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Poor solubility of substantial hydrocarbons in CO2 has constrained the use of CO2-EOR (enhanced oil recovery) in the modern oil recovery industry to some extent. Subsequently, it is significant to research the solubility regularity of various hydrocarbons in supercritical carbon dioxide (scCO2) in the first place. CO2 injection as one of the popular methodologies in light of financially and environmentally friendly has wide applications in EOR. In this paper, our objective is to estimate the solubility of n-alkanes in scCO2. This study highlights the application of a model based on least square support vector machine for estimation of solubility of n-alkanes in scCO2. The tuning parameters of the developed model were determined by an optimization algorithm, namely coupled simulated annealing. A set of 184 data points of solubility was used to execute the new model. To assess the accuracy and effectiveness of the developed model for prediction of experimental data, statistical and graphical techniques were used. Moreover, the outcomes were compared with the results of literature correlations to predict the solubility of alkanes. Results demonstrate that the model is precise and viable for prediction of solubility data. The resulted values of R2, root-mean-square error, SD, and % average absolute relative deviation for total data points are 0.99204, 0.12862, 0.6437, and 0.7753 for overall data, respectively. [ABSTRACT FROM AUTHOR]

Due to dense matrix and serious heterogeneity, the water flooding development effect is poor in Qiaojiaowa block, Yanchang Oilfield. Therefore, CO2 indoor flooding experiment is carried out to potentially evaluate CO2 flooding and water alternating gas (WAG) on the basis of water flooding, and optimize the injection parameters such as injecting velocity, slug size and the ratio of gas and water. Besides, yield predictions of water flooding, water flooding based on well optimized, CO2 flooding and WAG after injection CO2 for 5 years are conducted using numerical simulation. Experimental results show that it is a large potential in target block for CO2 flooding after water flooding. The enhanced oil recovery (EOR) improvement of CO2 flooding and WAG are 8. 43% and 20. 95% respectively compared with water flooding. Oil recovery with WAG increases first and then decreases with three injection parameters increase. The best injected velocity, slug size and gas-water ratio are 0. 73 mL/min, 0. 1 PV and 1 : 1. Simulation results show that the EOR improvement of water flooding based on well optimized, CO2 flooding and WAG after injecting CO2 for five years after developing 15 years are 0. 77%, 13. 81% and 12. 98% respectively compared with water flooding. The suggested production plan is WAG after injecting CO2 for five years. [ABSTRACT FROM AUTHOR]

A simple model for reconstructing the paleomagnetic field intensity with 10Be production rate was used for the first time in Loess 10Be studies of Luochuan profile. Using the LGM (Last Glacial Maxmium) method, the climatic effects and geomagnetic modulation effects on loess 10Be was separated and in turn the 80 ka geomagnetic excursion sequence reconstructed, of which the globally remarkable geomagnetic excursion events such as the Laschamp (42 ka), Mono Lake (32 ka) during the Last Glacial period were revealed and the paleo-geomagnetic intensity curve from Loess 10Be over the past 80 ka was quantitatively reconstructed. The reconstructed paleo-intensity fits well with the paleo-intensity curves (SINT200 and NAPIS75), which indicates the significance of global criterion of the 10Be paleo-intensity curve and the future direction of loess 10Be tracing studies. Results show the irregular variability of the East Asian monsoon precipitation in Loess Plateau is the main cause that has resulted in the ambiguity of the geomagnetic modulation of the 10Be record in the loess, and the intrinsic source component of the loess 10Be and inherited fraction of magnetic susceptibility (SUS) are characterized by the “quasi-homogeneous distribution” manner. [ABSTRACT FROM AUTHOR]

Poor solubility of substantial hydrocarbons in CO2 has constrained the use of CO2-EOR (enhanced oil recovery) in the modern oil recovery industry to some extent. Subsequently, it is significant to research the solubility regularity of various hydrocarbons in supercritical carbon dioxide (scCO2) in the first place. CO2 injection as one of the popular methodologies in light of financially and environmentally friendly has wide applications in EOR. In this paper, our objective is to estimate the solubility of n-alkanes in scCO2. This study highlights the application of a model based on least square support vector machine for estimation of solubility of n-alkanes in scCO2. The tuning parameters of the developed model were determined by an optimization algorithm, namely coupled simulated annealing. A set of 184 data points of solubility was used to execute the new model. To assess the accuracy and effectiveness of the developed model for prediction of experimental data, statistical and graphical techniques were used. Moreover, the outcomes were compared with the results of literature correlations to predict the solubility of alkanes. Results demonstrate that the model is precise and viable for prediction of solubility data. The resulted values of R2, root-mean-square error, SD, and % average absolute relative deviation for total data points are 0.99204, 0.12862, 0.6437, and 0.7753 for overall data, respectively. [ABSTRACT FROM AUTHOR]