Data for: Machine learning approaches for petrographic classification of carbonate-siliciclastic rocks using well logs and textural information
Published: 28 June 2018| Version 1 | DOI: 10.17632/5zb4vbvmx7.1
Contributors:
Camila Saporetti, Leonardo da Fonseca, Leonardo de Oliveira, Egberto PereiraDescription
The database obtained from Fournier (2009) combines (1) ultrasonic measurements of P- and S-wave velocities at various effective pressures, (2) density and porosity measurements, (3) quantitative mineralogic analyses using X-ray diffraction (XRD), (4) detailed petrographic studies of thin sections, and (5) critical porosity and elastic properties of microporous mixed carbonate-siliciclastic rocks. Fournier, F., & Borgomano, J. (2009). Critical porosity and elastic properties of microporous mixed carbonate-siliciclastic rocks. Geophysics, 74, E93–E109.
Files
Categories
Geophysics, Computational Intelligence