By reviewing the development of “three-high” oil and gas well testing technology of Sinopec in recent years, this paper systematically summarizes the application of “three-high” oil and gas well testing technology...By reviewing the development of “three-high” oil and gas well testing technology of Sinopec in recent years, this paper systematically summarizes the application of “three-high” oil and gas well testing technology of Sinopec in engineering optimization design technology, and high temperature and high pressure testing technology, high pressure and high temperature transformation completion integration technology. Major progress has been made in seven aspects: plug removal and re-production technology of production wells in high acid gas fields;wellbore preparation technology of ultra-deep, high-pressure, and high-temperature oil and gas wells;surface metering technology;and supporting tool development technology. This paper comprehensively analyzes the challenges faced by the “three-high” oil and gas well production testing technology in four aspects: downhole tools, production testing technology, safe production testing, and the development of low-cost production test tools. Four development directions are put forward: 1) Improve ultra-deep oil and gas testing technology and strengthen integrated geological engineering research. 2) Deepen oil and gas well integrity evaluation technology to ensure the life cycle of oil and gas wells. 3) Carry out high-end, customized, and intelligent research on oil test tools to promote the low-cost and efficient development of ultra deep reservoirs. 4) Promote the fully automatic control of the surface metering process to realize the safe development of “three-high” reservoirs.展开更多
软件规模和复杂程度的不断提高,为软件质量保障带来了严峻的挑战.软件缺陷定位是一种重要的软件质量保障技术,其中基于频谱的缺陷定位(Spectrum-based Fault Localization,SFL)是应用最为广泛的软件缺陷定位技术,其通过分析语句覆盖信...软件规模和复杂程度的不断提高,为软件质量保障带来了严峻的挑战.软件缺陷定位是一种重要的软件质量保障技术,其中基于频谱的缺陷定位(Spectrum-based Fault Localization,SFL)是应用最为广泛的软件缺陷定位技术,其通过分析语句覆盖信息矩阵计算代码语句的可疑度值,并根据可疑度值定位缺陷所在语句.然而,语句覆盖信息矩阵中存在着严重的数据冗余问题,冗余的数据极大地影响了SFL的缺陷定位性能.以Defects4J数据集中395个程序的语句覆盖信息矩阵为例,在超过一半的语句覆盖信息矩阵中有90%的语句存在与其具有相同覆盖信息的语句.特征选择是常用的数据预处理技术,通过去除冗余和不相关特征来获取原始特征集中有价值的特征子集.因此,我们将语句覆盖信息矩阵作为原始特征集,将冗余覆盖信息约简建模为特征选择问题,提出了一种基于冗余覆盖信息约简的软件缺陷定位方法(Fault Localization based on Redundant coverage information Reduction,FLRR).首先,使用特征选择技术对语句覆盖信息和测试用例执行结果组成的语句覆盖信息矩阵进行约简,得到语句覆盖信息矩阵子集;然后,使用SFL计算语句覆盖信息矩阵子集中语句的可疑度值,并根据可疑度值对语句进行降序排列,以定位缺陷语句.本文使用六种常用的特征选择技术对语句覆盖信息矩阵进行特征选择和约简,以得到语句覆盖信息矩阵子集,并使用四种典型的SFL技术对语句覆盖信息矩阵子集中的语句进行缺陷定位.为评估FLRR的缺陷定位性能,本文使用E_(inspect)@n和MRR(Mean Reciprocal Rank)评价指标在基于Defects4J的数据集上与四种典型的SFL技术进行了对比实验.实验结果表明,FLRR能够有效提升SFL的缺陷定位性能.对于E_(inspect)@n指标,当n=1时,FLRR相比DStar、Ochiai、Barinel和OP2分别多定位到23条、26条、14条和13条缺陷语句,分别增加了69.70%、76.47%、45.16%和38.24%;对于MRR指标,FLRR相比DStar、Ochiai、Barinel和OP2分别提升了20.08%、24.94%、17.45%和19.15%.展开更多
The deficiency theories of dyslexia are quite contradictory and the cross-cultural studies in recent years mainly focused on whether the dyslexics among cultures shared the same cognitive profile or just based on the ...The deficiency theories of dyslexia are quite contradictory and the cross-cultural studies in recent years mainly focused on whether the dyslexics among cultures shared the same cognitive profile or just based on the language.This study used Near-Infrared Spectroscopy (NIRS) imaging to measure the regional cerebral blood volume (BV) and the changes of cerebral activation in the left prefrontal cortex of 12 Chinese dyslexic children and their 12 age-matched normal controls during the Paced Vis-ual Serial Addition Test (PVSAT).Results showed that the scores of PVSAT of dyslexic children were significantly lower than those of the normal children (t=3.33,P<0.01).The activations of the left pre-frontal cortex in the normal group were significantly greater than those of dyslexic children (all P<0.01).Our results indicated that Chinese dyslexia had a general deficiency in working memory and this may be caused by the abnormal metabolic activity of brain blood volume in the left prefrontal cortex and the deficits in brain function might be the basis of neuropathology of Chinese dyslexia.Present study sup-ports the difference on brain activation of dyslexics from different languages may be caused by the same cognitive system related to reading.展开更多
文摘By reviewing the development of “three-high” oil and gas well testing technology of Sinopec in recent years, this paper systematically summarizes the application of “three-high” oil and gas well testing technology of Sinopec in engineering optimization design technology, and high temperature and high pressure testing technology, high pressure and high temperature transformation completion integration technology. Major progress has been made in seven aspects: plug removal and re-production technology of production wells in high acid gas fields;wellbore preparation technology of ultra-deep, high-pressure, and high-temperature oil and gas wells;surface metering technology;and supporting tool development technology. This paper comprehensively analyzes the challenges faced by the “three-high” oil and gas well production testing technology in four aspects: downhole tools, production testing technology, safe production testing, and the development of low-cost production test tools. Four development directions are put forward: 1) Improve ultra-deep oil and gas testing technology and strengthen integrated geological engineering research. 2) Deepen oil and gas well integrity evaluation technology to ensure the life cycle of oil and gas wells. 3) Carry out high-end, customized, and intelligent research on oil test tools to promote the low-cost and efficient development of ultra deep reservoirs. 4) Promote the fully automatic control of the surface metering process to realize the safe development of “three-high” reservoirs.
文摘软件规模和复杂程度的不断提高,为软件质量保障带来了严峻的挑战.软件缺陷定位是一种重要的软件质量保障技术,其中基于频谱的缺陷定位(Spectrum-based Fault Localization,SFL)是应用最为广泛的软件缺陷定位技术,其通过分析语句覆盖信息矩阵计算代码语句的可疑度值,并根据可疑度值定位缺陷所在语句.然而,语句覆盖信息矩阵中存在着严重的数据冗余问题,冗余的数据极大地影响了SFL的缺陷定位性能.以Defects4J数据集中395个程序的语句覆盖信息矩阵为例,在超过一半的语句覆盖信息矩阵中有90%的语句存在与其具有相同覆盖信息的语句.特征选择是常用的数据预处理技术,通过去除冗余和不相关特征来获取原始特征集中有价值的特征子集.因此,我们将语句覆盖信息矩阵作为原始特征集,将冗余覆盖信息约简建模为特征选择问题,提出了一种基于冗余覆盖信息约简的软件缺陷定位方法(Fault Localization based on Redundant coverage information Reduction,FLRR).首先,使用特征选择技术对语句覆盖信息和测试用例执行结果组成的语句覆盖信息矩阵进行约简,得到语句覆盖信息矩阵子集;然后,使用SFL计算语句覆盖信息矩阵子集中语句的可疑度值,并根据可疑度值对语句进行降序排列,以定位缺陷语句.本文使用六种常用的特征选择技术对语句覆盖信息矩阵进行特征选择和约简,以得到语句覆盖信息矩阵子集,并使用四种典型的SFL技术对语句覆盖信息矩阵子集中的语句进行缺陷定位.为评估FLRR的缺陷定位性能,本文使用E_(inspect)@n和MRR(Mean Reciprocal Rank)评价指标在基于Defects4J的数据集上与四种典型的SFL技术进行了对比实验.实验结果表明,FLRR能够有效提升SFL的缺陷定位性能.对于E_(inspect)@n指标,当n=1时,FLRR相比DStar、Ochiai、Barinel和OP2分别多定位到23条、26条、14条和13条缺陷语句,分别增加了69.70%、76.47%、45.16%和38.24%;对于MRR指标,FLRR相比DStar、Ochiai、Barinel和OP2分别提升了20.08%、24.94%、17.45%和19.15%.
基金supported by a grant from National Natural Science Foundation of China (No. 30872132)
文摘The deficiency theories of dyslexia are quite contradictory and the cross-cultural studies in recent years mainly focused on whether the dyslexics among cultures shared the same cognitive profile or just based on the language.This study used Near-Infrared Spectroscopy (NIRS) imaging to measure the regional cerebral blood volume (BV) and the changes of cerebral activation in the left prefrontal cortex of 12 Chinese dyslexic children and their 12 age-matched normal controls during the Paced Vis-ual Serial Addition Test (PVSAT).Results showed that the scores of PVSAT of dyslexic children were significantly lower than those of the normal children (t=3.33,P<0.01).The activations of the left pre-frontal cortex in the normal group were significantly greater than those of dyslexic children (all P<0.01).Our results indicated that Chinese dyslexia had a general deficiency in working memory and this may be caused by the abnormal metabolic activity of brain blood volume in the left prefrontal cortex and the deficits in brain function might be the basis of neuropathology of Chinese dyslexia.Present study sup-ports the difference on brain activation of dyslexics from different languages may be caused by the same cognitive system related to reading.
