Synthesis and characterization of Ni-Mo catalyst using Jatropha curcas leaves as carbon support and its catalytic activity for hydrotreating of gas oil,Jatropha oil,and their blends

A novel carbon-based Ni-Mo catalyst has been synthesized successfully from Jatropha curcas leaves using boric acid as a surface modifying agent. The Ni-Mo catalyst prepared on Jatropha curcas leaves had shown BET surface area of 316 m²/g whereas the Ni-Mo catalyst prepared without boric acid activation had shown BET surface area of only 14 m²/g. XRD and SEM data have shown that the active catalyst particles such as Ni and Mo have been found to be uniformly distributed. The inventive catalyst was studied for hydrotreating of gas oil, Jatropha curcas oil and 20% Jatropha oil in gas oil at 370°C, 90 bar H₂ pressure, liquid hour space velocity of 1 h^?1, and gas-to-oil ratio of 500 Nm³/m³ and the results obtained were found to be comparable with that of the commercial Ni-Mo catalyst supported on alumina.     

Co-optimization of carbon dioxide storage and enhanced oil recovery in oil reservoirs using a multi-objective genetic algorithm （NSGA-II）

Climate researchers have observed that the carbon dioxide （CO2） concentration in the atmosphere have been growing significantly over the past century. CO2 from energy represents about 75% of the greenhouse gas （GHG） emissions for Annex B （Developed） countries, and over 60% of global emissions. Because of impermeable cap rocks hydrocarbon reservoirs are able to sequester CO〉 In addition, due to high-demand for oil worldwide, injection of CO2 is a useful way to enhance oil production. Hence, applying an efficient method to co-optimize CO2 storage and oil production is vital. Lack of suitable optimization techniques in the past led most multi-objective optimization problems to be tackled in the same way as a single objective optimization issue. However, there are some basic differences between the multi and single objective optimization methods. In this study, by using a non- dominated sorting genetic algorithm （NSGA-II） for an oil reservoir, some appropriate scenarios are proposed based on simultaneous gas storage and enhanced oil recovery optimization. The advantages of this method allow us to amend production scenarios after implementing the optimization process, by regarding the variation of economic parameters such as oil price and CO2 tax. This leads to reduced risks and time duration of making new decisions based on upcoming situations.     

Geochemical characteristics of shale gas and its response to thermal maturity (Ro) in the Longmaxi formation,Dingshan area,Southeast Sichuan

The composition and carbon isotope distribution of shale gas from the Longmaxi Formation in the Dingshan area were measured, and their responses to thermal maturity (Ro) were analyzed. The results show that the shale gas is mainly composed of methane (97.98–98.99%), ethane, propane and nonhydrocarbon gases (N₂ and CO₂) and is an organic high temperature oil-type cracked gas. The wetness value [(C₂+C₃)/(C₁+C₂+C₃) × 100%] ranges from 0.39% to 0.74%. The early (Ro > 1.3%) residual kerogen and crude oil cracking gas was mixed with the late (Ro > 2.0%) secondary cracking gas, resulting in the full inversion of the carbon isotope sequence (δ¹³C₁?>?δ¹³C₂?>?δ¹³C₃).