Gas Ind. 2021; 2(3). https://doi.org/10.5281/zenodo.5804425

Wang H, Huang H, Bi W, Ji G, Zhou B, Zhuo L. Deep and ultra-deep oil and gas well drilling technologies: progress and prospect. Nat Gas Ind B. 2022; 9(2): 141-57. https://doi.org/10.1016/j.ngib.2021.08.019

Kwon H, Mah JS. Diversification and industrialization in the economic development of Turkmenistan. Perspect Glob Dev Technol. 2021; 20(4): 358-79. https://doi.org/10.1163/15691497-12341506

Tao S, Pan Z, Tang S, Chen S. Current status and geological conditions for the applicability of CBM drilling technologies in China: a review. Int J Coal Geol. 2019; 202: 95-108. https://doi.org/10.1016/j.coal.2019.01.001

Aghahosseini A, Breyer C. From hot rock to useful energy: a global estimate of enhanced geothermal systems potential. Appl Energy. 2020; 279: 115769. https://doi.org/10.1016/j.apenergy.2020.115769

Patel H, Salehi S, Ahmed R, Teodoriu C. Review of elastomer seal assemblies in oil & gas wells: performance evaluation, failure mechanisms, and gaps in industry standards. J Pet Sci Eng. 2019; 179: 1046-62. https://doi.org/10.1016/j.petrol.2019.04.037

Xiao D, Hu Y, Wang Y, Deng H, Zhang J, Tang B, et al. Wellbore cooling and heat energy utilization method for deep shale gas horizontal well drilling. Appl Therm Eng. 2022; 213: 118684. https://doi.org/10.1016/j.applthermaleng.2022.118684

Khuzin RR, Mukhametshin VS, Salikhov DA, Andreev VE, Pepelyaev DV, Stefanovich YN. Improving the efficiency of horizontal wells at multilayer facilities. IOP Conf Ser Mater Sci Eng. 2021; 1064: 012066. https://doi.org/10.1088/1757-899X/1064/1/012066

Alsaihati A, Elkatatny S, Mahmoud AA, Abdulraheem A. Use of machine learning and data analytics to detect downhole abnormalities while drilling horizontal wells: case study. J Energy Resour Technol. 2021; 143(4): 043201. https://doi.org/10.1115/1.4049383

Liu T, Leusheva E, Morenov V, Li L, Jiang G, Fang C, et al. Influence of polymer reagents in drilling fluids on efficiency of deviated and horizontal wells drilling. Energies. 2020; 13(18): 4704. https://doi.org/10.3390/en13184704

Zongyu L, Fei Z, Ming L, Lingzhan Z, Jiangang S, Lubin Z. Key technologies for drilling horizontal wells in glutenite tight oil reservoirs in Mahu Oilfield, Xinjiang. Pet Drill Technol. 2019; 47(2): 9-14. http://doi.org/10.11911/syztjs.2019029

Yakupov RF, Sh MV, Khakimzyanov IN, Trofimov VE. Optimization of reserve production from water-oil zones of Shkapovsky oil field by means of horizontal wells. Georesursy. 2019; 21(3): 55-61. https://doi.org/10.18599/grs.2019.3.55-61

Mahmoud H, Hamza A, Nasser MS, Hussein IA, Ahmed R, Karami H. Hole cleaning and drilling fluid sweeps in horizontal and deviated wells: comprehensive review. J Pet Sci Eng. 2020; 186: 106748. https://doi.org/10.1016/j.petrol.2019.106748

Zhang YZ, Ju B, Zhang ML, Guo P. Development strategies of a gas condensate reservoir with a large gas cap and strong bottom water, and natural barriers. Pet Sci. 2025; e-pub ahead. https://doi.org/10.1016/j.petsci.2025.06.016

Mohamadi-Baghmolaei M, Zhang Z, et al. Advances in gas injection for gas condensate reservoirs. Energy Rep. 2025; 143: 205711. https://doi.org/10.1016/j.jgsce.2025.205711

Zhu K, Gao L, Sun F. Numerical simulation study on optimization of development parameters of condensate gas reservoir. Processes. 2024; 12(10): 2069. https://doi.org/10.3390/pr12102069

Latrach A, Malki ML, Morales M, Mehana M, Rabiei M. A critical review of physics-informed machine learning applications in subsurface energy systems. Geoenerg Sci Eng. 2024; 239: 212938. https://doi.org/10.1016/j.geoen.2024.212938

Zhong R, Salehi C, Jonson R. Machine learning for drilling applications: a review. J Pet Sci Eng. 2022; 108: 104807. https://doi.org/10.1016/j.jngse.2022.104807

Brantson ET, Adu-Awuku J, Asase W, Akoto Obeng SD, Kwakye-Tannor MB, Nuamah JA, et al. Optimization of well trajectory with machine learning algorithms for geosteering directional drilling. J Geophys Eng. 2025; 22(5): 1245-65. https://doi.org/10.1093/jge/gxaf055

Póvoas MdS, Moreira JF, Neto SVM, Carvalho CAS, Cezario BS, Guedes ALA, et al. AI in the oil and gas industry: applications, challenges, and future directions. Appl Sci. 2025; 15(14): 7918. https://doi.org/10.3390/app15147918

Nour M, Eksayed SK, Mahmoud O. A supervised machine learning model to select cost-optimal directional tool. Sci Rep. 2024; 14: 76910. https://doi.org/10.1038/s41598-024-76910-z

Reis P, Carvalho M. Pore-scale analysis of gas injection in condensate reservoirs. 2022; 212: 110189. https://doi.org/10.1016/j.petrol.2022.110189

Li N, Li H, Tan X, Zhang L, Liu Y. Effect of retrograde condensation and stress sensitivity on properties of condensate gas reservoirs. Front Energy Res. 2023; 10: 1078755. https://doi.org/10.3389/fenrg.2022.1078755

Zhang A, Fan Z, Zhao L, He J, et al. Effect of water vapor on phase behaviors during depletion and CO₂ injection in gas condensate reservoir. J Pet Sci Technol. 2024; 42: 1018-30. https://doi.org/10.1080/10916466.2022.2149794

Tang Y, Long K, Wang J, Xu H, Wang Y, He Y, et al. Change of phase state during multicycle injection and production in condensate reservoirs. Pet Explor Dev. 2021; 48(2): 395-406. https://doi.org/10.1016/S1876-3804(21)60031-9

ASME. Transforming oil well drilling: prediction of real-time rate of penetration with novel machine learning approach in varied lithological formations. Energy Resour Technol. 2025; 1(1): 1-27. https://doi.org/10.1115/1.4066015

Jatmiko AP, Setiono HP, Athallah F, Fajarrenaningtyas U, Sayendra FH, Rinanda W, et al. Integrated real-time well engineering: the role of AI/ML-based well surveillance to achieve Indonesia's 2032 oil and gas production and drilling targets. In: SPE Europe Energy Conference. 2025; Paper 225600-MS. https://doi.org/10.2118/225600-MS

Davoodi Sh, Burnaev E, Mohammadi AH. Machine-learning modeling of water, oil, and solids in oil-based muds: an alternative approach to retort test. Colloids Surf A Physicochem Eng Asp. 2026; 728(pt 2): 138500. https://doi.org/10.1016/j.colsurfa.2025.138500

Elosionu B, Onyyinyechi UB, Chiamaka GG. Recent application of machine learning algorithms in petroleum geology: brief review. Int J Res Sci Innov. 2023; 10(9): 91-9. https://doi.org/10.51244/IJRSI.2023.10910

Machado Pacheco B, Seman LO, Camponogara E. Deep-learning-based early fixing for gas-lifted oil production optimization: supervised approaches. arXiv Preprint. 2023; 2309.00197. http://doi.org/10.48550/arXiv.2309.00197

Alyaev S, Fossum K, Djecta H, Tveranger J, Elsheikh AH. DISTINGUISH workflow: a new paradigm of dynamic well placement using generative ML. arXiv Preprint. 2025; 2503.08509. https://doi.org/10.3997/2214-4609.202437018

Li JX, Zhang TC, Zhu Y, Chen ZW. Artificial general intelligence (AGI) for the oil and gas industry: review. arXiv Preprint. 2024; 2406.00594. https://doi.org/10.1016/j.jgsce.2024.205469

Mitacc Meza EB, Borges de Souza DG, Copetti A, Barbosa Sobral AP, Silva GV, Tammela L, et al. Tools, technologies and frameworks for digital twins in the oil and gas industry: an in-depth analysis. Sensors. 2024; 24: 6457. https://doi.org/10.3390/s24196457

Ajentumobi MO, Murphy OO, Emmanuel OA. Automation and digitalization in drilling operations. Int J Sci Res Technol. 2025; 8(9): 104-28. https://doi.org/10.70382/tijsrat.v08i9.048

Xiao C, Wang GC, Zhang Y, Deng Y. Machine-learning-based well production prediction under geological and hydraulic fracture parameters uncertainty for unconventional shale gas reservoirs. J Nat Gas Sci Eng. 2022; 106: 104762. https://doi.org/10.1016/j.jngse.2022.104762

Kalinin O, Elfimov M, Baybolov T. Exploration drilling management system based on digital twins technology. In: Proceedings of the SPE Annual Technical Conference and Exhibition, Dubai, United Arab Emirates, 21-23 September 2021. Kuala Lumpur: SPE; 2021. p. D031S055R009. https://doi.org/10.2118/205994-MS

Mayani MG, Baybolov T, Rommetveit R, Odegaard SI, Koryabkin V, Lakhtionov S. Optimizing drilling wells and increasing the operation efficiency using digital twin technology. In: Proceedings of the IADC/SPE International Drilling Conference and Exhibition, Galveston, TX, USA, 3-5 March 2020. Richardson: OnePetro; 2020. https://doi.org/10.2118/199566-MS

Li G, Song X, Tian S, Zhu Z. Intelligent drilling and completion: a review. Eng. 2022;18:33-48. https://doi.org/10.1016/j.eng.2022.07.014

Liu M, Fang S, Dong H, Xu C. Review of digital twin about concepts, technologies, and industrial applications. J Manuf Syst. 2021; 58: 346-61. https://doi.org/10.1016/j.jmsy.2020.06.017

Sharma A, Kosasih E, Zhang J, Brintrup A, Calinescu A. Digital twins: state of the art theory and practice, challenges, and open research questions. J Ind Inf Integr. 2022; 30: 100383. https://doi.org/10.1016/j.jii.2022.100383

Al-Rbeawi S. A review of modern approaches of digitalization in oil and gas industry. Upstream Oil Gas Technol. 2023; 11: 100098. https://doi.org/10.1016/j.upstre.2023.100098

Iskandar FF, Abiddin MSZ, Nazzeri N, Aziz AA, Atemin A. Integrated real-time operation centre: a complete solution towards effective and efficient drilling operation. In: Proceedings of the Offshore Technology Conference Asia, Kuala Lumpur, Malaysia, 20-23 March 2018. OTC; 2018. p. D021S008R003. https://doi.org/10.4043/28598-MS

Wang H, Huang H, Bi W, Ji G, Zhou B, Zhuo L. Deep and ultra-deep oil and gas well drilling technologies: progress and prospect. Nat Gas Ind B. 2022; 9(2): 141-57. https://doi.org/10.1016/j.ngib.2021.08.019

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Copyright (c) 2025 Annaguly Deryaev

Downloads

Download data is not yet available.