APPI(+) FT-ICR MS as a Tool for Evaluating the Thermal Maturation of Petroleum Systems

Introduction

Aromatic biomarkers – mono and triaromatic steroids - can be used in oil-oil and oil-source rock correlation. They are also used to evaluate the thermal evolution of oils and condensates, generated in the regressive phase of the oil window (Peters and Modowan, 1993). The polyaromatics hydrocarbons (HPA’s) are thermodynamic more stable than those with methyl in the α position (Radke, 19900; van Aarssen et. al, 1999).

Molecular parameters obtained with biomarkers and another’s molecular markers are usually employed in the characterization of crude oils. Besides determination of the origin and presence of process of secondary alteration, the isomeric changes in biomarkers are usually used for estimating the thermal evolution of oils and condensates (Mackenzie et al., 1981; Seifert and Moldowan, 1978,1980). Most parameters are based on the relative abundance of two stereoisomers and involve the relative increase of the thermodynamically more stable isomer in relation to the one with the biologically inherited stereochemistry (Farrimond et al., 1998). For example, the C27-hopane compounds - 17 α(H), 21β(H)-22,29,30-trisnorhopane (Tm) and 18 α(H), 21β(H)-22,29,30-trisnorhopane (Ts) present different thermodynamic stabilities. Tm, which is less stable, has a relatively reduced concentration during catagenesis, in relation to Ts, which is more stable. Based on this characteristic, the relationship Ts/(Ts+Tm) (Seifert and Moldowan, 1978) was proposed to estimate thermal evolution. For steranes, the biological configuration αααR, thermodynamically less stable, disappears, while the more stable configuration - αββS has its relative concentration increased.

The aromatic biomarkers, mono and triaromatic steroids, resulting from the aromatization of steranes during diagenesis, are also used to evaluate thermal evolution (Mackenzie et al., 1981; Mackenzie et al., 1982). The aromatization of monoaromatic sterane (MA) to triaromatic sterane (TA) occurs with increasing temperature, as short-chain mono and triaromatic are even more stable than long-chain ones. These characteristics are reflected in the reasons TA/(MA+TA); MA(I)/MA(I+II) e TA(I)/TA(I+II), in these last two the numerators represent the short-chain compounds. In a way, the oil window range covered by the relationships between saturated and aromatics biomarkers are complementary. In general, saturated biomarkers reflect the thermal evolution until the peak of the oil window. In general, saturated biomarkers reflect the thermal evolution up to the peak of the oil window, Ro at 0.9%-1.0%, while aromatics evaluate it up to Ro of 1.3%-1.4%. FT-ICR MS cannot differentiate isomers, however other correlations can be proposed based on condensation reactions and thermal stability of some molecular markers. For the evaluation, the samples were acquired in APPI (+), a source that directly ionizes nonpolar ions such as hydrocarbons. In this way, the objective of this work was to analyze 18 oils from a Brazilian basin with different thermal evolutions using the APPI(+) FT-ICR MS technique.

Experimental

In this study, eighteen crude oil samples from a Brazilian Basin were analyzed. The crude oil samples were prepared by dissolving 10 mg of the oil in 10 mL of toluene. For APPI (+) analyses, 500 μL of the stock solution were collected and transferred to a vial containing 500 μL of methanol. The final concentration of the analyzed solution is ±500 ppm in toluene/methanol (50:50). The solvents methanol and toluene are HPLC grade and purchased from J.T. Baker (Phillipsburg, NJ, USA).

Mass spectrometry analyses were performed using a FT-ICR MS 7T SolariX 2xR (Bruker Daltonics - Bremen, Germany) coupled to an APPI source. Samples were injected using a syringe pump at a flow rate of 600 μL.h-1. 8 MW data sets were acquired using magnitude mode, 2ω detection, with a detection range spanning m/z 150-2000. Typically, a total of 300 scans were acquired for each sample to obtain spectra with excellent signal-to-noise ratios.

The data were internally calibrated using homologous series of the hydrocarbon class of radical cations (HC), by the Data Analysis 4.2 software (Bruker Daltonics GmbH, Bremen, Germany). The data were processed using the Composer 64 software (Version 1.5.3 Sierra Analytica, Modesto, USA). The graphs were produced using the software, Thanus (developed at CEMEP), Origin 2018 and the free software Metaboanalyst as a tool for multivariate analysis.

Results and Discussion

            Analyzing eighteen samples from a Brazilian basin using APP(+) FT-ICR MS it was possible, according to the graph, which displays distinct ranges of thermal evolution, analyze that the samples 94 and 95 are more thermally mature than 87, as indicated by their stronger signals and higher biomarkers. This suggests a more advanced stage of thermal alteration. Among the marine-derived samples, 87 shows the lowest thermal evolution, while 94 and 95 exhibit the highest. In contrast, 93 and 96 do not present ions corresponding to the C17 and C27 structures, likely due to extensive thermal cracking. Meanwhile, the lacustrine saline samples display very similar thermal evolution patterns, indicating a more uniform maturation process when compared to the more variable marine samples (Fig. 1).

Figure 1: Scatter plot using the ratios of triaromatic steroids divided by the sum of monoaromatic and triaromatic steroids (TA/TA+TM), using C17 and C27 for a Brazilian Basin samples.

Conclusions

With this method, it was possible to determine the thermal evolution of the samples, contributing significantly to the geochemical characterization of petroleum systems. The use of the APPI(+) source in FT-ICR MS enabled the detection of key biomarkers, allowing differentiation between maturity levels and thermal histories. This study reinforces the importance of biomarker analysis in evaluating the evolution of oil samples and demonstrates the effectiveness of APPI(+) in advancing petroleum characterization.