A Predictive Model for Maceral Discrimination by Means of Raman Spectra on Dispersed Organic Matter: A Case Study from the Carpathian Fold-and-Thrust Belt (Ukraine)

Abstract

In this study, we propose a predictive model for maceral discrimination based on Raman spectroscopic analyses of dispersed organic matter. Raman micro-spectroscopy was coupled with optical and Rock-Eval pyrolysis analyses on a set of seven samples collected from Mesozoic and Cenozoic successions of the Outer sector of the Carpathian fold and thrust belt. Organic petrography and Rock-Eval pyrolysis evidence a type II/III kerogen with complex organofacies composed by the coal maceral groups of the vitrinite, inertinite, and liptinite, while thermal maturity lies at the onset of the oil window spanning between 0.42 and 0.61 Ro%. Micro-Raman analyses were performed, on approximately 30–100 spectra per sample but only for relatively few fragments was it possible to perform an optical classification according to their macerals group. A multivariate statistical analysis of the identified vitrinite and inertinite spectra allows to define the variability of the organofacies and develop a predictive PLS-DA model for the identification of vitrinite from Raman spectra. Following the first attempts made in the last years, this work outlines how machine learning techniques have become a useful support for classical petrography analyses in thermal maturity assessment.

Characterization of the evolution of thermal maturity and pore structure of continental organic-rich shales

“…These increases in separation between the D-and G-bands may be caused by the increase in number of larger aromatic clusters and improved structural ordering of kerogen as maturity increases (Schito et al, 2017;. Further investigations have speculated that these shifts may be attributed to the wavelength dependence of the D-band position and the independence of the excitation energy of the G-band position in the Raman spectra of carbonaceous materials (Marshall et al, 2010;Lünsdorf, 2016;Schito et al, 2017;Schito et al, 2021). The VR, T max , and D-and G-band shifts of the original and pyrolyzed samples are listed in Table 3.…”

Calibrating Carbonization Temperatures of Wood Fragments Embedded within Pyroclastic Density Currents through Raman Spectroscopy

“…In recent years, Raman spectroscopy was demonstrated to be a powerful tool for the analysis of carbonaceous material. It is now routinely used to assess maximum paleotemperature experienced by the rocks during prograde regional metamorphisms [26][27][28] and is becoming one of the most-used methods for thermal maturity assessment in diagenetic environment [29][30][31][32][33][34][35][36][37][38][39][40]. The main advantages of this geothermometer are its nondestructive nature, the minimum or null time for sample preparation and the ability to provide quantitative chemical parameters with a definition within microns.…”