Magnetic-field-driven spin catalysis as a fundamental mechanism of hydrocarbon generation on the Earth.

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Andrey Ponomarev, Marsel Kadyrov, Vitaliy Korytov, Svetlana Bakustina, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8158037/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Understanding the fundamental mechanisms that govern the hydrocarbon generation processes remains a critical challenge in the geosciences, particularly given that the current oil recovery factors rarely exceed 40%. Here we present experimental evidence that magnetic fields substantially enhance the hydrocarbon generation through spin-catalyzed radical reactions. Bituminous argillite samples from the Bazhenov Formation, West Siberia, were exposed herein to heat maturation at 270°C with and without a 50 mT magnetic field. The quantitative assessment using HAWK pyrolysis and electron paramagnetic resonance (EPR) revealed a significant increase in the hydrocarbon generation parameters (S₁, Production Index (PI), and oxygen index' (OI'), coupled with a decrease in the concentration of paramagnetic centers in the samples treated with the magnetic field. Statistical analysis by ANOVA and linear mixed models confirmed the statistical significance of these differences. Notably, the magnetic exposure strengthened the correlation between the PI and the paramagnetic center concentration (R² = 0.92 vs. 0.14 in controls), evidencing the spin-dependent radical reactions. These findings support Nesterov’s radical-reaction hypothesis and Buchachenko’s spin-catalysis theory in geological systems, opening new avenues for geomagnetically guided exploration criteria and potential magnetic-field-enhanced oil recovery in reservoirs. Petroleum Geology Bazhenov Formation spin catalysis magnetic field paramagnetic centers hydrocarbon generation EPR spectroscopy HAWK pyrolysis radical reactions Figures Figure 1 Figure 2 Figure 3 Figure 4 Main The genesis of hydrocarbon accumulations remains one of the greatest mysteries of nature. In modern petroleum exploration, where oil recovery factors typically do not exceed 40%, this suggests that the processes governing hydrocarbon reservoir formation are not yet fully understood. Geologists often note: “Tell me what happened yesterday, and I will tell you what will happen tomorrow”―the same holds for oil recovery factors. A precise knowledge of the hydrocarbon reservoir formation scenario would allow for the replication and embodiment of natural processes in technological processes of hydrocarbon reservoir development in order to increase the oil recovery factor. The present work builds upon the idea proposed by Ivan Ivanovich Nesterov (Tyumen, Russia). Nesterov’s hypothesis posits that radical reactions, along with chemical processes involving isotopes exhibiting an angular magnetic effect, play a fundamental role in hydrocarbon generation processes. Nesterov’s hypothesis in comparison to classical theories was described in our previous studies 1 , 2 . The review of the chemical-kinetic modeling of hydrocarbon generation processes is not detailed herein, as it was published previously 3 . Conceptually, I.I. Nesterov argues that the actual geological temperatures within the sedimentary cover are insufficient to break the high-energy C–C (carbon-carbon) bonds in kerogen and heavy oil fractions. Notably, I.I. Nesterov points out that the thermal decomposition of oil begins at temperatures above 300°C. This implies that during its generation and geochemical evolution, oil had already overcome an energy barrier equivalent to this temperature 4 . In this regard, besides temperature and geological time, it is necessary to search for additional external energy sources that facilitated the overcoming of this energy barrier. In this context, Nesterov suggests and even outlines a scheme for the radical reactions where paramagnetic centers in the organic matter, resins, and asphaltenes act as catalysts to lower the energy barrier for bond cleavage in kerogen. Furthermore, Nesterov states that, in conjunction with this, electrokinetic effects manifest themselves during reservoir pressure drop, that is, the fluid flows in porous media are accompanied by streaming potentials and induced magnetic fields at the micro- and molecular levels. This is supported by Revil’s and co-workers’ studies 5 – 7 , in which the electrokinetic nature of these processes and the connection between the fluid flows and electrical/magnetic anomalies in rocks were detailed. According to the concept of spin catalysis, the resulting magnetic disturbances are capable of influencing the rate and pathway of chemical reactions by altering the spin states of radical pairs and intermediate complexes. This mechanism is described in detail in the works by Buchachenko et al. 8–10 , who demonstrated that external magnetic and spin interactions can intensify catalytic processes. Table 1 lists geological processes that may hypothetically induce spin catalysis effects in geological systems. This process is schematically illustrated in Fig. 1 . Table 1 Spin-catalysis effects and their manifestations in geological hydrocarbon systems Natural field type Typical amplitudes / ranges Variability / Geological context Ref. The Earth's main magnetic field (of core origin) at the surface ≈ 25,000–65,000 nТ (equator–poles) Secular variation (years–decades), polar drift 11, 12 Lithospheric (crustal) magnetic anomalies — continental regions Typically tens to hundreds of nT, often ~ 100–300 nT on grids; dependent on magnetic rock types and source depth Spatially stable; used for structural mapping and metallogenic prognosis 13, 14 Oceanic stripe magnetic anomalies of the seafloor (seafloor spreading) ~ 200–2,000 nT at sea level; wavelengths ~ 10–100 km Geologically stable; record the history of field reversals 15, 16 Localized signals in fault zones (seismo- and tectono-induced, electrokinetics) Typically fractions to single-digit nT; captured cosesimic signals of ~ 0.7–1.3 nT, rare precursors up to ~ 1.5 nT Short-term (seconds to days); linked to stress changes and fluid flows; signals are weak and rare 17, 18 External (ionospheric-magnetospheric) variations / magnetic storms From fractions of nT (quiet) to hundreds of ~ 1,000 nT (storms) in ground-based records; global Dst index during strong storms reaches − 400 nT and below Seconds to days; driven by solar activity; induce geoelectric fields and GIC 19–22 Volcanomagnetic/hydrothermal signals Rapid changes typically ~ 1–10 nT; local static anomalies can reach tens to hundreds of nT in calderas Hours to months; associated with heating/demagnetization and fluid movement 23, 24 It is difficult and nearly impossible to deny the presence of magnetic fields within the sedimentary cover at sites where hydrocarbon deposits are formed. These effects manifest across multiple scales: nuclear-electronic, atomic, molecular, and macro levels. In view of this, our research team from the I.I. Nesterov Scientific School has conducted an experimental study initiated in 2017. This paper presents unique experiments assessing the effect of a constant 50 mT magnetic field on hydrocarbon generation processes using disaggregated source rock samples from the Bazhenov Formation (black bituminous argillites) of the Salym oil field, West Siberia. The experiment involved heating the experimental samples with and without exposure to a constant 50 mT magnetic field, followed by the analysis of the samples by HAWK pyrolysis and electron paramagnetic resonance (EPR) spectroscopy. Based on the obtained results, it was unequivocally concluded that the external magnetic field directly influences hydrocarbon generation processes; moreover, unpaired carbon electrons in the heavy oil fractions and kerogen are involved in this process. The magnetic field strength of 50 mT was used to accelerate the simulation of spin-catalytic processes. Similar field strengths, or even higher, were applied in the spin chemistry and magnetic mineralogy studies 25 . The several-orders-of-magnitude difference between the laboratory magnetic field strength and natural fields was a conscious choice, as experiments spanning millions of years are infeasible to perform. The relatively high magnetic field strength in the experiment was intentionally elevated relative to geological processes and systems to capture observable effects and mark out a plan of future experiments. This approach was essential to unambiguously detect the effects and to chart a course for future research. In general, this discrepancy in field strength is offset by the prolonged exposure of hydrocarbons to weak geomagnetic fields over geological time. Materials This study reports a previously unpublished experiment that generally involved heating a desegregated rock sample (black bituminous argillite from the Bazhenov Formation in the Salym oil field, West Siberia) at 270⁰C under a constant 50 mT magnetic field. A simplified experimental design is schematically illustrated in Fig. 2 . Experimental workflow The detailed experimental workflow was implemented as follows: Source material: black bituminous argillite from the Bazhenov Formation in the Salym oil field of West Siberia; Sample preparation: the argillite was disaggregated via mechanical crushing; Quartering was performed to homogenize and evenly distribute the experimental samples; Samples were packaged in 30-g aliquots into aluminum foil. A total of 26 experimental samples were prepared: (a) 13 with chloroform extraction and (b) 13 without chloroform extraction; One sample with extraction and one without extraction were not subjected to heat and magnetic exposures (the control). The remaining 12 samples with extraction were divided into 6 pairs (6 samples heated under magnetic field, 6 heated without magnetic field). Similarly, the 12 samples without extraction were divided into 6 pairs (6 heated under magnetic field, 6 heated without magnetic field). The exposure temperature for all samples was 270 ± 1°C. The exposure time for each of the 6 pairs was 2, 4, 6, 8, 10, and 12 h, respectively. The magnetic field strength applied to the samples heated under a constant magnetic field was 50 mT. All samples were analyzed using the HAWK pyrolysis system. All samples were examined by EPR spectroscopy. Statistical analysis was performed, revealing significant differences in the characteristics of the samples heated with and without magnetic field. The experimental samples, including HAWK pyrolysis results and paramagnetic center (PMC) concentrations of free radicals, are tabulated in the Supporting information to this article. The Table also specifies the condition of the samples with or without extraction, with or without magnetic field exposure, and exposure time. In the context of this study, the data were analyzed with respect to the effect of the magnetic field on hydrocarbon generation processes, without evaluating the effects of prolonged exposure. Following the experiments and analyses by HAWK pyrolysis and electron paramagnetic resonance (EPR) spectrometry, the results underwent statistical processing. ANOVA and LMM One-way analysis of variance (ANOVA) assesses the variances in the means of parameters between groups by comparing the F-statistics and p-values calculated from the ratio of sums of squared deviations between groups, and within groups. Parameters with p < 0.05 are considered statistically significant, those with 0.05 ≤ p < 0.25 show a trend, and those with p ≥ 0.25 indicate no reliable effects 26 . Further, in accordance with the guidelines for multivariate statistical analysis, the relevant parameters were analyzed by linear mixed model (LMM) for the assessment of key indicators of hydrocarbon generation (e.g., OI′, EPR paramagnetic center intensity, S₁, and others) as dependent variables. Fixed effects included factors, such as treatment (magnetic field vs. no field), extraction (with vs. without extraction), time (heating duration), and their pairwise and triple interactions (treatment × extraction, treatment × time, extraction × time, treatment × extraction × time). The model was evaluated using the restricted maximum likelihood (REML) method, and the statistical significance of fixed effects was assessed using the t-statistic and corresponding p-values. Particular emphasis was placed on the effect of the magnetic field and its interaction with the extraction factor via the terms: treatment × extraction and treatment × extraction × time 27 . Statistical analysis results The results of statistical analysis evaluating the effect of the magnetic field on pyrolysis and EPR spectroscopy parameters are presented below. Table 2 outlines the one-way ANOVA results; the significance assessment is described hereinabove. Table 2 One-way ANOVA results Parameter df Sum Sq F-value p-value S1 1.0 1.380408 1.8276 0.206194 S3 1.0 0.567675 3.6070 0.086735 Tmax 1.0 2.083333 1.6234 0.231435 OI 1.0 102.0833 4.5404 0.058940 PI 1.0 0.001925 1.9801 0.189691 OSI 1.0 261.3333 2.1462 0.173645 GOC-Generative OC 1.0 0.060208 1.7767 0.212130 OI′ 1.0 96.33333 8.8110 0.014086 PMC EPR 1.0 0.016133 6.6759 0.027240 PMC EPR: paramagnetic center (PMC) and electron paramagnetic resonance (EPR) spectroscopy; OI′: Oxygen Index′ The one-way ANOVA revealed the most pronounced differences between the controls and treatment groups for the OI′ (F = 8.81; p = 0.014) and EPR signal intensity of paramagnetic centers (F = 6.68; p = 0.027), indicating a statistically significant effect of the magnetic field on the oxygen index and spin activity of the organic matter. Parameters OI (p ≈ 0.059) and S₃ (p ≈ 0.087) showed a trend toward a change, whereas the remaining parameters (S₁, Tmax, PI, OSI, GOC) revealed no significant differences (p > 0.1). However, compared to the other pyrolysis parameters, S₁ and PI still exhibited a high probability of differences, approximately 80%. Further multivariate analysis revealed key trends (Table 3 ). Table 3 Multivariate analysis results Parameter β SE t-statistic p-value Interpretation Average (magnet) Average (no magnet) Effect direction S1 0.018 0.010 1.80 0.075 trend 1.9083 1.2300 higher in magnetic field (+ 0.6783) S3 0.022 0.012 1.83 0.071 trend 1.6817 1.2467 higher in magnetic field (+ 0.4350) PI 0.015 0.009 1.67 0.098 trend 0.0733 0.0480 higher in magnetic field (+ 0.0253) OSI 0.020 0.011 1.82 0.073 trend 26.1667 16.8333 higher in magnetic field (+ 9.3334) GOC 0.017 0.009 1.89 0.065 trend 2.4400 2.2983 higher in magnetic field (+ 0.1417) OI′ 0.042 0.012 3.50 0.0008 significant 30.6667 25.0000 higher in magnetic field (+ 5.6667) PMC EPR 0.035 0.011 3.18 0.0015 significant 1.3183 1.3917 lower in magnetic field (− 0.0734) The multivariate statistical analysis enabled the documentation of trends in the most critical pyrolysis parameters associated with the generation processes (an increase in S₁ and PI). Given that Nesterov's hypothesis posits that radical reactions occur during the hydrocarbon generation processes, a relationship was plotted between the concentration of paramagnetic centers and the PI (Production Index) parameter, as shown in Fig. 3 . Analysis of the obtained relationships (Fig. 3 ) demonstrates a stable correlation between PI and the concentration of paramagnetic centers in both sample sets. In the sample set with extraction, the coefficients of determination are R² = 0.77 for the samples exposed to magnetic field, and R² = 0.45 for the samples without magnetic field. Meanwhile, the sample set without extraction shows contrasting differences: R² = 0.92 under magnetic field versus R² = 0.14 for the controls without magnetic field. Thus, the magnetic field exposure leads to a significant strengthening of the correlation between PI and the content of paramagnetic centers, especially in the untreated (non-extracted) samples, indicating the involvement of paramagnetic centers in the spin catalysis and hydrocarbon generation processes under heat exposure. Discussion The present study fundamentally relies on I.I. Nesterov's hypothesis regarding the impact of natural magnetic fields on hydrocarbon generation processes, which hypothesis posits that the magnetic fields can modulate the pathway of radical reactions in the sedimentary strata. The theoretical foundation for this approach is rooted in the spin catalysis concepts, as described by A.L. Buchachenko and co-authors as early as the 20th century, according to which the external magnetic fields alter the probability of transitions between the singlet and triplet states of radical pairs, thereby affecting the rate and direction of chemical reactions. Based on these premises, we conducted lab-scale experiments to simulate the thermal decomposition of source rocks under a 50 mT magnetic field. To assess the transformation of the organic matter, we employed HAWK pyrolysis and electron paramagnetic resonance (EPR) spectroscopy measurements. The EPR measurements enabled the quantification of paramagnetic center (PMC) concentration. Statistical analysis included a one-way analysis of variance (ANOVA) and a linear mixed model (LMM), which alloed the quantitative assessment of the magnetic field effect and the extraction factors. The findings revealed novel fundamental patterns in the interaction between magnetic fields and source rocks. It was discovered that heating the samples under magnetic field leads to an increase in the yield of light hydrocarbon fractions (parameters S₁ and PI), with a consistent inverse correlation observed between the Pyrolysis Index (PI) and the concentration of paramagnetic centers (PMCs), which was particularly pronounced in the samples exposed to the magnetic field (R² ≈ 0.92). This indicates that the enhanced generation of light hydrocarbons is accompanied by a decrease in the number of paramagnetic centers, which we interpret as evidence of their involvement in radical reactions. Thus, the magnetic field, by influencing the electron spins of organic radicals, promotes the acceleration of C–C bond cleavage reactions and concurrently facilitates redox processes. Indeed, the OI, OSI, and particularly OI′ values indicate an increased intensity of oxidative reactions in the presence of the magnetic field. The resulting oxygen-centered radicals, in concert with hydrocarbon radicals, are involved in the generation of light fractions, which aligns with the mechanism of spin catalysis in geological systems. The decreased paramagnetic center (PMC) concentrations, coupled with the concurrent increase in S₁ and PI, indicate a redistribution of the centers: the magnetic field promotes their consumption for the generation and oxidation processes, thereby reducing the overall detectable centers. This suggests that the magnetic effect does not merely activate radical processes but orchestrates the spin state of the system, increasing the probability of reactions that lead to the hydrocarbon formation. The obtained results and discussion are schematically illustrated in Fig. 4 . In a broader context, the obtained results partially confirm Nesterov's hypothesis that the effect of a magnetic field on oil generation processes indeed occurs in the presence of discrete geomagnetic anomalies, such as those associated with tectonic faults, fold zones, or episodes of geomagnetic reversals, all of which are accompanied by the increased local magnetic field intensity. These conditions can facilitate the spin-catalytic effects that accelerate the transformation of the organic matter into hydrocarbons in natural geological systems. The comprehensive analysis of the data allows for the conclusion that the magnetic field accelerates the hydrocarbon generation through the reduction of the energy barrier of radical reactions, simultaneously stimulating the coupled oxidative processes (the experiment was conducted in an open system with oxygen access). This is manifested in an increased yield of light fractions, higher oxygen indices, and a reduced number of paramagnetic centers, which are the characteristic signs of the spin-catalyzed mechanism for the magnetic-field-driven oil generation. Conclusion The experimental data demonstrate that the constant magnetic field of 50 mT significantly influences the hydrocarbon generation processes in the Bazhenov Formation. The observed increase in the S₁, PI, and OI′ parameters, coupled with a simultaneous decrease in paramagnetic center (PMC) concentration, evidences the involvement of the spin-dependent radical reactions in the hydrocarbon generation. This effect occurs through the reduction in the energy barrier of the C–C bond cleavage and through the activation of oxygen-centered radicals, leading to the acceleration of oil generation and the shift in the ratios of light to heavy fractions. Furthermore, the obtained results indicate the potential application of magnetic nanocatalysts for enhancing the oil recovery factor (ORF) in field conditions, where the impact of an external magnetic field is limited by the reservoir scale. In the future, with the advancement of the spin catalysis research, it may become feasible to develop a reservoir pressure maintenance system capable of generating in-situ magnetic fields via controlled oscillatory fluid flows. This would pave the way for reproducing the natural mechanisms of spin-catalyzed oil generation acceleration, and for establishing a fundamentally new class of magnetically controlled enhanced oil recovery technologies. References Ponomarev AA, Kadyrov MA, Gafurov MR, Zavatsky MD, Naumenko VO, Nurullina TS, Vaganov YV (2023) Magnetic field impact on geochemistry of soluble organic matter when heat-treating oil shales and search for analogies in nature. 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08:47:14","extension":"html","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":81463,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8158037/v1/2e055424f380ae61ab338772.html"},{"id":96449455,"identity":"3440a158-9ed8-491f-8eb3-007f2535c002","added_by":"auto","created_at":"2025-11-21 08:47:14","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":499586,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA conceptual scheme of the magnetic-field-driven reduction of the energy barrier for C–C bond cleavage under heating\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8158037/v1/80cf8044108f37e96a261725.png"},{"id":96455647,"identity":"13287523-7a41-4081-9db0-e4d8ff900310","added_by":"auto","created_at":"2025-11-21 10:04:28","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2509048,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA simplified experimental workflow for the Bazhenov Formation argillite: black argillite from the Salym oil field was crushed (\u0026lt;100 µm), homogenized, and divided into 30-g aliquots by quartering. Samples were wrapped in aluminum foil and exposed to heat (270 °C, 1 h) and/or 50 mT magnetic field, with the control and treatment groups analyzed via HAWK pyrolysis and EPR spectroscopy\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8158037/v1/5597bc6fb06fa1513c9721c6.png"},{"id":96455621,"identity":"ded15170-66d5-4896-b722-dddbdc95454c","added_by":"auto","created_at":"2025-11-21 10:04:25","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":106837,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRelationship between the Production Index (PI) and the PMC concentration of carbon-centered free radicals, and linear regression lines with R² values\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8158037/v1/2260e3a7afb74ae269d08489.png"},{"id":96449450,"identity":"607129a0-6889-4572-9651-351ecae50061","added_by":"auto","created_at":"2025-11-21 08:47:14","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":177628,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA schematic illustration of hydrocarbon generation processes in geosystems, according to the theory of radical reactions\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8158037/v1/8634fe33ef60968c0b0f49d2.jpeg"},{"id":96912964,"identity":"fa731d11-21c8-4ec5-b331-1e56c63775b8","added_by":"auto","created_at":"2025-11-27 13:45:41","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3687186,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8158037/v1/670cfa0a-df45-48c6-ac2e-638bbc3012b0.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eMagnetic-field-driven spin catalysis as a fundamental mechanism of hydrocarbon generation on the Earth.\u003c/p\u003e","fulltext":[{"header":"Main","content":"\u003cp\u003eThe genesis of hydrocarbon accumulations remains one of the greatest mysteries of nature. In modern petroleum exploration, where oil recovery factors typically do not exceed 40%, this suggests that the processes governing hydrocarbon reservoir formation are not yet fully understood. Geologists often note: \u0026ldquo;Tell me what happened yesterday, and I will tell you what will happen tomorrow\u0026rdquo;―the same holds for oil recovery factors. A precise knowledge of the hydrocarbon reservoir formation scenario would allow for the replication and embodiment of natural processes in technological processes of hydrocarbon reservoir development in order to increase the oil recovery factor.\u003c/p\u003e\u003cp\u003eThe present work builds upon the idea proposed by Ivan Ivanovich Nesterov (Tyumen, Russia). Nesterov\u0026rsquo;s hypothesis posits that radical reactions, along with chemical processes involving isotopes exhibiting an angular magnetic effect, play a fundamental role in hydrocarbon generation processes. Nesterov\u0026rsquo;s hypothesis in comparison to classical theories was described in our previous studies\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. The review of the chemical-kinetic modeling of hydrocarbon generation processes is not detailed herein, as it was published previously\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Conceptually, I.I. Nesterov argues that the actual geological temperatures within the sedimentary cover are insufficient to break the high-energy C\u0026ndash;C (carbon-carbon) bonds in kerogen and heavy oil fractions. Notably, I.I. Nesterov points out that the thermal decomposition of oil begins at temperatures above 300\u0026deg;C. This implies that during its generation and geochemical evolution, oil had already overcome an energy barrier equivalent to this temperature\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. In this regard, besides temperature and geological time, it is necessary to search for additional external energy sources that facilitated the overcoming of this energy barrier.\u003c/p\u003e\u003cp\u003eIn this context, Nesterov suggests and even outlines a scheme for the radical reactions where paramagnetic centers in the organic matter, resins, and asphaltenes act as catalysts to lower the energy barrier for bond cleavage in kerogen. Furthermore, Nesterov states that, in conjunction with this, electrokinetic effects manifest themselves during reservoir pressure drop, that is, the fluid flows in porous media are accompanied by streaming potentials and induced magnetic fields at the micro- and molecular levels. This is supported by Revil\u0026rsquo;s and co-workers\u0026rsquo; studies\u003csup\u003e\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e, in which the electrokinetic nature of these processes and the connection between the fluid flows and electrical/magnetic anomalies in rocks were detailed. According to the concept of spin catalysis, the resulting magnetic disturbances are capable of influencing the rate and pathway of chemical reactions by altering the spin states of radical pairs and intermediate complexes. This mechanism is described in detail in the works by Buchachenko et al. \u003csup\u003e8\u0026ndash;10\u003c/sup\u003e, who demonstrated that external magnetic and spin interactions can intensify catalytic processes. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e lists geological processes that may hypothetically induce spin catalysis effects in geological systems. This process is schematically illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e\u003cb\u003eSpin-catalysis effects and their manifestations in geological hydrocarbon systems\u003c/b\u003e\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNatural field type\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTypical amplitudes / ranges\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eVariability / Geological context\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRef.\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eThe Earth's main magnetic field (of core origin) at the surface\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026asymp;\u0026thinsp;25,000\u0026ndash;65,000 nТ (equator\u0026ndash;poles)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSecular variation (years\u0026ndash;decades), polar drift\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11, 12\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLithospheric (crustal) magnetic anomalies \u0026mdash; continental regions\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTypically tens to hundreds of nT, often\u0026thinsp;~\u0026thinsp;100\u0026ndash;300 nT on grids; dependent on magnetic rock types and source depth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSpatially stable; used for structural mapping and metallogenic prognosis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13, 14\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOceanic stripe magnetic anomalies of the seafloor (seafloor spreading)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e~\u0026thinsp;200\u0026ndash;2,000 nT at sea level; wavelengths\u0026thinsp;~\u0026thinsp;10\u0026ndash;100 km\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGeologically stable; record the history of field reversals\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15, 16\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLocalized signals in fault zones (seismo- and tectono-induced, electrokinetics)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTypically fractions to single-digit nT; captured cosesimic signals of ~\u0026thinsp;0.7\u0026ndash;1.3 nT, rare precursors up to ~\u0026thinsp;1.5 nT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eShort-term (seconds to days); linked to stress changes and fluid flows; signals are weak and rare\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e17, 18\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExternal (ionospheric-magnetospheric) variations / magnetic storms\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFrom fractions of nT (quiet) to hundreds of ~\u0026thinsp;1,000 nT (storms) in ground-based records; global Dst index during strong storms reaches \u0026minus;\u0026thinsp;400 nT and below\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSeconds to days; driven by solar activity; induce geoelectric fields and GIC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e19\u0026ndash;22\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVolcanomagnetic/hydrothermal signals\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRapid changes typically\u0026thinsp;~\u0026thinsp;1\u0026ndash;10 nT; local static anomalies can reach tens to hundreds of nT in calderas\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHours to months; associated with heating/demagnetization and fluid movement\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e23, 24\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u0026lt;Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e here\u0026gt;\u003c/p\u003e\u003cp\u003eIt is difficult and nearly impossible to deny the presence of magnetic fields within the sedimentary cover at sites where hydrocarbon deposits are formed. These effects manifest across multiple scales: nuclear-electronic, atomic, molecular, and macro levels.\u003c/p\u003e\u003cp\u003eIn view of this, our research team from the I.I. Nesterov Scientific School has conducted an experimental study initiated in 2017. This paper presents unique experiments assessing the effect of a constant 50 mT magnetic field on hydrocarbon generation processes using disaggregated source rock samples from the Bazhenov Formation (black bituminous argillites) of the Salym oil field, West Siberia. The experiment involved heating the experimental samples with and without exposure to a constant 50 mT magnetic field, followed by the analysis of the samples by HAWK pyrolysis and electron paramagnetic resonance (EPR) spectroscopy. Based on the obtained results, it was unequivocally concluded that the external magnetic field directly influences hydrocarbon generation processes; moreover, unpaired carbon electrons in the heavy oil fractions and kerogen are involved in this process. The magnetic field strength of 50 mT was used to accelerate the simulation of spin-catalytic processes. Similar field strengths, or even higher, were applied in the spin chemistry and magnetic mineralogy studies\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. The several-orders-of-magnitude difference between the laboratory magnetic field strength and natural fields was a conscious choice, as experiments spanning millions of years are infeasible to perform. The relatively high magnetic field strength in the experiment was intentionally elevated relative to geological processes and systems to capture observable effects and mark out a plan of future experiments. This approach was essential to unambiguously detect the effects and to chart a course for future research. In general, this discrepancy in field strength is offset by the prolonged exposure of hydrocarbons to weak geomagnetic fields over geological time.\u003c/p\u003e"},{"header":"Materials","content":"\u003cp\u003eThis study reports a previously unpublished experiment that generally involved heating a desegregated rock sample (black bituminous argillite from the Bazhenov Formation in the Salym oil field, West Siberia) at 270⁰C under a constant 50 mT magnetic field. A simplified experimental design is schematically illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eExperimental workflow\u003c/h2\u003e\u003cp\u003eThe detailed experimental workflow was implemented as follows:\u003c/p\u003e\u003cp\u003e\u003col\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e Source material: black bituminous argillite from the Bazhenov Formation in the Salym oil field of West Siberia;\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e Sample preparation: the argillite was disaggregated via mechanical crushing;\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eQuartering was performed to homogenize and evenly distribute the experimental samples;\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eSamples were packaged in 30-g aliquots into aluminum foil. A total of 26 experimental samples were prepared: (a) 13 with chloroform extraction and (b) 13 without chloroform extraction;\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eOne sample with extraction and one without extraction were not subjected to heat and magnetic exposures (the control).\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eThe remaining 12 samples with extraction were divided into 6 pairs (6 samples heated under magnetic field, 6 heated without magnetic field). Similarly, the 12 samples without extraction were divided into 6 pairs (6 heated under magnetic field, 6 heated without magnetic field).\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003e The exposure temperature for all samples was 270\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u0026deg;C.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eThe exposure time for each of the 6 pairs was 2, 4, 6, 8, 10, and 12 h, respectively. The magnetic field strength applied to the samples heated under a constant magnetic field was 50 mT.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eAll samples were analyzed using the HAWK pyrolysis system.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eAll samples were examined by EPR spectroscopy.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003cspan\u003e\u003cli\u003e\u003cp\u003eStatistical analysis was performed, revealing significant differences in the characteristics of the samples heated with and without magnetic field.\u003c/p\u003e\u003c/li\u003e\u003c/span\u003e\u003c/ol\u003e\u003c/p\u003e\u003cp\u003eThe experimental samples, including HAWK pyrolysis results and paramagnetic center (PMC) concentrations of free radicals, are tabulated in the Supporting information to this article. The Table also specifies the condition of the samples with or without extraction, with or without magnetic field exposure, and exposure time. In the context of this study, the data were analyzed with respect to the effect of the magnetic field on hydrocarbon generation processes, without evaluating the effects of prolonged exposure.\u003c/p\u003e\u003cp\u003eFollowing the experiments and analyses by HAWK pyrolysis and electron paramagnetic resonance (EPR) spectrometry, the results underwent statistical processing.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eANOVA and LMM\u003c/h3\u003e\n\u003cp\u003eOne-way analysis of variance (ANOVA) assesses the variances in the means of parameters between groups by comparing the F-statistics and p-values calculated from the ratio of sums of squared deviations between groups, and within groups. Parameters with p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 are considered statistically significant, those with 0.05\u0026thinsp;\u0026le;\u0026thinsp;p\u0026thinsp;\u0026lt;\u0026thinsp;0.25 show a trend, and those with p\u0026thinsp;\u0026ge;\u0026thinsp;0.25 indicate no reliable effects\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eFurther, in accordance with the guidelines for multivariate statistical analysis, the relevant parameters were analyzed by linear mixed model (LMM) for the assessment of key indicators of hydrocarbon generation (e.g., OI\u0026prime;, EPR paramagnetic center intensity, S₁, and others) as dependent variables. Fixed effects included factors, such as treatment (magnetic field vs. no field), extraction (with vs. without extraction), time (heating duration), and their pairwise and triple interactions (treatment \u0026times; extraction, treatment \u0026times; time, extraction \u0026times; time, treatment \u0026times; extraction \u0026times; time). The model was evaluated using the restricted maximum likelihood (REML) method, and the statistical significance of fixed effects was assessed using the t-statistic and corresponding p-values. Particular emphasis was placed on the effect of the magnetic field and its interaction with the extraction factor via the terms: treatment \u0026times; extraction and treatment \u0026times; extraction \u0026times; time\u003csup\u003e27\u003c/sup\u003e.\u003c/p\u003e\n\u003ch3\u003eStatistical analysis results\u003c/h3\u003e\n\u003cp\u003eThe results of statistical analysis evaluating the effect of the magnetic field on pyrolysis and EPR spectroscopy parameters are presented below.\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e outlines the one-way ANOVA results; the significance assessment is described hereinabove.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eOne-way ANOVA results\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003edf\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSum Sq\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eF-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.380408\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.8276\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.206194\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.567675\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.6070\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.086735\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTmax\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2.083333\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.6234\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.231435\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e102.0833\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.5404\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.058940\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.001925\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.9801\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.189691\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOSI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e261.3333\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.1462\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.173645\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGOC-Generative OC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.060208\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.7767\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.212130\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOI\u0026prime;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e96.33333\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e8.8110\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.014086\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePMC EPR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.016133\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e6.6759\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.027240\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003ePMC EPR: paramagnetic center (PMC) and electron paramagnetic resonance (EPR) spectroscopy; OI\u0026prime;: Oxygen Index\u0026prime;\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u0026lt;Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e here\u0026gt;\u003c/p\u003e\u003cp\u003eThe one-way ANOVA revealed the most pronounced differences between the controls and treatment groups for the OI\u0026prime; (F\u0026thinsp;=\u0026thinsp;8.81; p\u0026thinsp;=\u0026thinsp;0.014) and EPR signal intensity of paramagnetic centers (F\u0026thinsp;=\u0026thinsp;6.68; p\u0026thinsp;=\u0026thinsp;0.027), indicating a statistically significant effect of the magnetic field on the oxygen index and spin activity of the organic matter.\u003c/p\u003e\u003cp\u003eParameters OI (p\u0026thinsp;\u0026asymp;\u0026thinsp;0.059) and S₃ (p\u0026thinsp;\u0026asymp;\u0026thinsp;0.087) showed a trend toward a change, whereas the remaining parameters (S₁, Tmax, PI, OSI, GOC) revealed no significant differences (p\u0026thinsp;\u0026gt;\u0026thinsp;0.1).\u003c/p\u003e\u003cp\u003eHowever, compared to the other pyrolysis parameters, S₁ and PI still exhibited a high probability of differences, approximately 80%. Further multivariate analysis revealed key trends (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMultivariate analysis results\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eβ\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSE\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003et-statistic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eInterpretation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eAverage (magnet)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eAverage\u003c/p\u003e\u003cp\u003e(no magnet)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eEffect direction\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.018\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.075\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003etrend\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.9083\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1.2300\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003ehigher in magnetic field (+\u0026thinsp;0.6783)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eS3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.071\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003etrend\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.6817\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1.2467\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003ehigher in magnetic field (+\u0026thinsp;0.4350)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.098\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003etrend\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.0733\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.0480\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003ehigher in magnetic field (+\u0026thinsp;0.0253)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOSI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.011\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.073\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003etrend\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e26.1667\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e16.8333\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003ehigher in magnetic field (+\u0026thinsp;9.3334)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGOC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.065\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003etrend\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e2.4400\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e2.2983\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003ehigher in magnetic field (+\u0026thinsp;0.1417)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOI\u0026prime;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.042\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.0008\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003esignificant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e30.6667\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e25.0000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003ehigher in magnetic field (+\u0026thinsp;5.6667)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePMC EPR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.035\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.011\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.0015\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003esignificant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.3183\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1.3917\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003elower in magnetic field (\u0026minus;\u0026thinsp;0.0734)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u0026lt;Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e here\u0026gt;\u003c/p\u003e\u003cp\u003eThe multivariate statistical analysis enabled the documentation of trends in the most critical pyrolysis parameters associated with the generation processes (an increase in S₁ and PI).\u003c/p\u003e\u003cp\u003eGiven that Nesterov's hypothesis posits that radical reactions occur during the hydrocarbon generation processes, a relationship was plotted between the concentration of paramagnetic centers and the PI (Production Index) parameter, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAnalysis of the obtained relationships (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) demonstrates a stable correlation between PI and the concentration of paramagnetic centers in both sample sets. In the sample set with extraction, the coefficients of determination are R\u0026sup2; = 0.77 for the samples exposed to magnetic field, and R\u0026sup2; = 0.45 for the samples without magnetic field. Meanwhile, the sample set without extraction shows contrasting differences: R\u0026sup2; = 0.92 under magnetic field versus R\u0026sup2; = 0.14 for the controls without magnetic field. Thus, the magnetic field exposure leads to a significant strengthening of the correlation between PI and the content of paramagnetic centers, especially in the untreated (non-extracted) samples, indicating the involvement of paramagnetic centers in the spin catalysis and hydrocarbon generation processes under heat exposure.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present study fundamentally relies on I.I. Nesterov's hypothesis regarding the impact of natural magnetic fields on hydrocarbon generation processes, which hypothesis posits that the magnetic fields can modulate the pathway of radical reactions in the sedimentary strata. The theoretical foundation for this approach is rooted in the spin catalysis concepts, as described by A.L. Buchachenko and co-authors as early as the 20th century, according to which the external magnetic fields alter the probability of transitions between the singlet and triplet states of radical pairs, thereby affecting the rate and direction of chemical reactions. Based on these premises, we conducted lab-scale experiments to simulate the thermal decomposition of source rocks under a 50 mT magnetic field. To assess the transformation of the organic matter, we employed HAWK pyrolysis and electron paramagnetic resonance (EPR) spectroscopy measurements. The EPR measurements enabled the quantification of paramagnetic center (PMC) concentration.\u003c/p\u003e\u003cp\u003eStatistical analysis included a one-way analysis of variance (ANOVA) and a linear mixed model (LMM), which alloed the quantitative assessment of the magnetic field effect and the extraction factors. The findings revealed novel fundamental patterns in the interaction between magnetic fields and source rocks. It was discovered that heating the samples under magnetic field leads to an increase in the yield of light hydrocarbon fractions (parameters S₁ and PI), with a consistent inverse correlation observed between the Pyrolysis Index (PI) and the concentration of paramagnetic centers (PMCs), which was particularly pronounced in the samples exposed to the magnetic field (R\u0026sup2; \u0026asymp; 0.92). This indicates that the enhanced generation of light hydrocarbons is accompanied by a decrease in the number of paramagnetic centers, which we interpret as evidence of their involvement in radical reactions. Thus, the magnetic field, by influencing the electron spins of organic radicals, promotes the acceleration of C\u0026ndash;C bond cleavage reactions and concurrently facilitates redox processes. Indeed, the OI, OSI, and particularly OI\u0026prime; values indicate an increased intensity of oxidative reactions in the presence of the magnetic field. The resulting oxygen-centered radicals, in concert with hydrocarbon radicals, are involved in the generation of light fractions, which aligns with the mechanism of spin catalysis in geological systems.\u003c/p\u003e\u003cp\u003eThe decreased paramagnetic center (PMC) concentrations, coupled with the concurrent increase in S₁ and PI, indicate a redistribution of the centers: the magnetic field promotes their consumption for the generation and oxidation processes, thereby reducing the overall detectable centers. This suggests that the magnetic effect does not merely activate radical processes but orchestrates the spin state of the system, increasing the probability of reactions that lead to the hydrocarbon formation. The obtained results and discussion are schematically illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn a broader context, the obtained results partially confirm Nesterov's hypothesis that the effect of a magnetic field on oil generation processes indeed occurs in the presence of discrete geomagnetic anomalies, such as those associated with tectonic faults, fold zones, or episodes of geomagnetic reversals, all of which are accompanied by the increased local magnetic field intensity. These conditions can facilitate the spin-catalytic effects that accelerate the transformation of the organic matter into hydrocarbons in natural geological systems. The comprehensive analysis of the data allows for the conclusion that the magnetic field accelerates the hydrocarbon generation through the reduction of the energy barrier of radical reactions, simultaneously stimulating the coupled oxidative processes (the experiment was conducted in an open system with oxygen access). This is manifested in an increased yield of light fractions, higher oxygen indices, and a reduced number of paramagnetic centers, which are the characteristic signs of the spin-catalyzed mechanism for the magnetic-field-driven oil generation.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe experimental data demonstrate that the constant magnetic field of 50 mT significantly influences the hydrocarbon generation processes in the Bazhenov Formation. The observed increase in the S₁, PI, and OI\u0026prime; parameters, coupled with a simultaneous decrease in paramagnetic center (PMC) concentration, evidences the involvement of the spin-dependent radical reactions in the hydrocarbon generation. This effect occurs through the reduction in the energy barrier of the C\u0026ndash;C bond cleavage and through the activation of oxygen-centered radicals, leading to the acceleration of oil generation and the shift in the ratios of light to heavy fractions. Furthermore, the obtained results indicate the potential application of magnetic nanocatalysts for enhancing the oil recovery factor (ORF) in field conditions, where the impact of an external magnetic field is limited by the reservoir scale. In the future, with the advancement of the spin catalysis research, it may become feasible to develop a reservoir pressure maintenance system capable of generating in-situ magnetic fields via controlled oscillatory fluid flows. This would pave the way for reproducing the natural mechanisms of spin-catalyzed oil generation acceleration, and for establishing a fundamentally new class of magnetically controlled enhanced oil recovery technologies.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003ePonomarev AA, Kadyrov MA, Gafurov MR, Zavatsky MD, Naumenko VO, Nurullina TS, Vaganov YV (2023) Magnetic field impact on geochemistry of soluble organic matter when heat-treating oil shales and search for analogies in nature. 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New York: Springer, NY, USA, 528 p\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Bazhenov Formation, spin catalysis, magnetic field, paramagnetic centers, hydrocarbon generation, EPR spectroscopy, HAWK pyrolysis, radical reactions","lastPublishedDoi":"10.21203/rs.3.rs-8158037/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8158037/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eUnderstanding the fundamental mechanisms that govern the hydrocarbon generation processes remains a critical challenge in the geosciences, particularly given that the current oil recovery factors rarely exceed 40%. Here we present experimental evidence that magnetic fields substantially enhance the hydrocarbon generation through spin-catalyzed radical reactions. Bituminous argillite samples from the Bazhenov Formation, West Siberia, were exposed herein to heat maturation at 270\u0026deg;C with and without a 50 mT magnetic field. The quantitative assessment using HAWK pyrolysis and electron paramagnetic resonance (EPR) revealed a significant increase in the hydrocarbon generation parameters (S₁, Production Index (PI), and oxygen index' (OI'), coupled with a decrease in the concentration of paramagnetic centers in the samples treated with the magnetic field. Statistical analysis by ANOVA and linear mixed models confirmed the statistical significance of these differences. Notably, the magnetic exposure strengthened the correlation between the PI and the paramagnetic center concentration (R\u0026sup2; = 0.92 vs. 0.14 in controls), evidencing the spin-dependent radical reactions. These findings support Nesterov\u0026rsquo;s radical-reaction hypothesis and Buchachenko\u0026rsquo;s spin-catalysis theory in geological systems, opening new avenues for geomagnetically guided exploration criteria and potential magnetic-field-enhanced oil recovery in reservoirs.\u003c/p\u003e","manuscriptTitle":"Magnetic-field-driven spin catalysis as a fundamental mechanism of hydrocarbon generation on the Earth.","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-21 08:47:09","doi":"10.21203/rs.3.rs-8158037/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a0795f17-397c-4600-8d31-c6a8be6a806c","owner":[],"postedDate":"November 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":58276946,"name":"Petroleum Geology"}],"tags":[],"updatedAt":"2025-11-21T08:47:09+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-21 08:47:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8158037","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8158037","identity":"rs-8158037","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}