The metallogenic fluid and metallogenic material sources are discussed through analyzing the sulfur isotope of pyrite and published carbon, hydrogen and oxygen isotopic data from main uranium deposits in southern Zhuguang granitic batholith. Sulfur isotope studies show that the δ 34 S value is -0.2‰~-0.5‰ in pyrite from nonmineralized fresh diabase that intrude in granite, -6.5‰~ -10.9‰ in pyrite from mineralized cataclastic diabase that cut by fault and -17.4‰~-17.9‰ in pyrite from uraniumrich granitic cataclasite formed by fault. The δ 34 S value is significant different between the uranium-rich granitic cataclasite and non-mineralized diabase that indicate the sulfur of uranium-rich ore is not possible from diabase, which may from the surrounding wall rock by hydrothermal extraction. δD H2O -δ 18 O H2O plot map shows that hydrogen and oxygen isotopic of quartz vein of metallogenic stage are located in mixing area between the metamorphic water, primary magmatic water or mantle fluid and atmospheric precipitation water. Due to the big time differences between uranium mineralizaion and granite wall rock, also during uranium mineralization there is no obvious regional metamorphism, so the metallogenic fluid is impossible from metamorphic water or primary magmatic water. The changes of δ 18 O H2O may be caused by isotope exchange reaction between the wall rock and atmospheric precipitation when the hydrothermal temperature arising. The 13 C value of deposits is -9.8‰~ -4.3‰ that fall in range of southern China granite and mantle carbon 13 C value. Combined with the feature of sulfur, hydrogen and oxygen isotopes, it is inferred that the carbon in the metallogenic fluid may also come from wall rock granite.
A probabilistic method named discovery process modeling is described for estimating the quantity of undiscovered oil and gas resources in Aral sea area in the North Ustrurt basin. In this model, the pool size distribution was demonstrated, and the numbers and sizes of undiscovered pools were estimated. The most likely remaining plays potential in Area sea area is 3447.2 Billions of standard cubic meters of gas in place. The eastern Jurassic-Cretaceous play bears 2901.5 Billions of standard cubic meters of undiscovered gas in place, and 17 gas pools are yet to be discovered; the paleogene-Neogene play bears 545.7 Billions of standard cubic meters of undiscovered gas in place, and 13 gas pools are yet to be discovered. Based on resources analysis, the Aral sea area is a prospecting exploration area for gas, and the emphasis should be strengthened on the eastern Jurassic-Cretaceous play.
In oil and gas exploration of Block K in Amu Darya basin Uzbekistan, the reservoir lithologies are mainly in different carbonate rocks, the more types of rocks, the more various reservoir space is, as a result, it brings some difficulties to the reservoir quantitative evaluation. Therefore, according to this situation that the difficulty in identification of complex carbonate lithologies is, in this study block, artificial neural network analysis method is used in this paper. The method combines mud logging, cutting, core data, well logging, studies logging response characteristics of the different types of carbonate rocks, establishes lithology identification index. In this study, the method is used in identifying the types of carbonate rocks, the identified result compared to actual rocks displays about 70.51~87.23%, and it plays the positive role for reservoir quantitative evaluation.
The North Ustyurt basin, located in Central Asia, is an important gas-bearing potential area, but the gas source has been the key difficult point. Based on the geo-chemical analysis of Jurassic mudstone samples and research on the petroleum geology, the qualitative evaluation was conducted, it proposed that middle Jurassic source rock was dominative hydrocarbon-generation source rock for relative high organic matter abundance and maturity compared to upper and lower Jurassic source rocks. According to the thickness distribution of dark mudstones, Kosbulak sag, Sudochi sag and Barsakelmes sag were preferable hydrocarbon-generation sags.
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