Vitrinite maturity and programmed pyrolysis are conventional methods to evaluate organic matter (OM) regarding its thermal maturity. Moreover, vitrinite reflectance analysis can be difficult if prepared samples have no primary vitrinite or dispersed widely. Raman spectroscopy is a nondestructive method that has been used in the last decade for maturity evaluation of organic matter by detecting structural transformations, however, it might suffer from fluorescence background in low mature samples. In this study, four samples of different maturities from both shale formations of Bakken (the upper and lower members) Formation were collected and analyzed with Rock-Eval (RE) and Raman spectroscopy. In the next step, portions of the same samples were then used for the isolation of kerogen and analyzed by Raman spectroscopy. Results showed that Raman spectroscopy, by detecting structural information of OM, could reflect thermal maturity parameters that were derived from programmed pyrolysis. Moreover, isolating kerogen will reduce the background noise (fluorescence) in the samples dramatically and yield a better spectrum. The study showed that thermal properties of OM could be precisely reflected in Raman signals.

A 59 m-thick section of a freshwater oil shale interbedded with marlstone of Lower Carboniferous (Tournaisian) age from the Big Marsh area in Antigonish Basin, Nova Scotia, Canada, was examined using reflected light microscopy, Rock-Eval pyrolysis, X-ray diffractometry analysis, inductively coupled plasma-mass spectrometry for elemental analysis, and prompt γ for boron concentration. The oil shale was deposited in a lacustrine environment based on geology, sedimentology, variation in organic matter, and boron content (28–54 ppm). Organic petrology classified the oil shale into three broadly distinct types. Type A oil shale is a coastal facies shale containing terrestrially derived macerals, such as vitrinite and inertinite, sporinite, with some lamalginite, and amorphous bituminous matrix. Type B oil shale was deposited in a shallow-water facies and contains mostly lamalginite and some vitrinite and sporinite. Type C oil shale is a relatively deep-water facies, associated with open-water Torbanite-type oil shale and contains mostly Botryococcus colonial telalginite. The oil shale is thermally mature (T_max is 441–443 °C). Total organic carbon (TOC) varies from 5.8 to 7.3 wt %, and the hydrogen index is between 507 and 557 mg HC/g TOC. The rate of sedimentation as determined by the Th/U ratio indicates possibility of three sedimentation periods: an irregular but mostly slow rate of sedimentation from the base of the section up to 68 m, followed by a regular and slow rate between 68 and 53 m, and a regular and fast rate between 53 m and the top of the section. The higher Th/U ratio during deposition of the shallow-water facies was due to the input of allochthonous U. The redox conditions, as reflected in the variation of Cr to Mo, U, and Ni + V, indicate that the oil shale was deposited under suboxic–dysoxic conditions. The high organic productivity by phytoplankton and bacteria is characterized by a low Cr and high V/Cr ratio and suboxic conditions. In contrast, the well-oxygenated and uniform, warm-temperature upper water level supports a dysoxic environment. Variation of Sr/Ca vs Mn/Ca ratios indicates that most samples have low values, a characteristic of colder water and high terrigenous influx. The post-Archean Australian shale (PAAS)-normalized rare earth elements (REEs) follow three trends. Type A oil shale has the highest concentration of total REEs (648 ppm) and light REEs (LREEs, 605 ppm) as compared with type C (269 and 233 ppm), which are less than half of type A. Type B oil shale has the lowest total REEs (184 ppm) and LREEs (152 ppm). The concentration of heavy REEs decreased from 43 ppm in type A oil shale to 36 ppm in type C oil shale. Comparison of PAAS-normalized REEs for the three oil shale types indicates a reduction of the negative Eu anomaly with depth, which is possibly related to sedimentary sorting as a result of accumulation of fine sediments in the deeper water zone of the lake. The concentration of most elements of environmental concern is similar to and/or lower than the world shale. However, there are instances of higher concentrations of hazardous elements (e.g., As, Cd, Mo, and Se).

Samples were taken at different levels of thermal maturity in the unconventional Bakken source rock. Programmed pyrolysis derived T_max, solid bitumen reflectance, liptinite group maceral UV fluorescence, and nuclear magnetic resonance spectroscopy as different thermal maturity indicators were utilized in order to compare redox-sensitive trace metal (TM) concentration to maturity variations and disclose any probable relationship. Comparing redox-sensitive TMs with total organic carbon revealed the presence of anoxic/euxinic conditions in the depositional environment of the Bakken Shale. Although some of the TMs (V and Mo) exhibit slightly positive correlations with some of the thermal maturity indices used in this study, the correlations between other redox-sensitive TMs with maturity were neutral. Collectively, this study demonstrates that thermal maturity may have an impact on some redox-sensitive TMs such as Mo and V concentrations in marine sediments. Additional samples spanning higher maturities will need to be included because there is a possibility that an increase in thermal maturity may lead to the release and liberation of some redox-sensitive TMs from the organic matter (OM) directly. Remineralization and decomposition of OM with thermal maturity advance could release sulfur as a source of thermogenic H₂S, which could accelerate pore water/rock interaction and authigenic Fe-sulfides. This could enhance the capability of uptaking of most of the redox-sensitive TMs and increase their concentration in pore water.

The combustion of fossil fuels from the input of oil refineries, power plants, and the venting or flaring of produced gases in oil fields leads to greenhouse gas emissions. Economic usage of greenhouse and flue gases in conventional and unconventional reservoirs would not only enhance the oil and gas recovery but also offers CO₂ sequestration. In this regard, the accurate estimation of the interfacial tension (IFT) between the injected gases and the crude oils is crucial for the successful execution of injection scenarios in enhanced oil recovery (EOR) operations. In this paper, the IFT between a CO₂/N₂ mixture and n-alkanes at different pressures and temperatures is investigated by utilizing machine learning (ML) methods. To this end, a data set containing 268 IFT data was gathered from the literature. Pressure, temperature, the carbon number of n-alkanes, and the mole fraction of N₂ were selected as the input parameters. Then, six well-known ML methods (radial basis function (RBF), the adaptive neuro-fuzzy inference system (ANFIS), the least square support vector machine (LSSVM), random forest (RF), multilayer perceptron (MLP), and extremely randomized tree (extra-tree)) were used along with four optimization methods (colliding bodies optimization (CBO), particle swarm optimization (PSO), the Levenberg–Marquardt (LM) algorithm, and coupled simulated annealing (CSA)) to model the IFT of the CO₂/N₂ mixture and n-alkanes. The RBF model predicted all the IFT values with exceptional precision with an average absolute relative error of 0.77%, and also outperformed all other models in this paper and available in the literature. Furthermore, it was found that the pressure and the carbon number of n-alkanes would show the highest influence on the IFT of the CO₂/N₂ and n-alkanes, based on sensitivity analysis. Finally, the utilized IFT database and the area of the RBF model applicability were investigated via the leverage method.