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Geoinformatika 2019; 3(71) : 52-61

УДК 550.832+550.8.05

MODELING THE EFFECT OF THE STRUCTURE OF THE VOID SPACE ON THE ELASTIC PROPERTIES OF COMPLEX RESERVOIRS

I.I. Virshylo, V. Khalimendik

Kyiv national University of Taras Shevchenko Institute of Geology, 90 Vasylkivska str., Kyiv, 03022, Ukraine, e-mail: ivirshylo@gmail.com

Purpose. The gradual exhaustion of traditional easily recoverable hydrocarbon deposits in the world and on the territory of Ukraine, makes the problem of predicting the filtration-capacitive properties of reservoir rocks with heterogeneous structure of voids, both in size and shape and orientation, more important. Such an environment can be described as matrix model with inclusions of ellipsoidal voids of different shapes, which are responsible for the fractured, granular and cavernous components of the void space. The form of such inclusions can be expressed as the format α=a/c (where a and c — fixed and rotating half-axis of the ellipsoid). In this formulation, the problem is complicated from the definition of one integral index (porosity coefficient) to an array of indicators (volume concentrations of different components of the void space, their shape and orientation). The issues of this work is studding the dependence of the volume elastic parameters of various complex rocks-reservoirs and to determine the necessary data set for the construction of methods for predicting the structure of the void space.

Design/methodology/approach. It is determined based on numerous studies, that the cheapest and at the same time sensitive and informative methods that allow to determine the structure of the void space are a combination of acoustic and density methods, which, depending on the research base, study the propagation of oscillations of different frequencies. The paper presents the results of the study of models of complex rocks-reservoirs of oil and gas, in which the same volume of void space acoustic properties vary significantly depending on the aspect ratio of different types of voids and the total porosity of the rock, obtained using the author’s utility «SDI» working on the basis of system principles and methods of mechanics of stochastic heterogeneous environment and which implemented an algorithm for sorting models with different concentrations of void formats.

Implications. The results of modeling for matrix models with two components of voids are rearranged for determine the total porosity coefficient for different parameters. The concentration of the matrix is postponed along the vertical axis, the volume concentration of one of the components of inclusions — along the horizontal axis.
The paper shows the conceptual narrowing of the field of solving the problem of the inversion of logging data at a concentration of voids of different sizes. The obtained result makes it possible to use the data of geophysical studies of wells (acoustic logging, broadband acoustic logging and gamma-gamma density method) to determine the structure of the pore space.

Keywords: acoustic properties, different types of pores, pore aspect ratio.

The full text of papers

References

  1. Vizhva S.A, Kozhan O.M. Methods of determining the structure of the void space and their application for solving problems of Geophysics, engineering Geology. Visnyk Taras Shevchenko National University of Kyiv. Geology. 2002. Vol. 22. P. 134—139 [in Russian].
  2. Prodajvoda G.T., Vizhva S.A., Bezrodna ².M., Prodajvoda T.G. Geophysical methods of assessing the productivity of oil and gas reservoir. Kyiv: VPC «Kyiv University», 2011. [in Ukrainian].
  3. Prodajvoda G.T., Vizhva S.A., V³rshilo ².V. Mathematical modeling of effective geophysical parameters. Kyiv: VPC «Kyiv University, 2012. P. 287 [in Ukrainian].
  4. Prodajvoda G.T., Maslov B.P., Korol’ V.V. The Definition of spectrum of distribution of parameters of structure of fracture-porous space of rocks by inversion data of the dependence of the velocity of elastic waves from pressure. Geophysical journal. 1995. Vol. 17. P. 75—80 [in Russian].
  5. Al-Raoush R.I., Willson C.S. Extraction of physically realistic pore network properties from three-dimensional synchrotron X-ray microtomography images of unconsolidated porous media systems. Journal of hydrology, 2005. Vol. 300(1—4). P. 44—64. https://doi.org/10.1016/j.jhydrol.2004.05.005
  6. Berryman J.G. Single-scattering approximations for coefficients in Biot’s equations of poroelasticity. The Journal of the Acoustical Society of America. 1992. Vol. 91(2). P. 551—571. https://doi.org/10.1121/1.402518
  7. Fournier F., Pellerin M., Villeneuve Q. Et al. The equivalent pore aspect ratio as a tool for pore type prediction in carbonate reservoirs. AAPG Bulletin. 2018. Vol. 102(7). P. 1343—1377. https://doi.org/10.1306/10181717058
  8. Karimpouli S., Tahmasebi P. Conditional reconstruction: An alternative strategy in digital rock physics. Geophysics. 2016. Vol. 81(4). D465—D477. https://doi.org/10.1190/geo2015-0260.1
  9. Karimpouli S., Tahmasebi P., Saenger E.H. Estimating 3D elastic moduli of rock from 2D thin-section images using differential effective medium theory. Geophysics. 2018. Vol. 83(4), MR211-MR219. https://doi.org/10.1190/geo2017-0504.1
  10. Khalimendik V., Virshylo I. Velocities of elastic waves modeling for complex reservoir rocks. In 16th International Conference on Geoinformatics-Theoretical and Applied Aspects (2017, May). https://doi.org/10.3997/2214-4609.201701859
  11. Kuster G.T., Toksöz M.N. Velocity and attenuation of seismic waves in two-phase media: Part I. Theoretical formulations. Geophysics. 1974. Vol. 39(5). P. 587—606. https://doi.org/10.1190/1.1440450
  12. Müller-Huber E., Schön J., Börner F. Pore space characterization in carbonate rocks—approach to combine nuclear magnetic resonance and elastic wave velocity measurements. Journal of Applied Geophysics. 2016. Vol. 127. P. 68—81. https://doi.org/10.1016/j.jappgeo.2016.02.011
  13. Ren X.H., Stapf S., Blümich B. Magnetic resonance visualisation of flow and pore structure in packed beds with low aspect ratio. Chemical Engineering & Technology: Industrial Chemistry-Plant Equipment-Process Engineering-Biotechnology, 2005. Vol. 28(2). P. 219—225. https://doi.org/10.1002/ceat.200407092
  14. Schmitt M., Halisch M., Müller C., Fernandes C.P. Classification and quantification of pore shapes in sandstone reservoir rocks with 3-D X-ray micro-computed tomography. Solid Earth. 2016. Vol. 7(1). P. 285—300. https://doi.org/10.5194/se-7-285-2016
  15. Zerhouni O., Tarantino M.G., Danas K., Hong F. Influence of the internal geometry on the elastic properties of materials using 3D printing of computer-generated random microstructures. SEG Technical Program Expanded Abstracts. 2018. P. 3713—3718. https://doi.org/10.1190/segam2018-2998182.1

 

Received 10/07/2019