Theoretical and methodological approaches to identifying deep accumulations of oil and gas in oil and gas basins of the Russian Federation
Теоретические и методические подходы к выявлению глубоких залежей нефти и газа в нефтегазоносных бассейнах Российской Федерации
2023-05-17
SCID: 54.1/qqwgha54
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deep and ultra-deep oil and gas accumulationsgeochemical studies of hydrocarbons and bitumoidskerogen type and transformationsedimentary basin typification (Russian basins)thermobaric conditions
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Abstract (AI)
A large number of oil and gas accumulations at deep and ultra-deep depths, recently revealed in the world due to the development of drilling technologies, forces a revision of theoretical ideas on many issues, including conditions of oil and gas formation and hydrocarbon conservation in zones of high pressures and temperatures, as well as evaluating the possibility of conservation and formation of reservoirs. Among the most discussed, in this regard, are the issues determining the processes and rate of oil and gas formation at deep and ultra-deep depths, which differ significantly from those at small and medium depths: Thermobaric conditions responsible for the possibility of formation, phase distribution and conservation of hydrocarbons, geochemical indicators—type of kerogen, and its transformation, responsible for the phase distribution and staging of generation peaks—lithological composition of kerogen-bearing strata—the rate and scale of dip and uplift and the timing of exposure to high temperatures—the formation of overlapping saline strata and the presence of deep conductive faults that significantly affect temperature and pressure gradients. Analysis of the influence of the above factors on the prospects of deep-lying complexes taking into account new studies and achievements, mainly in the sedimentary basins of China (Tarim, Jungar, Ordos, Sichuan), the Gulf of Mexico and offshore Brazil (Santos) allowed typifying the sedimentary basins and major depressions of Russia, with the allocation of areas with high and ultra-low depth potential for hydrocarbon studies. Thermobaric and historical and geological criteria have been developed and a methodology for detailed study of promising areas has been proposed, including a complex of geochemical studies of hydrocarbons, extracts of bitumoids (pyrolytic, chromatographic) and lithological and petrophysical core studies aimed at assessing the prospects of oil and gas content of deep complexes in Russian sedimentary basins and the subsequent localization of the most promising areas for deep drilling.
Key Findings
1
A methodology combining thermobaric, historical-geological criteria and integrated geochemical, bitumoid, lithological and petrophysical core studies is proposed to evaluate and localize promising deep drilling targets in Russia.
2
Analysis of global deep-basin studies (China, Gulf of Mexico, Santos) enabled typification of Russian sedimentary basins and identification of areas with high and ultra-low deep-depth hydrocarbon potential.
3
Deep and ultra-deep oil and gas accumulations require revision of theories on hydrocarbon formation and conservation under high pressure-temperature conditions.
4
Formation of overlying saline strata and presence of deep conductive faults significantly alter temperature and pressure gradients, affecting deep hydrocarbon prospectivity.
5
Processes and rates of hydrocarbon generation at deep depths differ significantly from shallow/medium depths due to thermobaric conditions, kerogen type/transformation, and burial/uplift history.
Research Object
Deep and ultra-deep oil and gas accumulations/complexes in sedimentary basins of the Russian Federation
Research Subject
Theoretical and methodological criteria and evaluation of factors (thermobaric conditions, kerogen type and transformation, lithology, burial/uplift history, saline seals, deep faults) and geochemical/petrophysical study methods to identify, assess prospectivity, and localize promising deep hydrocarbon accumulations for deep drilling
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2023-05-17
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References available in scid.ai6
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