Data for: Machine learning approaches for petrographic classification of carbonate-siliciclastic rocks using well logs and textural information

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.本数据集源自Fournier（2009）的研究，整合了以下五项内容：(1) 不同有效压力条件下纵波（P-wave）与横波（S-wave）速度的超声波测试；(2) 密度与孔隙度测量；(3) 采用X射线衍射（X-ray diffraction, XRD）完成的定量矿物学分析；(4) 岩石薄片的详细岩相学研究；(5) 微孔混合碳酸盐岩-硅质碎屑岩的临界孔隙度与弹性属性。 其文献引用信息为：Fournier, F. 与 Borgomano, J.（2009），《微孔混合碳酸盐岩-硅质碎屑岩的临界孔隙度与弹性属性》，Geophysics，74卷，E93–E109页。