Scientific and technical journal

«Oilfield engineering»

ISSN 0207-2351

Oilfield engineering
Formation of the state of wells near-bottom zones operating terrigenous reservoirs

UDC: 622.276.031.011.433:519.2
DOI: -

Authors:

SOROMOTIN ANDREY V.1

1 Perm National Research Polytechnic University, Perm, Russia

Keywords: permeability of the near-wellbottom zone, skin-factor, sandstone reservoirs, machine learning

Annotation:

The article presents the results of studying the influence of wells geological and operational parameters on the permeability of the near-wellbottom zone of the reservoir (near-wellbottom zone permeability) and skin factor. In this study a series of multidimensional static models were built, allowing for highly reliable prediction of a near-wellbottom zone permeability in conditions of the investigated terrigenous reservoir under study. The specific productivity coefficient and water cut have a significant impact on the permeability of the near-wellbore zone. A hypothesis is put forward that the high significance of the water cut parameter may be caused by the individual interaction between the rock of the investigated objects and the displacing agent, represented by fresh water (clay swelling). It has been revealed that there is no dependence between the investigated parameters and the model skin factor. Additional parameters (permeability of the reservoir remote zone, well radius, external reservoir boundary radius, effective well radius, wells’ perfection degree) and the SHAP library (gradient boosting) were introduced to determine the contribution of each parameter to the final prediction of the desired value – the skin factor. Thus, the most significant parameters influencing the formation of the permeability of the near-wellbottom zone and the skin factor have been identified, and the possibility of their prediction has been assessed.

Bibliography:

1. New insights into optimizing perforation clean up and enhancing productivity with zinc-case shaped charges / R.P. Satti, R. White, D. Ochsner [et al.] // SPE International Conference and Exhibition on Formation Damage Control, Lafayette, Louisiana, USA, 2016. – URL: https://doi.org/10.2118/178935-ms

2. Zakharov L.A., Martyushev D.A., Ponomareva I.N. Prognozirovanie dinamicheskogo plastovogo davleniya metodami iskusstvennogo intellekta // Zapiski Gornogo instituta. – 2022. – T. 253. – S. 23–32. – URL: https://doi.org/10.31897/PMI.2022.11

3. Research on the damage of porosity and permeability due to perforation on sandstone in the compaction zone / S. Xue, X. Zhu, L. Zhang [et al.] // Computers, Materials & Continua. – 2016. – Vol. 51, № 1. – P. 21–42. – URL: https://doi.org/10.3970/cmc.2016.051.021

4. Yuan B., Wood D.A. A comprehensive review of formation damage during enhanced oil recovery // J. of Petroleum Science and Engineering. – 2018. – Vol. 167. – P. 287–299. – URL: https://doi.org/10.1016/j.petrol.2018.04.018

5. Wood B.D., He X., Apte S.V. Modeling turbulent flows in porous media // Annual Review of Fluid Mechanics. – 2020. – Vol. 52(1). – P. 171–203. – URL: https://doi.org/10.1146/annurev-fluid-010719-060317

6. Dong W., Wang X., Wang J. A new skin factor model for partially penetrated directionally drilled wells in anisotropic reservoirs // J. of Petroleum Science and Engineering. – 2018. – Vol. 161. – P. 334–348. – URL: https://doi.org/10.1016/j.petrol.2017.11.062

7. Quantifying the partial penetration skin factor for evaluating the completion efficiency of vertical oil wells / E. Abobaker, A. Elsanoose, F. Khan [et al.] // J. of Petroleum Exploration and Production Technology. – 2021. – Vol. 11. – P. 3031–3043. – URL: https://doi.org/10.1007/s13202-021-01229-8

8. Comparison of Crushed-Zone Skin Factor for Cased and Perforated Wells Calculated with and without including a Tip-Crushed Zone Effect / E. Abobaker, A. Elsanoose, F. Khan [et al.] // Geofluids. – 2021. – Vol. 2021. – UR: https://doi.org/10.1155/2021/3689964

9. Vosproizvedenie plastovogo davleniya metodami mashinnogo obucheniya i issledovanie ego vliyaniya na protsess obrazovaniya treshchin pri gidravlicheskom razryve plasta / E.V. Filippov, L.A. Zakharov, D.A. Martyushev, I.N. Ponomareva // Zapiski Gornogo instituta. – 2022. – T. 258. – S. 924–932. – URL: https://doi.org/10.31897/PMI.2022.103

10. Galkin V.I., Ponomareva I.N., Martyushev D.A. Prognoz plastovogo davleniya i issledovanie ego povedeniya pri razrabotke neftyanykh mestorozhdeniy na osnove postroeniya mnogourovnevykh mnogomernykh veroyatnostno-statisticheskikh modeley// Georesursy. – 2021. – T. 23, № 3. – S. 73–82. – URL: https://doi.org/10.18599/grs.2021.3.10

11. Osobennosti formirovaniya prizaboynykh zon produktivnykh plastov na mestorozhdeniyakh s vysokoy gazonasyshchennost’yu plastovoy nefti / V.I. Galkin, D.A. Martyushev, I.N. Ponomareva, I.A. Chernykh // Zapiski Gornogo instituta. – 2021. – T. 249. – S. 386–392. – URL: https://doi.org/10.31897/PMI.2021.3.7

12. Primenenie mashinnogo obucheniya dlya prognozirovaniya plastovogo davleniya pri razrabotke neftyanykh mestorozhdeniy / D.A. Martyushev, I.N. Ponomareva, L.A. Zakharov, T.A. Shadrov // Izv. Tomskogo politekhnicheskogo un-ta. Inzhiniring georesursov. – 2021. – T. 332, № 10. – S. 140–149. – URL: https://doi.org/10.18799/24131830/2021/10/3401

13. Ponomareva I.N., Martyushev D.A., Galkin V.I. Operational method for determining bottom hole pressure in mechanized oil producing wells, based on the application of multivariate regression analysis // Petroleum Research. – 2021. – Vol. 6, Issue. 4. – P. 351–360. – URL: https://doi.org/10.1016/j.ptlrs.2021.05.010

14. Kantaatmadja B.P., Jiang L., Ralphie B. Hydrocarbon identification and evaluation in a bioturbated reservoir with new-generation pulsed neutron technology // SPE/IATMI Asia Pacific Oil & Gas Conference and Exhibition, 2019. – URL: https://doi.org/10.2118/196364-MS

15. Alghazal M., Alshakhs M., Bouaouaja M. Technology integration to assessend-point oil saturation of the relative permeability curves // International Petroleum Technology Conference. – 2020. – URL: https://doi.org/10.2523/IPTC-19614-MS

16. Ponomareva I.N., Martyushev D.A., Akhmetova M.I. Otsenka optimal’noy prodolzhitel’nosti provedeniya gidrodinamicheskikh issledovaniy nizkoproduktivnykh skvazhin na primere ozernogo mestorozhdeniya // Neft. khoz-vo. – 2016. – № 1. – S. 60–63.

17. Lundberg S.M., Lee S.I. A unified approach to interpreting model predictions // Proc. Of the Conf. on Advances in Neural Information Processing Systems, USA, 2017. – P. 4768–4774. – URL: https://doi.org/10.48550/arXiv.1705.07874