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Abstract

Summary

When dealing with the challenges of geophysical monitoring, one crucial problem is modeling realizations of random fields in a three-dimensional area. This involves working with various correlation functions. Previous research of authors has addressed correlation functions such as Bessel, also Whittle–Matérn, or “power”, and also spherical, pentamodel, and “cubic” types. In the work described here, the focus is on improving both the numerical modeling method and the algorithm specifically for random fields with a “cubic” type correlation function.

Long-term geophysical studies have been conducted in the industrial area of Rivne NPP. One of the primary interests in these observations has been radioisotope surveys of soil density and moisture along the station buildings’ perimeter. To complement the observed data and address areas that were inaccessible for direct monitoring, statistical modeling was employed. Specifically, the method simulated additional values of the studied parameter over a three-dimensional grid representing the studied area.

During the study, the average density of the chalk stratum was modeled using a “cubic” correlation function, enabling a detailed statistical map of its distribution in the 3D area. The algorithm for statistical modeling using a “cubic” correlation function was also improved.

Finally, a comprehensive statistical analysis was performed to verify the adequacy of the numerical simulation results, ensuring that the method meets the required standards for geophysical monitoring applications.

EAGE Publications BV © 2025 The Authors © European Association of Geoscientists and Engineers
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2025-04-14
2026-02-09

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/content/papers/10.3997/2214-4609.2025510191
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The Improved Algorithm for Statistical Modeling of Dataset in 3D Area with «cubic» Variogram on Rivne NPP Example
Conference Proceedings 2025, 1 (2025); https://doi.org/10.3997/2214-4609.2025510191
/content/papers/10.3997/2214-4609.2025510191
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