Study on algorithms of low SNR inversion of T_2 spectrum in NMR

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.

Nuclear magnetic resonance T_2 spectrum:multifractal characteristics and pore structure evaluation

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.

A decomposition method of nuclear magnetic resonance T2 spectrum for identifying fluid properties

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.

An Experimental Study on the Effect of a Nanofluid on Oil-Water Relative Permeability

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.

An algorithm for multi-exponential inversion of T_2 spectrum in nuclear magnetic resonance

NMR logging can provide the permeability parameter and abundant stratigraphical information such as total porosity,oil,gas and water saturation,oil viscosity,etc. And these physical parameters can be obtained by T2 spectrum inversion. NMR inversion is an important part in logging interpretation. The authors describe a multi-exponential inversion algorithm,solid iteration redress technique( SIRT),and apply the algorithm in real data and compare the results with those based on singular value decomposition( SVD). It shows that SIRT algorithm is easier to be understood and implemented,and the time spent in SIRT is much shorter than that of SVD algorithm. And the non-negative property of T2 spectrum is much easier to be implemented. It can match the results based on SVD very well. SIRT algorithm can be used in T2 spectrum inversion for NMR analysis.

An unsupervised clustering method for nuclear magnetic resonance transverse relaxation spectrums based on the Gaussian mixture model and its application

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.

瓦斯压力对低透性煤吸附-解吸特性及孔隙分布的影响

为了从微观的角度探究瓦斯压力对深部低透性煤层吸附-解吸特性及孔隙分布的影响,采用低磁场核磁共振技术(NMR),开展深部低透性煤不同瓦斯压力下的吸附-解吸试验。试验发现:瓦斯吸附态、游离态和自由态下,T_(2)谱幅值积分与瓦斯压力呈现较好的线性关系,其拟合结果R^(2)均大于0.973 48,微观自由态瓦斯在瓦斯压力等于3.739 MPa处瓦斯的吸附-解吸出现了迟滞效应。不同瓦斯压力下,孔径类型分布差距较大,煤样内部孔隙分布主要是小孔占据大部分,而中孔和大孔所占比列较小。研究结果对深部低透性煤矿资源开采具有一定的指导意义。

Meso-damage evolution and mechanical characteristics of low-porosity sedimentary rocks under uniaxial compression

Low pore sedimentary rocks(from Guangxi, China) were subjected to uniaxial compression loading experiment under different initial stresses. The rock samples were investigated by nuclear magnetic resonance before and after the loading. The relationships between the mesoscopic rock damage and macroscopic mechanical parameters were established, and the initial damage stress of the low-porosity sedimentary rock was determined. The results showed that this type of rock has the initial stress of damage. When the initial loading stress is lower than the initial stress of damage, the T2 spectrum area of the rock sample gradually decreases, and the primary pores of the rock are further closed under the stress. The range of the initial stress of damage for this type of rock is 8-16 MPa. When the loading stress exceeds the initial stress of damage, the T2 spectrum area gradually increases, indicating that the porosity of the rock increases and microscopic damage of the rock appears. The rock damage degree is defined, and the nonlinear function between the rock damage degree and the initial loading stress is established.

基于核磁共振的页岩孔隙结构特征研究

页岩储层普遍存在低孔低渗的特点,微-纳孔喉及微裂缝发育,其储层孔隙结构表征及物性评价具有较大难度。为了实现页岩储层快速评价和孔隙结构表征,应用核磁共振技术开展了页岩孔隙结构特征研究。结果表明:1)通过对页岩岩心核磁T_(2)谱分析,将页岩划分为单峰-丘型、单峰-尖峰型、双峰-左高型、双峰-右高型、多峰-基质型和多峰-裂缝型。其中单峰型页岩孔隙分布较为集中,双峰型次之,多峰型页岩孔隙分布复杂,且可能包含裂缝等流体赋存空间。2)建立了储层中干酪根等固体有机质、黏土束缚流体、毛管束缚流体、技术可动流体及自由可动流体识别与评价方法,并通过与Qemscan扫描结果对比,明确了T_(2)与页岩孔径换算系数为5.3 nm/ms。3)将页岩岩心T_(2)谱分为固定区间(P_(1))、束缚区间(P_(2))和自由可动区间(P_(3))3个区间,其中P_(1)区间累积信号量与渗透率呈负相关关系,P_(2)区间与P_(3)区间累积信号与渗透率呈现正相关关系。以上成果认识对页岩油气藏勘探与开发具有重要意义。

基于核磁共振实验的低渗透砂岩岩电参数分类及应用——以东营凹陷南坡沙四段为例

低渗透砂岩储层孔隙结构复杂,储层有效性识别及饱和度准确计算难度较大.笔者以东营凹陷南坡沙四段(Es4)低渗透砂岩为研究对象,根据压汞、物性、薄片及核磁等资料,将研究区孔隙结构分为三大类、五小类.在岩样孔隙结构分类基础上,明确了孔隙结构类型与岩电参数之间存在确定的关系,而核磁共振T2谱定量特征参数在一定程度上能够表征孔隙结构类型及其细节信息,通过提取T2谱中T2几何平均值(T2g)、T2均值(2)、峰度(KG)、可动流体分量(Smf)及区间孔隙分量等孔隙结构参数,建立了基于核磁T2谱特征参数的孔隙结构识别图版,显示核磁T2谱孔隙结构参数对不同类型的储层有较好的识别效果,进而探讨核磁孔隙结构参数和岩电参数之间的关系,结果表明,T2谱峰度值与孔隙胶结指数(m)值相关性较高,进一步确定了岩电参数m的核磁计算公式.最终,将该套方法应用于研究区井筒剖面中,有效地提高了饱和度计算精度,也为东营凹陷南坡低渗透砂岩油藏储量估算与高效开发提供了依据.

核磁共振测井评价水淹层方法的研究及应用

针对常规测井方法在评价水淹层方面存在的问题 ,分析研究了油层、水层、水淹层在核磁共振测井的标准T2 谱、移谱、差谱上响应特征的差异 ,提出了利用核磁共振测井水淹层响应特征定性识别水淹层的方法 ;在对不同类型的水淹层综合分析的基础上提出了不同的定量评价方法 ,对于中等粘度油的水淹层 ,采用加强扩散移谱法定量确定水淹层的剩余油饱和度 ;对于稠油水淹层 ,采用加强扩散移谱差分谱法定量确定水淹层可动水饱和度。通过定性、定量方法在实际生产中的应用总结出了优化的水淹层核磁共振测井观测模式 ,强调了加强移谱测井是水淹层核磁共振测井中一个必不可少的观测模式。实例分析说明了该方法在实际应用中的有效性和实用性。

红外-核磁共振光谱-免疫亲和柱法解析梨孢镰孢菌代谢产物成分

利用红外光谱,核磁共振光谱结合免疫亲和柱的方法解析梨孢镰孢菌代谢产物成分,为真菌代谢产物的分析提供新的信息。将F.poae菌株在GYM培养基上25℃条件下培养12 h后转至8℃培养12 h,交替进行4周,将其代谢产物分离纯化、结晶,80℃干燥后用红外光谱仪分析产物结构,然后利用免疫亲和柱特异性,比较产物经T-2免疫亲和柱纯化前后的1H核磁谱图。由红外谱图可判断目标组分存在与单端孢霉烯族毒素相同的特征官能团,初步判定产物为单端孢霉烯族毒素。通过1H核磁谱图比较T-2免疫亲和柱纯化前后物质结构一致。梨孢镰孢菌代谢产物成分为T-2毒素。红外-核磁共振光谱结合免疫亲和柱的方法解析梨孢镰孢菌代谢产物的方法在国内外尚未见报道。

核磁共振敏感参数在低对比度油层识别中的应用

鄂尔多斯盆地姬塬地区延长组长×储层为低对比度油层,油水关系复杂,矿化度较低且变化大,发育大量高电阻率水层,常规油水识别难,解释符合率较低。通过储层特征与油水识别难点分析,在岩石物理实验的基础上,明确核磁共振T2谱形态特征的主要影响因素,提出了基于核磁共振T2谱的半幅点偏移量、离散度、右翼展幅、拖尾面积等多个反映流体性质的敏感参数。综合应用敏感参数加权组合,建立了基于核磁共振敏感参数的油水定量识别标准。应用于20口井,解释符合率明显提升,形成了阵列感应+核磁共振测井系列,解决了低对比度油层的识别问题,取得良好地质应用效果。

A Novel Model of Predicting Archie's Cementation Factor from Nuclear Magnetic Resonance(NMR) Logs in Low Permeability Reservoirs

The resistivity experimental measurements of core samples drilled from low permeability reservoirs of Ordos Basin, Northwest China, illustrate that the cementation factors are not agminate, but vary from 1.335 to 1.749. This leads to a challenge for the estimation of water and hydrocarbon sa- turation. Based on the analysis of Purcell equation and assumption that rock resistivity is determined by the parallel connection of numerous capillary resistances, a theoretical expression of cementation factor in terms of porosity and permeability is established. Then, cementation factor can be calculated if the parameters of porosity and permeability are determined. In the field application, porosity can be easily obtained by conventional logs. However, it is a tough challenge to estimate permeability due to the strong heterogeneity of low permeability reservoirs. Thus, the Schlumberger Doll Research （SDR） model derived from NMR logs has been proposed to estimate permeability. Based on the analysis of the theoretical expressions of cementation factor and SDR model, a novel cementation factor prediction model, which is relevant to porosity and logarithmic mean of NMR T2 spectrum （T21m）, is derived. The advantage of this model is that all the input information can be acquired from NMR logs accurately. In order to confirm the credibility of the novel model, the resistivity and corresponding laboratory NMR measurements of 27 core samples are conducted. The credibility of the model is confirmed by compar- ing the predicted cementation factors with the core analyzed results. The absolute errors for all core samples are lower than 0.071. Once this model is extended to field application, the accuracy of water and hydrocarbon saturation estimation will be significantly improved.

A New Empirical Method for Constructing Capillary Pressure Curves from Conventional Logs in Low-Permeability Sandstones

Pore structure reflected from capillary pressure curves plays an important role in low-permeability formation evaluation. It is a common way to construct capillary pressure curves by Nuclear Magnetic Resonance（NMR） log. However, the method＇s efficiency will be severely affected if there is no NMR log data or it cannot reflect pore structure well. Therefore, on the basis of J function and diagenetic facies classification, a new empirical model for constructing capillary pressure curves from conventional logs is proposed here as a solution to the problem. This model includes porosity and the relative value of natural gamma rays as independent variables and the saturation of mercury injection as a dependent variable. According to the 51 core experimental data sets of three diagenetic facies from the bottom of the Upper Triassic in the western Ordos Basin, China, the model＇s parameters in each diagenetic facies are calibrated. Both self-checking and extrapolation tests show a positive effect, which demonstrates the high reliability of the proposed capillary pressure curve construction model. Based on the constructed capillary pressure curves, NMR T_2 spectra under fully brine-saturated conditions are mapped by a piecewise power function. A field study is then presented. Agreement can be seen between the mapped NMR T_2 spectra and the MRIL-Plog data in the location of the major peak, right boundary, distribution characteristics and T_2 logarithmic mean value. In addition, the capillary pressure curve construction model proposed in this paper is not affected by special log data or formation condition. It is of great importance in evaluating pore structure, predicting oil production and identifying oil layers through NMR log data in low-permeability sandstones.