Based on the productivity equation of coalbed methane (CBM) well, considering the impact of coal reservoir reformability on gas well productivity, the main production layer optimization index in the “three-step metho...Based on the productivity equation of coalbed methane (CBM) well, considering the impact of coal reservoir reformability on gas well productivity, the main production layer optimization index in the “three-step method” of optimal combination of production layers is corrected, and then the CBM production layer potential index is introduced to evaluate favorable areas for commingled multi-coal seam production. Through analysis of the key parameters of coal reservoirs affecting the CBM productivity index, a development unit division method for areas with multi-coal seams is established, and a quantitative grading index system is proposed. On this basis, the evaluation process of CBM development favorable area is developed: the mature 3-D modeling technology is used to characterize the reservoir physical properties of multi-coal seams in full-scale;the production layer potential index of each grid is calculated, and the production layer potential index contour under single-layer or commingled multi-layer production are plotted;according to the distribution of the contour of production layer potential index, the quantitative index of CBM development unit is adopted to outline the grade I, II, III coal reservoir distribution areas, and thus to pick out the favorable development areas. The practical application in the Yuwang block of Laochang in Yunnan proved that the favorable area evaluation process proposed can effectively overcome the defects of selecting favorable development areas only relying on evaluation results of a major coal seam pay, and enhance the accuracy of the evaluation results, meeting the requirements of selecting favorable areas for multi-coal seam commingled CBM production.展开更多
锂离子电池的荷电状态(State of charge,SOC)和健康状态(State of health,SOH)是电池储能系统在运维过程中所需要估算的重要参数。为了能够对电池状态进行可靠估计,采用深度学习方法中的简单循环单元(Simple recurrent unit,SRU)来实现...锂离子电池的荷电状态(State of charge,SOC)和健康状态(State of health,SOH)是电池储能系统在运维过程中所需要估算的重要参数。为了能够对电池状态进行可靠估计,采用深度学习方法中的简单循环单元(Simple recurrent unit,SRU)来实现对电池SOC和SOH的联合估计。首先,通过利用SRU在处理时序问题上的优势,建立了基于SRU的电池SOC估计模型;接着,给模型引入了数据单元的输入形式,并使用含有电池老化信息的样本数据来对模型进行训练,使得训练好的模型能够实现任意电池老化程度下的SOC估计;最后,通过对该模型输出的SOC估计值中所隐含的老化信息进行挖掘,实现对电池SOH的估计。试验结果表明,该联合估计方法可以实现电池SOC与SOH的准确估计,并且对不同种类的电池也有较好的适用能力。展开更多
基金Supported by the National Natural Science Foundation of China(No.41772155)the National Science and Technology Major Project of China(No.2016ZX05044-002)the Fundamental Research Funds for the Central Universities of China(No.2015XKZD07)
文摘Based on the productivity equation of coalbed methane (CBM) well, considering the impact of coal reservoir reformability on gas well productivity, the main production layer optimization index in the “three-step method” of optimal combination of production layers is corrected, and then the CBM production layer potential index is introduced to evaluate favorable areas for commingled multi-coal seam production. Through analysis of the key parameters of coal reservoirs affecting the CBM productivity index, a development unit division method for areas with multi-coal seams is established, and a quantitative grading index system is proposed. On this basis, the evaluation process of CBM development favorable area is developed: the mature 3-D modeling technology is used to characterize the reservoir physical properties of multi-coal seams in full-scale;the production layer potential index of each grid is calculated, and the production layer potential index contour under single-layer or commingled multi-layer production are plotted;according to the distribution of the contour of production layer potential index, the quantitative index of CBM development unit is adopted to outline the grade I, II, III coal reservoir distribution areas, and thus to pick out the favorable development areas. The practical application in the Yuwang block of Laochang in Yunnan proved that the favorable area evaluation process proposed can effectively overcome the defects of selecting favorable development areas only relying on evaluation results of a major coal seam pay, and enhance the accuracy of the evaluation results, meeting the requirements of selecting favorable areas for multi-coal seam commingled CBM production.
文摘锂离子电池的荷电状态(State of charge,SOC)和健康状态(State of health,SOH)是电池储能系统在运维过程中所需要估算的重要参数。为了能够对电池状态进行可靠估计,采用深度学习方法中的简单循环单元(Simple recurrent unit,SRU)来实现对电池SOC和SOH的联合估计。首先,通过利用SRU在处理时序问题上的优势,建立了基于SRU的电池SOC估计模型;接着,给模型引入了数据单元的输入形式,并使用含有电池老化信息的样本数据来对模型进行训练,使得训练好的模型能够实现任意电池老化程度下的SOC估计;最后,通过对该模型输出的SOC估计值中所隐含的老化信息进行挖掘,实现对电池SOH的估计。试验结果表明,该联合估计方法可以实现电池SOC与SOH的准确估计,并且对不同种类的电池也有较好的适用能力。