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Impact of Different Experimental Heating Rates on Calculated Hydrocarbon Generation Kinetics
Energy & Fuels ( IF 5.3 ) Pub Date : 2017-09-15 00:00:00 , DOI: 10.1021/acs.energyfuels.7b01035 Yuanyuan Ma 1, 2 , Tingting Cao 1, 2 , Lloyd Snowdon 1, 2 , Menhui Qian 1, 2 , Qigui Jiang 1, 2 , Maowen Li 1, 2 , Nicolaj Mahlstedt 3 , Brian Horsfield 3
Energy & Fuels ( IF 5.3 ) Pub Date : 2017-09-15 00:00:00 , DOI: 10.1021/acs.energyfuels.7b01035 Yuanyuan Ma 1, 2 , Tingting Cao 1, 2 , Lloyd Snowdon 1, 2 , Menhui Qian 1, 2 , Qigui Jiang 1, 2 , Maowen Li 1, 2 , Nicolaj Mahlstedt 3 , Brian Horsfield 3
Affiliation
Four organic-rich samples from four basins in China have been analyzed, using open-system bulk pyrolysis with heating rates ranging from 0.7 K/min to 40 K/min. The resulting programs have been digitized and first-order Arrhenius kinetics have been optimized using groups of different heating rate ranges. Low heating rate optimization was performed for data generated at 5 K/min, 2 K/min, and either 0.7 or 1 K/min. High heating rate optimization used experimental rates of 15, 25, and 40 K/min. Optimization was also completed for wide heating rate ranges at 40 K/min, 15 K/min, and either 1 or 2 K/min. The kinetics solutions were then used to calculate bulk hydrocarbon generation at a geological heating rate of 3 K/Ma, in order to determine the impact of using different experimental approaches. The results showed that low versus high and narrow versus wide heating rates did not yield systematically different results. The highest predicted geological temperature was observed for the low heating rates (Huadian, Ordos), high heating rates (Maoming), and wide heating rate range (Wang18 and Ordos). The wide heating rate ranges yielded predicted temperatures that were between the high and low heating rates for Huadian and Maoming but higher than or equal to both narrow range rates for Wang18 and Ordos. The results from the Source Rock Analyzer optimized using Kinetics2015 software predicted similar activation energy distributions and frequency factors and, consequently, similar geological temperatures for all samples to the Rock-Eval results optimized using Kinetics2005 software, although the samples run on the two instruments were not homogeneous aliquots but rather separate pieces broken from field or core samples. Predicted temperatures for 50% transformation at a geological heating rate show a variability of less than ±6 °C, which translates to a burial difference of <300 m for a basin with a “normal” geothermal gradient.
更新日期：2017-09-15
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