2-19-8

УДК 550.834.048.05

https://doi.org/10.21440/2307-2091-2019-2-63-71

The relevance of the work. This paper is devoted to topical issues of identifying promising intervals favorable for petrophysical properties for hydrocarbon accumulations using 3D seismic data. The purpose of these studies is to establish the effective attributes of the seismic-wave motion to determine the petrophysical properties of Maikop sediments aimed at restoring oil and gas production in the Gazanbulak area. The subjects of research are core materials, well geophysical survey data and seismic attributes, as well as relationships between core data and mathematical transformations of petrophysical properties data. The PP curves were transformed into the porosity values of the sediments of the target interval, and a regression equation was obtained for the research area, which establishes a relationship between the porosity coefficient and �PP.
The object of research is the Gazanbulak field. The paper gives a brief geological and geophysical characteristic, stratigraphic and lithological description of the rocks composing the section of this field. Despite the fact that this field has been repeatedly studied by various geological and geophysical methods, many features of its structure are not fully clarified; in 2014, 3D seismic surveys were carried out. Result of the studies. The main results of studies on the petrophysical properties of the Gazanbulak horizon II of the Maikop suite using 3D seismic and GIS seismic data are presented. The cubes, reservoir maps, and porosity maps were constructed according to which it was found that the percentage of sands is high and reaches 62% in the target interval; the average values of apparent resistivity vary from 3.0–8.4 ohm m. It is shown that the calculated �PP values by area increase in the southern and eastern parts of the Ziyadkhan area, and the predicted porosity data are observed in the central part of the Ziyadkhan area, in the northern and central parts of the Gazanbulak area. The values of the porosity coefficient calculated for the research interval are approximately 10–22%.
The results of the forecast of porosity using the seismic attribute RMS Amplitude are given. Comparison of maps constructed by different methods (GIS and RMS amplitude analysis) shows that the data obtained by different computation methods are similar and coincide quite well and can be used in determining the location of the next production well.
Conclusion. RMS Amplitude can be successfully used to determine the petrophysical properties of individual sediments of deposits with similar seismic and geological conditions.

Keywords: Upper Cretaceous, Paleocene, Eocene, Maikopskaya suite, petrophysical studies, apparent resistivity (AR), production potential of the well (PP), cubes and porosity maps, seismic attributes. Th is work was carried out with the fi nancial support of the Foundation for the Development of Science under the President of the Republic of Azerbaijan – Qrant No. EİF-KETL-2-2015-1 (25) -56/33/2.

REFERENCES

  1. Alizade A. A., Akhmedov G. A., Akhmedov A. M. et al. 1966, Geologiya neftyanykh i gazovykh mestorozhdeniy Azerbaydzhana [Geology of oil and gas fi elds in Azerbaijan]. Moscow, 384 p.
  2. Akhmedov T. R. 2016, About the geological effectiveness of seismic prospecting in the study of different types of non-anticlinal traps in Azerbaijan. Izvestya UGGU [News of the Ural State Mining University], issue 3 (43), pp. 41–45. (In Russ.)
  3. Urupov A. К. 2004, Osnovy trekhmernoy seysmorazvedki [The basics of three-dimensional seismic]. Moscow, 584 p.
  4. Balz O., Pivot F., Veeken P. 1999, Reservoir characterisation using neural networks controlled by petrophysical and seismic modelling. Extended Abstracts: 61th EAGE annual meeting. S015, pp. 1–4. https://doi.org/10.3997/2214-4609.201407673
  5. Loginov D. V., Lavrik S. A. 2010, Some methods for determining the informative set of seismic attributes for predicting reservoir properties. Neftegazovaya Geologiya. Teoriya I Praktika [Petroleum Geology – Theoretical and Applied Studies], vol. 5, no. 1. http://www.ngtp.ru/rub/3/3_2010.pdf
  6. Rakhmanov R. R. 2007, Zakonomernosti formirovaniya i razmeshcheniya zalezhey nefti i gaza v mezokaynozoyskikh otlozheniyakh YevlakhAgdzhabedinskogo progiba [Patterns of formation and placement of oil and gas deposits in the Meso-Cenozoic sediments of the YevlakhAgjabedinskiy downfold]. Baku, 191 p.
  7. Ampilov Yu. P. 2008, Ot seysmicheskoy interpretatsii k modelirovaniyu i otsenke mestorozhdeniy nefti i gaza [From seismic interpretation to modeling and evaluation of oil and gas fi elds]. Moscow, 429 p.
  8. Kirilov A. S., Zakrevsky K. Е. 2014, Praktikum po seysmicheskoy interpretatsii v PETREL [Practical course on seismic interpretation in PETREL]. Moscow, 288 p.
  9. Akhmedov T. R., Akhundlu A. A., Giyasov N. Sh. 2012, Some results of surface and borehole seismic exploration of the Govsaninskoe hydrocarbon fi eld. Karotazhnik [Well Logger], no. 6 (216), pp. 3–16. (In Russ.)
  10. 2002, Metodicheskiye ukazaniya po kompleksirovaniyu i etapnosti vypolneniya geofi zicheskikh, gidrodinamicheskikh i geokhimicheskikh issledovaniy neftyanykh i neftegazovykh mestorozhdeniy [Guidelines for the integration and staging of the implementation of geophysical, hydrodynamic and geochemical studies of oil and gas fi elds]: RD 153-39.0-109-01: approved By the Minenergo of Russia order, 05.02.2002 Entered 2002-03-01, no. 30. Moscow, 73 p.
  11. Marroquin I. D., Brault J., Hart B. S. 2009, A visual data-mining methodology for seismic facies analysis: Part 1. Testing and comparison with other unsupervised clustering methods. Geophysics, vol. 74, no. 1, pp. 1–11. http://dx.doi.org/10.1190/1.3046455
  12. Akhmedov T. R. 2017, Dynamic analysis of seismic data of 3D Govsan area in order to identify promising areas for oil and gas. Geoinformatika [Geoinformatics], no. 4, pp. 13–19. (In Russ.)
  13. Yusof M. A., Gbadamosi A., Junin R., Abbas A. 2018, Uncertainly analysis of hydrocarbon in place calculation using 3D seismic and well data during appraisal stage – Case study of Goldie Fild, offshore Sarawak. Journal of natural gas science and engineering, vol. 57, pp. 238–265. https://doi.org/10.1016/j.jngse.2018.06.038
  14. Fozao K. F., Fotso L., Djieto-Lordon A., Mbeleg M. 2018, Hydrocarbon inventory of the eastern part of the Rio Del Rey Basin using seismic attributes. Journal of petroleum exploration and production technology, vol. 8, issue 3, pp. 655–665.
  15. Ampilov Yu. P. 2005, Seysmicheskaya interpretatsiya: opyt i problemy [Seismic interpretation: experience and problems]. Moscow, 286 p.
  16. Latysheva M. G., Wendelstein B. Yu, Tuzov V. P. 1990, Obrabotka i interpretatsiya materialov geofizicheskikh issledovaniy skvazhin [Processing and interpretation of well log data]. Moscow, 305 p.
  17. Tyler M. N. 2013, Applications of 3D seismic attribute analysis workflows: a case study from NESS country KANSAS, USA, B.S APPL 3D SEISMIC ATTR. Manhattan, pp. 1–30.
  18. Chopra S., Marfut K. J. 2005, Seismic attributes – a historical perspective. Geophysics, vol. 70, issue 5, pp. 3–28. http://dx.doi.org/10.1190/1.2098670
  19. Hart B. S. 1999, Definition of subsurface stratigraphy, structure and rock properties from 3-D seismic data. Earth-science reviews, vol. 47, issue 3-4, pp. 189–218. https://doi.org/10.1016/S0012-8252(99)00029-X
  20. Neff D. B., Runnestrand S. A., Butler E. L. 2001, Multi-attribute seismic waveform classification. USA, Phillips Petroleum Company, USA Patent 6223126.

 

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