Based on analysis of NMR T2 spectral characteristics,a new method for identifying fluid properties by decomposing T2 spectrum through signal analysis has been proposed.Because T2 spectrum satisfies lognormal distribut...Based on analysis of NMR T2 spectral characteristics,a new method for identifying fluid properties by decomposing T2 spectrum through signal analysis has been proposed.Because T2 spectrum satisfies lognormal distribution on transverse relaxation time axis,the T2 spectrum can be decomposed into 2 to 5 independent component spectra by fitting the T2 spectrum with Gauss functions.By analyzing the free relaxation response characteristics of crude oil and formation water,the dynamic response characteristics of the core mutual drive between oil and water,the petrophysical significance of each component spectrum is clarified.T2 spectrum can be decomposed into clay bound water component spectrum,capillary bound fluid component spectrum,micropores fluid component spectrum and macropores fluid component spectrum.According to the nature of crude oil in the target area,the distribution range of T2 component spectral peaks of oil-bearing reservoir is 165-500 ms on T2 time axis.This range can be used to accurately identify fluid properties.This method has high adaptability in identifying complex oil and water layers in low porosity and permeability reservoirs.展开更多
The method of regularization factor selection determines stability and accuracy of the regularization method. A formula of regularization factor was proposed by analyzing the relationship between the improved SVD and ...The method of regularization factor selection determines stability and accuracy of the regularization method. A formula of regularization factor was proposed by analyzing the relationship between the improved SVD and regularization method. The improved SVD algorithm and regularization method could adapt to low SNR. The regularization method is better than the improved SVD in the case that SNR is below 30 and the improved SVD is better than the regularization method when SNR is higher than 30. The regularization method with the regularization factor proposed in this paper can be better applied into low SNR (5〈SNR) NMR logging. The numerical simulations and real NMR data process results indicated that the improved SVD algorithm and regularization method could adapt to the low signal to noise ratio and reduce the amount of computation greatly. These algorithms can be applied in NMR logging.展开更多
The low porosity and low permeability of tight oil reservoirs call for improvements in the current technologies for oil recovery.Traditional chemical solutions with large molecular size cannot effectively flow through...The low porosity and low permeability of tight oil reservoirs call for improvements in the current technologies for oil recovery.Traditional chemical solutions with large molecular size cannot effectively flow through the nanopores of the reservoir.In this study,the feasibility of Nanofluids has been investigated using a high pressure high temperature core-holder and nuclear magnetic resonance(NMR).The results of the experiments indicate that the specified Nanofluids can enhance the tight oil recovery significantly.The water and oil relative permeability curve shifts to the high water saturation side after Nanofluid flooding,thereby demonstrating an increase in the water wettability of the core.In the Nanofluid flooding process the oil recovery was enhanced by 15.1%,compared to waterflooding stage.The T2 spectra using the NMR show that after Nanofluid flooding,a 7.18%increment in oil recovery factor was gained in the small pores,a 4.9%increase in the middle pores,and a 0.29%increase in the large pores.These results confirm that the Nanofluids can improve the flow state in micro-sized pores inside the core and increase the ultimate oil recovery factor.展开更多
为了实现致密岩心的孔隙量化表征,采用核磁共振(nuclear magnetic resonance,NMR)技术,利用T2弛豫时间和孔隙半径(r)的正比关系可测致密岩心的孔隙度、渗透率和孔径分布,利用核磁共振T2截止值可区分孔隙中的自由流体和束缚流体。从核磁...为了实现致密岩心的孔隙量化表征,采用核磁共振(nuclear magnetic resonance,NMR)技术,利用T2弛豫时间和孔隙半径(r)的正比关系可测致密岩心的孔隙度、渗透率和孔径分布,利用核磁共振T2截止值可区分孔隙中的自由流体和束缚流体。从核磁共振表征岩心孔隙的原理出发,分析了核磁共振T2谱与岩心孔隙度、渗透率、孔径分布、孔隙内可动流体的关系。根据上述原理,通过实例验证了核磁共振技术在致密岩心孔隙度和渗透率量化表征中的准确性和适用性。实验岩心的T2截止值和孔径分布测试表明:1号岩心T2截止值为21.85 ms,2号岩心的T2截止值为40.11 ms;1号岩心小孔隙分量大,2号岩心孔隙分布较均匀。截止值的计算结果表明地区经验法得出的T2截止值不完全适用于该区域的致密岩心,有必要建立区域性的截止值变化范围图版。展开更多
随着科学技术的发展,低场核磁共振(Low Field Nuclear Magnetic Resonance, LF-NMR)横向弛豫时间(Transverse Relaxation Time, T_2)反演谱检测技术越来越多的被应用于农业,但当前对T_2反演谱的解译尚停留在水分相态分布层面。为探索从...随着科学技术的发展,低场核磁共振(Low Field Nuclear Magnetic Resonance, LF-NMR)横向弛豫时间(Transverse Relaxation Time, T_2)反演谱检测技术越来越多的被应用于农业,但当前对T_2反演谱的解译尚停留在水分相态分布层面。为探索从物质成分角度对种子T_2反演谱进行解译的新方法,该研究以银杏种子为对象,利用低场核磁共振技术检测并对比银杏鲜种、种子粉末及其主要成分试样的T_2反演谱,分析各信号峰的形成机理,并以此为依据对其在种子萌发过程中的变化进行解译。研究结果表明:淀粉与蛋白质混合试样T_2反演谱的峰T_(21)、T_(22)、T_(23)以及淀粉与油脂混合试样的峰T_(24)在峰顶时间上和种子粉末试样相对应信号峰完全一致;在物质成分及配比完全相同的情况下,种子粉末试样T_2反演谱的峰T_(21)~T24的峰顶时间较鲜种分别相差12.98%、32.21%、13.02%、0%,T_(21)、T_(22)峰比例较鲜种分别偏少41.72%、29.33%,T_(23)峰比例偏多92.26%,T_(24)峰比例偏少91.71%,说明种子组织结构会对其内部水分的弛豫时间和相态分布比例造成一定影响。仅从物质成分角度考虑,种子内水分的弛豫时间主要在淀粉、蛋白质的影响下表现为T_(21)、T_(22)、T_(23),在淀粉和油脂的影响下表现为T_(24)。由此认为峰T_(21)、T_(22)主要为吸附在淀粉和蛋白质上相态不同的结合水的信号,峰T_(23)为主要被淀粉和蛋白质束缚后产生的半结合水的信号,峰T_(24)主要为种子中自由水的信号(少量源自油脂)。此外,种子即将裂壳时将形成T_(2a)(峰顶时间在10 ms左右)、T_(2b)(峰顶时间>1 000 ms)2个新信号峰,可作为预示种子萌发状态即将发生重要变化的"预兆峰"。提出的从化学组分及核磁检测原理角度对银杏种子萌发过程T_2反演谱进行解译的新途径,可为基于LF-NMR方法对种子萌发过程中化学组分变化进行活体分析提供参考。展开更多
Pore structure characteristics are important to oil and gas exploration in complex low-permeability reservoirs. Using multifractal theory and nuclear magnetic resonance (NMR), we studied the pore structure of low-pe...Pore structure characteristics are important to oil and gas exploration in complex low-permeability reservoirs. Using multifractal theory and nuclear magnetic resonance (NMR), we studied the pore structure of low-permeability sandstone rocks from the 4th Member (Es4) of the Shahejie Formation in the south slope of the Dongying Sag. We used the existing pore structure data from petrophysics, core slices, and mercury injection tests to classify the pore structure into three categories and five subcategories. Then, the T2 spectra of samples with different pore structures were interpolated, and the one- and three-dimensional fractal dimensions and the multifractal spectrum were obtained. Parameters a (intensity of singularity) andf(a) (density of distribution) were extracted from the multifractal spectra. The differences in the three fractal dimensions suggest that the pore structure types correlate with a andf(a). The results calculated based on the multifractal spectrum is consistent with that of the core slices and mercury injection. Finally, the proposed method was applied to an actual logging profile to evaluate the pore structure of low-permeability sandstone reservoirs.展开更多
To make the quantitative results of nuclear magnetic resonance(NMR) transverse relaxation(T;) spectrums reflect the type and pore structure of reservoir more directly, an unsupervised clustering method was developed t...To make the quantitative results of nuclear magnetic resonance(NMR) transverse relaxation(T;) spectrums reflect the type and pore structure of reservoir more directly, an unsupervised clustering method was developed to obtain the quantitative pore structure information from the NMR T;spectrums based on the Gaussian mixture model(GMM). Firstly, We conducted the principal component analysis on T;spectrums in order to reduce the dimension data and the dependence of the original variables. Secondly, the dimension-reduced data was fitted using the GMM probability density function, and the model parameters and optimal clustering numbers were obtained according to the expectation-maximization algorithm and the change of the Akaike information criterion. Finally, the T;spectrum features and pore structure types of different clustering groups were analyzed and compared with T;geometric mean and T;arithmetic mean. The effectiveness of the algorithm has been verified by numerical simulation and field NMR logging data. The research shows that the clustering results based on GMM method have good correlations with the shape and distribution of the T;spectrum, pore structure, and petroleum productivity, providing a new means for quantitative identification of pore structure, reservoir grading, and oil and gas productivity evaluation.展开更多
基金Supported by the China National Science and Technology Major Project(2016ZX05050)
文摘Based on analysis of NMR T2 spectral characteristics,a new method for identifying fluid properties by decomposing T2 spectrum through signal analysis has been proposed.Because T2 spectrum satisfies lognormal distribution on transverse relaxation time axis,the T2 spectrum can be decomposed into 2 to 5 independent component spectra by fitting the T2 spectrum with Gauss functions.By analyzing the free relaxation response characteristics of crude oil and formation water,the dynamic response characteristics of the core mutual drive between oil and water,the petrophysical significance of each component spectrum is clarified.T2 spectrum can be decomposed into clay bound water component spectrum,capillary bound fluid component spectrum,micropores fluid component spectrum and macropores fluid component spectrum.According to the nature of crude oil in the target area,the distribution range of T2 component spectral peaks of oil-bearing reservoir is 165-500 ms on T2 time axis.This range can be used to accurately identify fluid properties.This method has high adaptability in identifying complex oil and water layers in low porosity and permeability reservoirs.
文摘The method of regularization factor selection determines stability and accuracy of the regularization method. A formula of regularization factor was proposed by analyzing the relationship between the improved SVD and regularization method. The improved SVD algorithm and regularization method could adapt to low SNR. The regularization method is better than the improved SVD in the case that SNR is below 30 and the improved SVD is better than the regularization method when SNR is higher than 30. The regularization method with the regularization factor proposed in this paper can be better applied into low SNR (5〈SNR) NMR logging. The numerical simulations and real NMR data process results indicated that the improved SVD algorithm and regularization method could adapt to the low signal to noise ratio and reduce the amount of computation greatly. These algorithms can be applied in NMR logging.
基金Open Fund of State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation(Southwest Petroleum University)Grant Number(PLN201802).
文摘The low porosity and low permeability of tight oil reservoirs call for improvements in the current technologies for oil recovery.Traditional chemical solutions with large molecular size cannot effectively flow through the nanopores of the reservoir.In this study,the feasibility of Nanofluids has been investigated using a high pressure high temperature core-holder and nuclear magnetic resonance(NMR).The results of the experiments indicate that the specified Nanofluids can enhance the tight oil recovery significantly.The water and oil relative permeability curve shifts to the high water saturation side after Nanofluid flooding,thereby demonstrating an increase in the water wettability of the core.In the Nanofluid flooding process the oil recovery was enhanced by 15.1%,compared to waterflooding stage.The T2 spectra using the NMR show that after Nanofluid flooding,a 7.18%increment in oil recovery factor was gained in the small pores,a 4.9%increase in the middle pores,and a 0.29%increase in the large pores.These results confirm that the Nanofluids can improve the flow state in micro-sized pores inside the core and increase the ultimate oil recovery factor.
文摘为了实现致密岩心的孔隙量化表征,采用核磁共振(nuclear magnetic resonance,NMR)技术,利用T2弛豫时间和孔隙半径(r)的正比关系可测致密岩心的孔隙度、渗透率和孔径分布,利用核磁共振T2截止值可区分孔隙中的自由流体和束缚流体。从核磁共振表征岩心孔隙的原理出发,分析了核磁共振T2谱与岩心孔隙度、渗透率、孔径分布、孔隙内可动流体的关系。根据上述原理,通过实例验证了核磁共振技术在致密岩心孔隙度和渗透率量化表征中的准确性和适用性。实验岩心的T2截止值和孔径分布测试表明:1号岩心T2截止值为21.85 ms,2号岩心的T2截止值为40.11 ms;1号岩心小孔隙分量大,2号岩心孔隙分布较均匀。截止值的计算结果表明地区经验法得出的T2截止值不完全适用于该区域的致密岩心,有必要建立区域性的截止值变化范围图版。
文摘随着科学技术的发展,低场核磁共振(Low Field Nuclear Magnetic Resonance, LF-NMR)横向弛豫时间(Transverse Relaxation Time, T_2)反演谱检测技术越来越多的被应用于农业,但当前对T_2反演谱的解译尚停留在水分相态分布层面。为探索从物质成分角度对种子T_2反演谱进行解译的新方法,该研究以银杏种子为对象,利用低场核磁共振技术检测并对比银杏鲜种、种子粉末及其主要成分试样的T_2反演谱,分析各信号峰的形成机理,并以此为依据对其在种子萌发过程中的变化进行解译。研究结果表明:淀粉与蛋白质混合试样T_2反演谱的峰T_(21)、T_(22)、T_(23)以及淀粉与油脂混合试样的峰T_(24)在峰顶时间上和种子粉末试样相对应信号峰完全一致;在物质成分及配比完全相同的情况下,种子粉末试样T_2反演谱的峰T_(21)~T24的峰顶时间较鲜种分别相差12.98%、32.21%、13.02%、0%,T_(21)、T_(22)峰比例较鲜种分别偏少41.72%、29.33%,T_(23)峰比例偏多92.26%,T_(24)峰比例偏少91.71%,说明种子组织结构会对其内部水分的弛豫时间和相态分布比例造成一定影响。仅从物质成分角度考虑,种子内水分的弛豫时间主要在淀粉、蛋白质的影响下表现为T_(21)、T_(22)、T_(23),在淀粉和油脂的影响下表现为T_(24)。由此认为峰T_(21)、T_(22)主要为吸附在淀粉和蛋白质上相态不同的结合水的信号,峰T_(23)为主要被淀粉和蛋白质束缚后产生的半结合水的信号,峰T_(24)主要为种子中自由水的信号(少量源自油脂)。此外,种子即将裂壳时将形成T_(2a)(峰顶时间在10 ms左右)、T_(2b)(峰顶时间>1 000 ms)2个新信号峰,可作为预示种子萌发状态即将发生重要变化的"预兆峰"。提出的从化学组分及核磁检测原理角度对银杏种子萌发过程T_2反演谱进行解译的新途径,可为基于LF-NMR方法对种子萌发过程中化学组分变化进行活体分析提供参考。
基金supported by the National Natural Science Foundation of China(Grant No.41202110)Open Fund of State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation(Southwest Petroleum University)(Grant No.PLN201612)+1 种基金the Applied Basic Research Projects in Sichuan Province(Grant No.2015JY0200)Open Fund Project from Sichuan Key Laboratory of Natural Gas Geology(Grant No.2015trqdz07)
文摘Pore structure characteristics are important to oil and gas exploration in complex low-permeability reservoirs. Using multifractal theory and nuclear magnetic resonance (NMR), we studied the pore structure of low-permeability sandstone rocks from the 4th Member (Es4) of the Shahejie Formation in the south slope of the Dongying Sag. We used the existing pore structure data from petrophysics, core slices, and mercury injection tests to classify the pore structure into three categories and five subcategories. Then, the T2 spectra of samples with different pore structures were interpolated, and the one- and three-dimensional fractal dimensions and the multifractal spectrum were obtained. Parameters a (intensity of singularity) andf(a) (density of distribution) were extracted from the multifractal spectra. The differences in the three fractal dimensions suggest that the pore structure types correlate with a andf(a). The results calculated based on the multifractal spectrum is consistent with that of the core slices and mercury injection. Finally, the proposed method was applied to an actual logging profile to evaluate the pore structure of low-permeability sandstone reservoirs.
基金Supported by the National Natural Science Foundation of China (42174142)National Science and Technology Major Project (2017ZX05039-002)+2 种基金Operation Fund of China National Petroleum Corporation Logging Key Laboratory (2021DQ20210107-11)Fundamental Research Funds for Central Universities (19CX02006A)Major Science and Technology Project of China National Petroleum Corporation (ZD2019-183-006)。
文摘To make the quantitative results of nuclear magnetic resonance(NMR) transverse relaxation(T;) spectrums reflect the type and pore structure of reservoir more directly, an unsupervised clustering method was developed to obtain the quantitative pore structure information from the NMR T;spectrums based on the Gaussian mixture model(GMM). Firstly, We conducted the principal component analysis on T;spectrums in order to reduce the dimension data and the dependence of the original variables. Secondly, the dimension-reduced data was fitted using the GMM probability density function, and the model parameters and optimal clustering numbers were obtained according to the expectation-maximization algorithm and the change of the Akaike information criterion. Finally, the T;spectrum features and pore structure types of different clustering groups were analyzed and compared with T;geometric mean and T;arithmetic mean. The effectiveness of the algorithm has been verified by numerical simulation and field NMR logging data. The research shows that the clustering results based on GMM method have good correlations with the shape and distribution of the T;spectrum, pore structure, and petroleum productivity, providing a new means for quantitative identification of pore structure, reservoir grading, and oil and gas productivity evaluation.