In the process of geothermal exploitation and utilization, the reinjection amount of used geothermal water in super-deep and porous reservoir is small and significantly decreases over time. This has been a worldwide p...In the process of geothermal exploitation and utilization, the reinjection amount of used geothermal water in super-deep and porous reservoir is small and significantly decreases over time. This has been a worldwide problem, which greatly restricts the exploitation and utilization of geothermal resources. Based on a large amount of experiments and researches, the reinjection research on the tail water of Xianyang No.2 well, which is carried out by combining the application of hydrogeochemical simulation, clogging mechanism research and the reinjection experiment, has achieved breakthrough results. The clogging mechanism and indoor simulation experiment results show: Factors affecting the tail water reinjection of Xianyang No.2 well mainly include chemical clogging, suspended solids clogging, gas clogging, microbial clogging and composite clogging, yet the effect of particle migration on clogging has not been found; in the process of reinjection, chemical clogging was mainly caused by carbonates(mainly calcite), silicates(mainly chalcedony), and a small amount of iron minerals, and the clogging aggravated when the temperature rose; suspended solids clogging also aggravated when the temperature rose, which showed that particles formed by chemical reaction had a certain proportion in suspended solids.展开更多
We present here for the first time,the Raman and infrared spectroscopic investigation of amphiboles from the World's deepest borehole,the Kola super-deep borehole,at the depth of 11.66 km.The Kola Super-deep boreh...We present here for the first time,the Raman and infrared spectroscopic investigation of amphiboles from the World's deepest borehole,the Kola super-deep borehole,at the depth of 11.66 km.The Kola Super-deep borehole(SG-3)(henceforth referred as KSDB)is located in the northwest of the Kola Peninsula in the northern frame of the Pechenga structure,Russia.It was drilled in the north-eastern part of the Baltic Shield(69о5’N,30о44’E)and reached a depth of 12.262 km.It has been drilled in the northern limb of the Pechenga geosyncline composed of rhythmically inter-bedded volcanogenic and tuffaceous-sedimentary strata extending to the NW at 300°–310°and dipping to SW at angles of 30°–50°.The SG-3 geological section is represented by two complexes–Proterozoic and Archaean.Amphibolite facies is dominant in the depth region from 6000 m to 12,000m to the deepest.The Raman spectra of the sample reveal abundant presence of plagioclase and amphiboles.The most distinct Raman peak in this study indicates the tremolite-ferro-actinolite rich enrichment of the borehole samples at this depth corroborating earlier conventional petrographic studies.展开更多
针对现有超分辨率重建网络具有较高的计算复杂度和存在大量内存消耗的问题,提出了一种基于Transformer-CNN的轻量级图像超分辨率重建网络,使超分辨率重建网络更适合应用于移动平台等嵌入式终端。首先,提出了一个基于Transformer-CNN的...针对现有超分辨率重建网络具有较高的计算复杂度和存在大量内存消耗的问题,提出了一种基于Transformer-CNN的轻量级图像超分辨率重建网络,使超分辨率重建网络更适合应用于移动平台等嵌入式终端。首先,提出了一个基于Transformer-CNN的混合模块,从而增强网络捕获局部−全局深度特征的能力;其次,提出了一个改进的倒置残差块来特别关注高频区域的特征,以提升特征提取能力和减少推理时间;最后,在探索激活函数的最佳选择后,采用GELU(Gaussian Error Linear Unit)激活函数来进一步提高网络性能。实验结果表明,所提网络可以在图像超分辨率性能和网络复杂度之间取得很好的平衡,而且在基准数据集Urban100上4倍超分辨率的推理速度达到91 frame/s,比优秀网络SwinIR(Image Restoration using Swin transformer)快11倍,表明所提网络能够高效地重建图像的纹理和细节,并减少大量的推理时间。展开更多
基金funded by National Science Foundation Project in 2015 (No.41472221)
文摘In the process of geothermal exploitation and utilization, the reinjection amount of used geothermal water in super-deep and porous reservoir is small and significantly decreases over time. This has been a worldwide problem, which greatly restricts the exploitation and utilization of geothermal resources. Based on a large amount of experiments and researches, the reinjection research on the tail water of Xianyang No.2 well, which is carried out by combining the application of hydrogeochemical simulation, clogging mechanism research and the reinjection experiment, has achieved breakthrough results. The clogging mechanism and indoor simulation experiment results show: Factors affecting the tail water reinjection of Xianyang No.2 well mainly include chemical clogging, suspended solids clogging, gas clogging, microbial clogging and composite clogging, yet the effect of particle migration on clogging has not been found; in the process of reinjection, chemical clogging was mainly caused by carbonates(mainly calcite), silicates(mainly chalcedony), and a small amount of iron minerals, and the clogging aggravated when the temperature rose; suspended solids clogging also aggravated when the temperature rose, which showed that particles formed by chemical reaction had a certain proportion in suspended solids.
基金National Institute of advanced Studies (NIAS)Indian National Science Academy (INSA) for the support in under the INSA senior Scientist scheme.
文摘We present here for the first time,the Raman and infrared spectroscopic investigation of amphiboles from the World's deepest borehole,the Kola super-deep borehole,at the depth of 11.66 km.The Kola Super-deep borehole(SG-3)(henceforth referred as KSDB)is located in the northwest of the Kola Peninsula in the northern frame of the Pechenga structure,Russia.It was drilled in the north-eastern part of the Baltic Shield(69о5’N,30о44’E)and reached a depth of 12.262 km.It has been drilled in the northern limb of the Pechenga geosyncline composed of rhythmically inter-bedded volcanogenic and tuffaceous-sedimentary strata extending to the NW at 300°–310°and dipping to SW at angles of 30°–50°.The SG-3 geological section is represented by two complexes–Proterozoic and Archaean.Amphibolite facies is dominant in the depth region from 6000 m to 12,000m to the deepest.The Raman spectra of the sample reveal abundant presence of plagioclase and amphiboles.The most distinct Raman peak in this study indicates the tremolite-ferro-actinolite rich enrichment of the borehole samples at this depth corroborating earlier conventional petrographic studies.
文摘针对现有超分辨率重建网络具有较高的计算复杂度和存在大量内存消耗的问题,提出了一种基于Transformer-CNN的轻量级图像超分辨率重建网络,使超分辨率重建网络更适合应用于移动平台等嵌入式终端。首先,提出了一个基于Transformer-CNN的混合模块,从而增强网络捕获局部−全局深度特征的能力;其次,提出了一个改进的倒置残差块来特别关注高频区域的特征,以提升特征提取能力和减少推理时间;最后,在探索激活函数的最佳选择后,采用GELU(Gaussian Error Linear Unit)激活函数来进一步提高网络性能。实验结果表明,所提网络可以在图像超分辨率性能和网络复杂度之间取得很好的平衡,而且在基准数据集Urban100上4倍超分辨率的推理速度达到91 frame/s,比优秀网络SwinIR(Image Restoration using Swin transformer)快11倍,表明所提网络能够高效地重建图像的纹理和细节,并减少大量的推理时间。
