OIL-AND-GAS WELL SECTIONS IN DNIEPER-DONETS DEPRESSION: SIMULATING GEOACOUSTIC PROPERTIES VIA EXCLUDIING ACOUSTIC LOGGING MEASUREMENTS
Journal: Visnyk of Taras Shevchenko National University of Kyiv. Geology (Vol.66, No. 3)Publication Date: 2014-12-29
Authors : V. Kolisnichenko; G. Kashuba; E. Solodkyi;
Page : 82-87
Keywords : geoacoustic model; interval velocity; acoustic impedance; reflection coefficient;
Abstract
The paper is focused on evaluating feasibilities to propose a geoacoustic model for a section of formations in the Dnieper-Donetsk Depression based on available well logging data. It provides a review of the methods and techniques sufficient to simulate a geoacoustic model for well #6 in Svyrydivska field including elastic wave propagation and velocity, acoustic impedance of the formation, reflection coefficients via limited data of well logging. There were carried out both well logging data processing and interpretation in the case of rock section explored, followed by defining rock chemistry. The method of linear geoacoustic modeling was used to simulate elastic velocity, wave propogation, and rock density.
In this paper an attempt was made to classify all main methods necessary to elaborate a geoacoustic model using well logging data. There is studied simulated interval velocity and reflection coefficients based on electrical, neutron logging and normal dependency in the changes of rock petrophysical properties with depth. Input data included rocks resistivity measured by normal probes, lateral probes, and laterolog; porosity, de-fined by electrical logging; readings of gamma and neutron logs; hydrogen content; the depth of the deposits. The findings of the research are summarized in the table illustrating the equations used to simulate velocity, listing correlational pair coefficients of the hypothesized and verified velocity, a mean(-root)-square error of wave velocities, acoustic impedance, and reflection coefficients. The authors provide advice how to solve the problem with available well logging data and validate theoretical conclusions by statistical analysis.
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