A new method for quantitative phase analysis is proposed by using X-ray diffraction multi-peak match intensity ratio. This method can obtain the multi-peak match intensity ratio among each phase in the mixture sample ...A new method for quantitative phase analysis is proposed by using X-ray diffraction multi-peak match intensity ratio. This method can obtain the multi-peak match intensity ratio among each phase in the mixture sample by using all diffraction peak data in the mixture sample X-ray diffraction spectrum and combining the relative intensity distribution data of each phase standard peak in JCPDS card to carry on the least square method regression analysis. It is benefit to improve the precision of quantitative phase analysis that the given single line ratio which is usually adopted is taken the place of the multi-peak match intensity ratio and is used in X-ray diffraction quantitative phase analysis of the mixture sample. By analyzing four-group mixture sample, adopting multi-peak match intensity ratio and X-ray diffraction quantitative phase analysis principle of combining the adiabatic and matrix flushing method, it is tested that the experimental results are identical with theory.展开更多
In this paper, the methods developed by?[1] are used to analyze flowback data, which involves modeling flow both before and after the breakthrough of formation fluids. Despite the versatility of these techniques, achi...In this paper, the methods developed by?[1] are used to analyze flowback data, which involves modeling flow both before and after the breakthrough of formation fluids. Despite the versatility of these techniques, achieving an optimal combination of parameters is often difficult with a single deterministic analysis. Because of the uncertainty in key model parameters, this problem is an ideal candidate for uncertainty quantification and advanced assisted history-matching techniques, including Monte Carlo (MC) simulation and genetic algorithms (GAs) amongst others. MC simulation, for example, can be used for both the purpose of assisted history-matching and uncertainty quantification of key fracture parameters. In this work, several techniques are tested including both single-objective (SO) and multi-objective (MO) algorithms for history-matching and uncertainty quantification, using a light tight oil (LTO) field case. The results of this analysis suggest that many different algorithms can be used to achieve similar optimization results, making these viable methods for developing an optimal set of key uncertain fracture parameters. An indication of uncertainty can also be achieved, which assists in understanding the range of parameters which can be used to successfully match the flowback data.展开更多
This article mainly introduces statistical methods for analyzing univariate quantitative data in paired design,including the hypothesis testing whether the population mean represented by the differences equals to 0 an...This article mainly introduces statistical methods for analyzing univariate quantitative data in paired design,including the hypothesis testing whether the population mean represented by the differences equals to 0 and its confidence interval estimation.Also,this article gives typical examples in the field of medical research as well as solutions,SAS programs,explanations and results. Outlined below are the main issues discussed in this article:展开更多
文摘A new method for quantitative phase analysis is proposed by using X-ray diffraction multi-peak match intensity ratio. This method can obtain the multi-peak match intensity ratio among each phase in the mixture sample by using all diffraction peak data in the mixture sample X-ray diffraction spectrum and combining the relative intensity distribution data of each phase standard peak in JCPDS card to carry on the least square method regression analysis. It is benefit to improve the precision of quantitative phase analysis that the given single line ratio which is usually adopted is taken the place of the multi-peak match intensity ratio and is used in X-ray diffraction quantitative phase analysis of the mixture sample. By analyzing four-group mixture sample, adopting multi-peak match intensity ratio and X-ray diffraction quantitative phase analysis principle of combining the adiabatic and matrix flushing method, it is tested that the experimental results are identical with theory.
文摘In this paper, the methods developed by?[1] are used to analyze flowback data, which involves modeling flow both before and after the breakthrough of formation fluids. Despite the versatility of these techniques, achieving an optimal combination of parameters is often difficult with a single deterministic analysis. Because of the uncertainty in key model parameters, this problem is an ideal candidate for uncertainty quantification and advanced assisted history-matching techniques, including Monte Carlo (MC) simulation and genetic algorithms (GAs) amongst others. MC simulation, for example, can be used for both the purpose of assisted history-matching and uncertainty quantification of key fracture parameters. In this work, several techniques are tested including both single-objective (SO) and multi-objective (MO) algorithms for history-matching and uncertainty quantification, using a light tight oil (LTO) field case. The results of this analysis suggest that many different algorithms can be used to achieve similar optimization results, making these viable methods for developing an optimal set of key uncertain fracture parameters. An indication of uncertainty can also be achieved, which assists in understanding the range of parameters which can be used to successfully match the flowback data.
文摘This article mainly introduces statistical methods for analyzing univariate quantitative data in paired design,including the hypothesis testing whether the population mean represented by the differences equals to 0 and its confidence interval estimation.Also,this article gives typical examples in the field of medical research as well as solutions,SAS programs,explanations and results. Outlined below are the main issues discussed in this article:
