Diagenetic thermal evolution of organic matter by Raman spectroscopy

Schito, Andrea; Romano, Cláudia; Corrado, Sveva; Grigo, D.; Poe, Brent T.

doi:10.1016/j.orggeochem.2016.12.006

Cited by 156 publications

(170 citation statements)

References 56 publications

(60 reference statements)

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“…The second metric that provided an accurate regression for both VRo and sample-depth when the D2 peak was included in the fit was the band separation (VRo%: R 2 = 0.90, Table 4, Figure 6C; R 2 = 0.90, Table 5; Figure S6C in Supplementary Material). This is not surprising given that it is the D-band that shifts with changes in thermal maturity, while the G-band remains relatively stationary (Figure 2, Table 2) (Quirico et al, 2005;Schito et al, 2017). Therefore, most of the differences in band separation stem from the migration of the D-band to lower wavenumbers with increases in thermal maturity.…”

Section: Data Processingmentioning

confidence: 89%

“…It should be noted that this rationale is not without its own limitations, as thermal maturity as a function of sample-depth is dependent on thermal gradient, which can vary through time, subsidence rate, uplift (or lack thereof), and faulting. Sample-depth was also used as a thermal maturity proxy by Schito et al (2017).…”

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confidence: 99%

“…Vibrational spectroscopy has been evaluated as a potential technique for predicting the thermal maturity of carbonaceous samples (Spotl et al, 1998;Ferrari and Robertson, 2000;Beyssac et al, 2002;Quirico et al, 2005;Rahl et al, 2005;Guedes et al, 2010Guedes et al, , 2012Hinrichs et al, 2014;Wilkins et al, 2014;Zhou et al, 2014;Chen et al, 2015;Bonoldi et al, 2016;Lünsdorf, 2016;Lünsdorf and Lünsdorf, 2016;Sauerer et al, 2017;Schito et al, 2017;Schmidt et al, 2017). Most of this research has focused on Raman spectroscopy, an analytical tool that provides fast, non-destructive analyses, requires little-to-no sample preparation, and can grant both qualitative and quantitative information about the analyte.…”

mentioning

confidence: 99%

“…While studies comparing Raman spectral parameters to intrinsic properties like thermal maturity have uncovered some basic trends, they have employed a multitude of different experimental and spectral processing techniques to develop the correlations (Spotl et al, 1998;Quirico et al, 2003Quirico et al, , 2005Rahl et al, 2005;Guedes et al, 2010Guedes et al, , 2012Hinrichs et al, 2014;Lünsdorf et al, 2014;Wilkins et al, 2014;Zhou et al, 2014;Bonoldi et al, 2016;Lünsdorf, 2016;Lünsdorf and Lünsdorf, 2016;Schito et al, 2017). These methods differed in the number of samples evaluated, the acquisition parameters used to generate the data (excitation wavelength, spectral resolution, acquisition time, number of unique and random points measured per sample), data processing (i.e., baseline correction) and peak-fitting metrics (number of peaks, wavenumber, maximum peak width).…”

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confidence: 99%

“…Several studies have evaluated samples with VRo < 1%, with some results showing reasonable correlations, and others exhibiting higher error with decreases in VRo% (Keleman and Fang, 2001;Hinrichs et al, 2014;Wilkins et al, 2014;Bonoldi et al, 2016;Lünsdorf, 2016;Schito et al, 2017). Correlations of Raman spectral parameters with VRo values ranging from 0.3 to 1.5% provided coefficients of determination (R 2 ) of >0.90 when fit with power equations (Schito et al, 2017). Lünsdorf (2016) evaluated coal samples with VRo values as low as 0.50%.…”

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confidence: 99%

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Assessment of Thermal Maturity Trends in Devonian–Mississippian Source Rocks Using Raman Spectroscopy: Limitations of Peak-Fitting Method

et al. 2017

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The thermal maturity of shale is often measured by vitrinite reflectance (VRo). VRo measurements for the Devonian-Mississippian black shale source rocks evaluated herein predicted thermal immaturity in areas where associated reservoir rocks are oil-producing. This limitation of the VRo method led to the current evaluation of Raman spectroscopy as a suitable alternative for developing correlations between thermal maturity and Raman spectra. In this study, Raman spectra of Devonian-Mississippian black shale source rocks were regressed against measured VRo or sample-depth. Attempts were made to develop quantitative correlations of thermal maturity. Using sample-depth as a proxy for thermal maturity is not without limitations as thermal maturity as a function of depth depends on thermal gradient, which can vary through time, subsidence rate, uplift, lack of uplift, and faulting. Correlations between Raman data and vitrinite reflectance or sample-depth were quantified by peak-fitting the spectra. Various peak-fitting procedures were evaluated to determine the effects of the number of peaks and maximum peak widths on correlations between spectral metrics and thermal maturity. Correlations between D-frequency, G-band full width at half maximum (FWHM), and band separation between the G-and D-peaks and thermal maturity provided some degree of linearity throughout most peak-fitting assessments; however, these correlations and those calculated from the G-frequency, D/G FWHM ratio, and D/G peak area ratio also revealed a strong dependence on peak-fitting processes. This dependency on spectral analysis techniques raises questions about the validity of peak-fitting, particularly given the amount of subjective analyst involvement necessary to reconstruct spectra. This research shows how user interpretation and extrapolation affected the comparability of different samples, the accuracy of generated trends, and therefore, the potential of the Raman spectral method to become an industry benchmark as a thermal maturity probe. A Raman method devoid of extensive operator interaction and data manipulation is quintessential for creating a standard method.

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Section: Data Processingmentioning

confidence: 89%

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Assessment of Thermal Maturity Trends in Devonian–Mississippian Source Rocks Using Raman Spectroscopy: Limitations of Peak-Fitting Method

et al. 2017

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Micro‐ R aman Imaging of Planetary Analogs: Nanoscale Characterization of Past and Current Processes

Bower

Jabukek

Fries

et al. 2022

Spectroscopy and Characterization of Nanomaterials and Novel Materials

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Biomolecular histology as a novel proxy for ancient DNA and protein sequence preservation

Anderson

2022

Ecology and Evolution

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Researchers' ability to accurately screen fossil and subfossil specimens for preservation of DNA and protein sequences remains limited. Thermal exposure and geologic age are usable proxies for sequence preservation on a broad scale but are of nominal use for specimens of similar depositional environments. Cell and tissue biomolecular histology is thus proposed as a novel proxy for determining sequence preservation potential of ancient specimens with improved accuracy. Biomolecular histology as a proxy is hypothesized to elucidate why fossils/subfossils of some depositional environments preserve sequences while others do not and to facilitate selection of ancient specimens for use in molecular studies.

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Diagenetic thermal evolution of organic matter by Raman spectroscopy

Cited by 156 publications

References 56 publications

Assessment of Thermal Maturity Trends in Devonian–Mississippian Source Rocks Using Raman Spectroscopy: Limitations of Peak-Fitting Method

Assessment of Thermal Maturity Trends in Devonian–Mississippian Source Rocks Using Raman Spectroscopy: Limitations of Peak-Fitting Method

Micro‐ R aman Imaging of Planetary Analogs: Nanoscale Characterization of Past and Current Processes

Biomolecular histology as a novel proxy for ancient DNA and protein sequence preservation

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