Determination of shaliness parameters of terrigenous rocks in cased boreholes and while drilling by radioactive logging combination
Abstract
Introduction. Shaliness is an important lithological and petrophysical characteristic of reservoirs and seals in section of oil-and-gas boreholes as well as near-surface rocks (grounds) as the basis of buildings and engineering structures. Granulometric shaliness, determined by the presence of pelitic particles, and mineral shaliness, which characterizes the content of clay minerals, are distinguished in terrigenous rocks. In the sections of oil-and-gas fields, granulometric shaliness is one of the criteria for identifying reservoirs and affects their reservoir properties. The physical properties of reservoirs, which are studied by borehole logging, depend on the content and type of clay minerals. Information about clay minerals is taken into account when drilling and stimulation of hydrocarbon production. Shaly grounds apply to the group of cohesive ones, which in construction most often serve as the foundations of structures. At that these grounds are classified as difficult engineering-geological conditions for construction, since clay minerals specifically affect their strength, stability, etc. In oil-and-gas and engineering-geological boreholes the empirical equations relating gamma-ray logging readings and granulometric shaliness are most often used for quantitative estimation. Herewith, it is traditionally thought that the clay minerals make up the bulk of the pelitic particles.
The paper is concerned with increasing the informativity of the borehole logging while investigating the shaliness of terrigenous oil-and-gas reservoirs and near-surface rocks based on a combination of gamma-ray logging, gamma-gamma density logging and neutron-neutron logging (GR+DL+NL).
The investigation methodology included: borehole geophysical measurements by tools created at the Institute of Geophysics of the National Academy of Sciences of Ukraine independently and in collaboration with partner organizations; interpretation and analysis of logging data; justification and development of approaches to increase the informativity of the GR+DL+NL combination; estimation of the effectiveness of author's developments using independent criterions.
As a result of the investigation, on the basis of the abovementioned logging combination, the set of determined parameters is increased as compared with the traditional practice; number of new methods is developed for determining the parameters of shaliness, among them the content of clay minerals, their density and hydrogen index. The use of these parameters, in turn, improves the accuracy of porosity determination and other reservoir properties from logging data. Method for estimating the type of clay mineral according to the GR+DL+NL data is proposed. The method is an available alternative to geochemical core studies and to more expensive and difficult logging methods.
The novelty of the developments is confirmed by patents, and their effectiveness is confirmed by the results of borehole tests and comparison with independent determinations of parameters (laboratory core examinations, control logging data).
Practical significance. The proposed approaches are an important component of technologies for investigating oil-and-gas reservoirs and near-surface rocks, which are being developed at the Institute of Geophysics of the National Academy of Sciences of Ukraine.
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References
Bezrodna, I. M., & Gozhyk, A. P. (2018). Petrophysics. Kyiv university. [in Ukrainian]
Dobrynin, V. M., Vendelshtein, B. Iu., & Kozhevnikov D. A. (1991). Petrophysics. M., Nedra.
Shutenko, L. N., Rud, A. H., Kychaeva, O. V., Samorodov, A. V., & Havryliuk, O. V. (2015). Ground mechanics, bases and foundations. KhNUGH im. Beketova.
Alexander, T., Baihly, J., Boyer, C., Clark, B., Waters, G., Jochen, V., Calvez, J., Lewis, R., Miller, C. K., Thaeler, J., & Toelle, B. (2011). Shale Gas Revolution. Oilfield Review, 23(3), 40–55. https://www.academia.edu/19167922/Shale_Gas_Revolution
Kuznetsov, O. N., & Poliachenko, A. L. (Eds.) (1990). Borehole nuclear geophysics. Geophysicist’s handbook (2nd ed.). M., Nedra.
Potiatynnyk, T. V. (2018). Estimation of the carbonate-shaly cement influence on the permeability of reservoirs by geophysical data. Scientific bulletin of Ivano-Frankivsk National Technical University of Oil and Gas, 1(44), 48–56. https://doi.org/10.31471/1993-9965-2018-1(44)-48-56 [in Ukrainian]
Bhuyan, K., & Passey, Q. (1994). Clay estimation from GR and Neutron-Density porosity logs. paper D, SPWLA 35th Annual Logging Symposium, June 19-22, 1994.
Ellis, D. V., & Singer, J. M. (2008). Well logging for earth scientists. (2nd ed.). Springer.
Kurniawan, B. (2005). Shaly sand interpretation using CEC-dependent petrophysical parameters [Doctoral disser-tation, Louisiana State University]. https://digitalcommons.lsu.edu/cgi/ viewcontent.cgi?referer=&httpsredir=1&article=3383&context=gradschool_dissertations
Abdideh, M. (2015). Study of dependence between clay mineral distribution and shale volume in reservoir rocks using geostatistical and petrophysical methods. Geodesy and Cartography, 41(2), 92–100. https://doi.org/10.3846/20296991.2015.1051333
Ahmad, K., Kristaly, F., Turzo, Z., & Docs, R. (2018). Effects of clay mineral and physico-chemical variables on sandstone rock permeability. Journal of Oil, Gas and Petrochemical Sciences, 1(1), 18-26. https://doi.org/10.30881/jogps.00006
Zhu, L., Sun, J., Zhou, X., Li, Q., Fan, Q., Wu, S., & Wu, S. (2022). Well logging evaluation of fine-grained hydrate-bearing sediment reservoirs: Considering the effect of clay content. Petroleum Science, Pre-proof. https://doi.org/10.1016/j.petsci.2022.09.018
Elhassan, A. M., Mnzool, M., Smaoui, H., Jendoubi, A., Elnaim, B., & Alotaibi, M. (2023). Effect of clay mineral content on soil strength parameters. Alexandria Engineering Journal, 63(1), 475-485. https://doi.org/10.1016/j.aej.2022.08.012
Ferronskiy, V. I. (2015). Nuclear geophysics. Applications in hydrology, hydrogeology, engineering geology, agri-culture and environmental science. Springer.
Diaz-Curiel, J., Miguel, M. J., Biosca, B., & Arevalo-Lomas, L. (2021). Gamma ray log to estimate clay content in the layers of water boreholes. Journal of Applied Geophysics, 195, 1–13. https://doi.org/10.1016/j.jappgeo.2021.104481
Martins, J. L., & Castro, T. M. (2018). Empirical and petrophysical models for shaliness estimation in clastic sedi-mentary rocks. Revista Brasileira de Geofisica, 36(2), 163–176. http://doi: 10.22564/rbgf.v36i2.919
Kamel, M. H., & Mabrouk, W. M. (2003). Estimation of shale volume using a combination of the three porosity logs. Journal of Petroleum Science and Engineering, 40, 145–157. https://doi.org/10.1016/S0920-4105(03)00120-7
Ghassem A. M., & Roozmeh A. (2017). Determination of shale types using well logs. International Journal of Pet-rochemical Science & Engineering, 2(5), 274–280. https://doi.org/10.15406/ipcse.2017.02.00051
Almeida, T. L. P, Passos, B. A. F., Costa, J. L. S., & Andrade, A. J. N. (2021). Identifying clay mineral using angular competitive neural network: A machine learning application for porosity estimative. Journal of Petroleum Science and Engineering, 200. https://doi.org/10.1016/j.petrol.2020.108303
Galford, J., Quirein, J., Shannon, S., Truax, J., & Witkowsky, J. (2009, October 04–07). Test Results of a New Neu-tron Induced Gamma Ray Spectroscopy Geochemical Logging Tool [Conference presentation]. 2009 SPE Annual Technical Conference and Exhibition, New Orleans, Louisiana, USA. https://doi.org/10.2118/123992-MS
Klaja, J, & Dudek, L. (2016). Geological interpretation of spectral gamma ray (SGR) logging in selected bore-holes. NAFTA-GAZ, 1, 3–14. https://doi.org/10.18668/NG2016.01.01
Schlumberger. (2005). Log interpretation charts. Schlumberger, Houston, TX. https://www.spec2000.net/freepubs/SLB1997R.pdf
Bondarenko, M. S., & Kulyk, V. V. (2015). Method for determining density parameters of sandshale rocks by the radioactivity logging complex. Ukrainian Patent for useful model № 95931. The State Enterprise "Ukrainian Intel-lectual Property Institute". [in Ukrainian]
Al-Obaidi, S. H. (2017). Calculation improvement of the clay content in the hydrocarbon formation rocks. Oil & Gas Research, 3(1), 1–2. https://doi.org/10.4172/2472-0518.1000130
Diaz-Curiel, J., Miguel, M. J., Biosca, B., & Medina, R. (2019). Environmental correction of gamma ray logs by geometrical / empirical factors. Journal of Petroleum Science and Engineering, 173, 462–468. https://doi.org/10.1016/j.petrol.2018.10.056
Wang, H., Liu, T., Tang, T., & Shi, Y. (2017). A unified model to evaluate shaliness in compacted and soft formations using downhole GR log. Journal of Petroleum Science and Engineering, 156, 877–883. https://doi.org/10.1016/j.petrol.2017.06.070
Larionov, V. V. (1969). Borehole radiometry. M., Nedra.
Fedoryshyn, D. D., Trubenko, O. M., Fedoryshyn, S. D., Ftemov, Ya. M., & Koval Ya. M. (2016). Prospects of nuclear-physical methods for the distinction of gas-saturated reservoir rocks in complicated Neogene sediments. Geody-namics, 2(21), 134–143.
Bondarenko, M. S., & Kulyk, V. V. (2019). The method of borehole determination of mass shale content of terri-genous rocks. Ukrainian Patent for useful model № 131232. The State Enterprise "Ukrainian Intellectual Property Institute". [in Ukrainian]
Kulyk, V. V., Bondarenko, M. S., & Deineko, S. I. (2015). Method for determining shaliness parameters of rocks by the radioactive logging complex. Ukrainian Patent for invention № 109230. The State Enterprise "Ukrainian In-tellectual Property Institute". [in Ukrainian]
Zhou, X., Liu, D., Bu, H., Deng, L., Liu, H., Yuan, P., Du, P., & Song, H. (2018). XRD-based quantitative analysis of clay minerals using reference intensity ratios, mineral intensity factors, Rietveld, and full pattern summation methods: A critical review. Solid Earth Sciences, 3, 16–29. https://doi.org/10.1016/j.sesci.2017.12.002
Kulyk, V. V., Bondarenko, M. S., & Kamilova, O. V. (2013). Method for determining mineral density of rock skeleton. Ukrainian Patent for invention № 103841. The State Enterprise "Ukrainian Intellectual Property Institute". [in Ukrainian]
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