T2 Distribution Research Articles

New Empirical Models for Estimating Permeability in One of Southern Iranian Carbonate Fields using NMR-Derived Features

Permeability is arguably the most important property in evaluating fluid flow in the reservoir. It is also one of the most difficult parameters to measure in field. One of the main techniques for determining permeability is the application of Nuclear Magnetic Resonance (NMR) logging across the borehole. However, available correlations in literature for estimating permeability from NMR data do not usually give acceptable accuracy in carbonate rocks. In this research, two new empirical models are introduced for quantifying NMR extracted permeability in carbonate formations. These models are validated for three carbonate formations, namely, Yamama, Gadvan, and Daryan in one of Iranian offshore reservoirs in the Persian Gulf. The first empirical model applies the pore-related NMR data such as free and bound fluid parameters. The second model, however, is a novel approach that uses the geometric features of the occurring humps in T2 distribution. For assessing the performance of the proposed models, statistical parameters as well as graphical tools are utilized. It is found that the for the examined case studies, geometric approach gives more accurate and reliable estimates compared to the available models in the literature including Timur-Coates and SDR methods.

Sandstone surface relaxivity determined by NMR T2 distribution and digital rock simulation for permeability evaluation

Many of the world's oil reservoirs are sandstones and some equations have been widely explored to estimate their permeability from NMR measurements, especially those based on the Schlumberger Doll Research (SDR) and Timur–Coates models. In both cases, the permeability is assumed to be related to pore sizes. Brownstein and Tarr showed that, under fast diffusion regime, the NMR transverse relaxation time is proportional to the pore size and the proportionality constant is defined by the interaction fluid/surface and represented by the surface relaxivity ρ. However, although there are several methods in the literature to estimate ρ, no standard methods have been established so far, to our knowledge. In this work, we estimated surface relaxivity by combining experimental and simulated NMR data using a recently developed computational method to emulate the NMR signal of fluids within Digital Rocks. In addition, we analyzed the correlation between the pore radii and the experimentally measured gas permeability. Comparing Schlumberger and Timur-Coates models for permeability prediction, we propose that the macro and microporosity intensities identified in the T2 distribution are correlated with characteristics of the sandstone surface. Thus, sandstone surface relaxivity can be estimated using the ratio of macro and microporosity intensities from NMR and, consequently, the pore size distribution can be obtained using only T2 distribution data.

A novel method to estimate resistivity index of tight sandstone reservoirs using nuclear magnetic resonance logs

The relationship between resistivity index and water saturation (I-Sw) is very important in formation evaluation via petrophysical data. Low permeability and complicated pore structure make it more difficult to determine I-Sw relationship through rock's electrical property measurements. Nuclear magnetic resonance (NMR) logs are alternative ways to obtain these key parameters. To establish a model to estimate resistivity index from NMR logs, 17 cores from the study area were selected for experiments. The helium porosity, air permeability, NMR T2 distribution, and resistivity of cores were measured. I-Sw relationship was evaluated accordingly. Given these variables, Archie formula, J function, Schlumberger-Doll-Research (SDR) model, and correlation between capillary pressure curve and T2 distribution (Pc-T2) were used to derive a novel method. It aims to calculate resistivity index from T2 time, porosity, and geometric mean of T2 time. The experimental data were applied and the corresponding model was established by multiple statistical regression method. Resistivity index is successfully predicted by T2 distribution. Then, the established model was tested by the experimental data not involved in the modeling. The validation shows that the model is highly precise. Finally, the model was applied to formation evaluation for a field case with satisfactory results. The proposed method and model provide a quantitative basis to analyze and predict resistivity index by well log data. They are of great significance for the accurate determination of oil and gas saturation of tight sandstone reservoirs.

The rock-fabric/petrophysical characteristics and classification of the micropores hosted between the calcite and dolomite crystals

For the substantial hydrocarbon potential and academic significance, focus of interest has been directed towards the microporous carbonate. Compared with the documented shallow burial microporous carbonate, carbonate with a depth deeper than 6000 m present, of course, different characteristics due to the long-term influences of the strong cementation and compaction. With the deepening of exploration, it is therefore essential to improve the understanding about the deep burial microporous carbonate. In this paper, an integrated petrographic and petrophysical approach, which combines thin section, high-resolution field emission scanning electron microscopy (FESEM) observations, and nuclear magnetic resonance (NMR) measurements, is chosen to study the deep to ultradeep carbonate in the Shunnan area, Tarim Basin, NW China.Results show that all the studied carbonate samples consist entirely of micropores with a radius less than 10 μm, belonging to the strictly microporous carbonate. These micropores exist between the calcite and dolomite microcrystals. To reliably calculate the permeability based on NMR data, a newly introduced factor P aiming to adjust the T2 cut-off value derived from the relaxation curve is applied to enhance the Coates model. Values of P are found to correlate well with the FFI (free fluid index) of the bioclastic and bioclasts-free detrital limestones through different quantitative relationships, respectively. Permeabilities calculated from the modified Coates model are in good agreements with those measured by the pulse-decay method (R2 = 0.93, 0.67). Considering the existing classifications of pore systems are not applicable to the peculiar intercrystalline micropores within the deep burial microporous carbonate, a noval classification scheme is thus explored by integrating the rock-fabric and petrophysical properties. Micropores hosted within the subhedral to anhedral microcrystals with distinct boundaries are the main reserving space of the microbial lime-/dolostone, which lead to relatively higher porosities (averaging 3.41%) than the detrital limestone (1.99%) and dolostone (2.47%), and an identical right-skewed trimodal NMR T2 distribution. Micropores related with the coalescent polyhedral to anhedral microcrystals, that are always glued together to form fusing boundaries, are mainly located within the micrite matrix and allochem of the detrital limestone. Certain relationships among porosity, permeability and FFI/BVI also exist for the bioclastic and bioclasts-free detrital limestones, respectively. Micropores within the dolostone exist between the rhombic dolomite crystals. This proposed classification of micropores comprehensively reflects the depositional, diagenetic textures and physical properties of the deep burial microporous carbonate. The particularity of microbial lime-/dolostone is highlighted.

Inverse Laplace transform and multiexponential fitting analysis of T2 relaxometry data: a phantom study with aqueous and fat containing samples

BackgroundThe inverse Laplace transform (ILT) is the most widely used method for T2 relaxometry data analysis. This study examines the qualitative agreement of ILT and a proposed multiexponential (Mexp method) regarding the number of T2 components. We performed a feasibility study for the voxelwise characterisation of heterogeneous tissue with T2 relaxometry.MethodsEleven samples of aqueous, fatty and mixed composition were analysed using ILT and Mexp. The phantom was imaged using a 1.5-T system with a single slice T2 relaxometry 25-echo Carr-Purcell-Meiboom-Gill sequence in order to obtain the T2 decay curve with 25 equidistant echo times. The adjusted R2 goodness of fit criterion was used to determine the number of T2 components using the Mexp method on a voxel-based analysis. Comparison of mean and standard deviation of T2 values for both methods was performed by fitting a Gaussian function to the ILT resulting vector.ResultsPhantom results showed pure monoexponential decay for acetone and water and pure biexponential behaviour for corn oil, egg yolk, and 35% fat milk cream, while mixtures of egg whites and yolks as well as milk creams with 12–20% fatty composition exhibit mixed monoexponential and biexponential behaviour at different fractions. The number of T2 components by the Mexp method was compared to the ILT-derived spectrum as ground truth.ConclusionsMexp analysis with the adjusted R2 criterion can be used for the detection of the T2 distribution of aqueous, fatty and mixed samples with the added advantage of voxelwise mapping.

Integration of NMR and Conventional Logs for Vuggy Facies Classification in the Arbuckle Formation: A Machine Learning Approach

Summary Diagenetic effects in carbonate rocks can enhance or occlude depositional pore space. Reliable identification of porosity-enhancing diagenetic features (e.g., vugs and fractures) is essential for petrophysical characterization of reservoir properties (e.g., porosity and permeability), construction of geological and reservoir models, reserve estimation, and production forecasting. Challenges remain in characterizing these diagenetic features from well logs as they are often mixed with variations in mineral and fluid concentrations. Herein, we explore a data-driven approach that is based on a comprehensive well log data set from the Arbuckle Formation in Kansas to classify vuggy facies in carbonate rocks. The available well log data include conventional logs (gamma ray (GRTC), resistivity (RT), neutron/density porosity (NPHI/RHOB), photoelectric factor (PE), and acoustic slowness) and nuclear magnetic resonance (NMR) transverse relaxation time (T2) logs. We parameterized the measured T2 distribution using a multimodal lognormal Gaussian density function and combined the resulting Gaussian parameters with conventional logs as inputs into three supervised machine learning (ML) algorithms; namely, support vector machine (SVM), random forest (RF), and artificial neural network (ANN). The facies labeling data used in this study were based on visual examination of vug sizes from core samples, which include five classes; namely, nonvuggy, pinpoint-size, centimeter-size, fist-size, and super-vuggy. In total, 80% of the data set was used as the training set, and a fivefold cross validation was used for hyperparameter tuning. We conducted a detailed comparison of the above three ML algorithms on the basis of different combinations of features. The highest classification accuracy achieved on the holdout testing set is 84% using SVM on a combination of conventional logs and selected NMR Gaussian parameters as inputs. In general, inclusion of conventional log data improves the prediction accuracy compared with using NMR data alone. Feature selection improves the performance for SVM and ANN but is not recommended for RF.

Wettability Quantification in Mixed-Wet Rocks Using a New NMR-Based Method

Summary Nuclear magnetic resonance (NMR) measurements have been attractive options for wettability characterization of reservoir rocks as they are sensitive to the type of fluid in contact with the grain surface. Several NMR-based wettability indices are documented in previous publications. Most of these methods require extensive calibration or involve complex inversion algorithms, which makes them computationally expensive and complicates their applicability in mixed-wet multimodal rocks. In this paper, we introduce a new NMR-based wettability index and verify its reliability in pore-scale and core-scale domains using numerical simulations and experimental measurements, respectively. This new index requires calibration at fully water-saturated water-wet and fully hydrocarbon-saturated hydrocarbon-wet states and can be applied to mixed-wet rocks at any fluid saturation level. This new NMR-based wettability index is a function of the transverse magnetization (T2) of mixed-wet rocks, the bulk relaxivity and saturation of each fluid, and the T2 distributions for fully water-wet and hydrocarbon-wet samples of the same rock type. The reliability of the new index was first tested in the pore-scale domain. For this part, we selected several pore-scale microcomputed tomography (CT) images of carbonate and sandstone rocks. We used a previously developed finite volume simulator to model the T2 responses in these images at fully water-wet and fully hydrocarbon-wet wettability states. Then we generated synthetic partially saturated mixed-wet samples and simulated T2 responses in these synthetic images. We used the simulated T2 results for determining their NMR-based wettability index and verified its applicability in the pore-scale domain. Next, we tested the reliability of the new NMR-based wettability index in the core-scale domain using NMR measurements in four Texas Cream (TC) rock samples, obtained from the Edwards formation. We altered the wettability of the cores to be water-, hydrocarbon-, and mixed-wet by injecting brine, a naphthenic acid in decane solution, or an anionic surfactant solution. We quantified the wettability of these samples using the Amott-Harvey (AH) index and contact angle measurements. Next, we measured the T2 distribution of these samples at different fluid saturation levels. Finally, we quantified the wettability values of these core samples using the new NMR-based index and compared them to those obtained from the AH index and contact angle measurements. We documented successful verification of the proposed method on samples with wettability ranging from −0.90 to 0.98 and from −0.6 to 0.5 (independently quantified using the AH method) in the pore- and core-scale domains, respectively. Results demonstrated that the new NMR-based wettability index reliably estimates the wettability of mixed-wet rocks in a wide range of wettability states. The new wettability index can potentially improve the speed and reliability of NMR-based wettability characterization and is promising for log-scale wettability assessment in mixed-wet rocks.

The Effect of Clay Content on the Spin-Spin NMR Relaxation Time Measured in Porous Media.

Clays, hydrous aluminous phyllosilicates, have a significant impact on the interpretation of physical measurements and properties of porous media. In particular, the presence of paramagnetic and/or ferromagnetic ions like iron, nickel, and magnesium in clays can complicate the analysis of nuclear magnetic resonance (NMR) data for porous media characterization. This is due to the internal magnetic field gradient induced by the clay minerals. In this study, we aim to investigate the impact of clay content on spin–spin relaxation time (T2), which is strongly influenced by the pore surface chemistry. Seven rock core plugs, characterized with variable clay content, were used for this purpose. The clay mineralogy and volume were determined by means of quantitative evaluation of minerals by scanning electron microscopy (QEMSCAN). The T2 relaxation time was measured using a Carr–Purcell–Meiboom–Gill (CPMG) sequence with variable echo spacing (TE). The maximum percentage difference in dominant T2 values (MRDT2) between shortest and longest echo spacing was subsequently correlated with clay content obtained from QEMSCAN. Our results show that the reduction in T2 distribution with increasing echo time TE is more significant in samples characterized by higher clay contents. The MRDT2 was found to be strongly correlated with clay content. An analytical equation is presented expressing MRDT2 as a function of clay content providing a quick and non-destructive approach for clay content estimation. Moreover, the MRDT2–clay content relationship showed a nonlinear behavior: MRDT2 increases drastically as the clay content increases up to 15%, beyond which the rate of MRDT2 change with clay content diminishes. This behavior could be attributed to the clay distribution. At higher clay contents (above 15%), it is more likely for clay to form clusters (structural clays), which will not significantly increase the clay surface in contact with the pore fluid. Further, experimental data suggests that ignoring the impact of clay on internal magnetic gradients and T2 signal may result in considerable underestimation of the actual pore size distribution.

Experimental investigation on T2 cutoffs of tight sandstones: Comparisons between outcrop and reservoir cores

T2 cutoff is a key representative parameter of rock pore structure, which can reflect the degree of mobile fluid as a function of variable water saturation controlled by the extent of centrifuging. However, few studies of T2 cutoff have been done on tight sandstones. In this study, residual fluid of samples after a series of centrifuges were scanned by NMR to determine T2 cutoffs (the relaxation time separating mobile from immobile water) and the extent of mobile fluid as a function of variable water saturation controlled by the extent of centrifuging. Results indicate that all reservoir cores exhibit bimodal NMR T2 distributions, while outcrop cores mainly show unimodal NMR T2 distributions. Tight sandstones showlittle or no mobile fluid controlled by pore throats with radii ≥1 μm, including outcrops and reservoir samples. In conclusion, T2 cutoffs of cores with bimodal NMR T2 distributions and the ones with unimodal NMR T2 distributions were obtained,respectively,at 418 psi and 208 psi, while the former cores exhibit larger T2 cutoffs than the later ones. The critical mobile pore radius for outcrop samples exhibiting a unimodal spectral NMR T2 distribution is 100 nm, whereas the critical pore radius of 50 nm is identified for reservoir samples which display a bimodal T2 distribution. T2gm (The geometric means of T2 fluid distribution at 100% saturation) may propagate error when applying the Schlumberger Doll Research (SDR) model to tight sandstones, whereas T2wa (the weighted average NMR T2 values for the mobile fluid distribution) shows promise as a parameter to predict pore connectivity.

Pore structure alteration induced by CO2–brine–rock interaction during CO2 energetic fracturing in tight oil reservoirs

CO2 energetic fracturing is an important technique for developing tight oil resources by creating complex fractures and enhancing formation pressure. The physical properties of host rocks may be changed by CO2–brine–rock interaction in the soaking stage of CO2 energetic fracturing. However, the pore structure alteration behavior and mechanism during CO2 energetic fracturing are still unclear. To address this problem, this work conducted static soaking experiment under reservoir temperature-pressure conditions and employed multiple techniques to comprehensively characterize the pore structure. The results show that CO2–brine–rock interaction generated many large pores (10–50 μm) due to the dissolutions of carbonate and feldspar, numerous tiny intragranular pores (1–6 μm) and some microfractures in clays. The T2 distribution could be applied to characterize the pore size distribution of tight sandstones when the pores saturated with brine. Some secondary clay particles and debris dispersed into the brine caused by CO2–brine–rock interaction. These particles may block extremely small pore throats during flowing back. These blockages weakened the exchange between the small and the large pores, characterized by single-peak and insignificant three-peak T2 distributions transformed into apparent dual-peak T2 distributions. After soaking the rock with CO2-saturated brine for 168 h at 20 MPa and 80 °C, the maximum pore throat radius increased four-fold, and the average pore throat radius increased by 86.5% from 0.089 μm to 0.166 μm, indicating a significant increase in the pore connectivity. Increasing the soaking pressure or CO2 concentration can transform small pores into larger pores and can open bedding planes significantly, thus increasing the porosity and permeability of tight sandstones.

Effect of Mineral Composition on Transverse Relaxation Time Distributions and MR Imaging of Tight Rocks from Offshore Ireland

In this paper, we investigate the effect of magnetic field strength on the transverse relaxation time constant (T2) in six distinct core plugs from four different rock types (three sandstones, one basalt, one volcanic tuff and one siltstone), retrieved from offshore Ireland. The CPMG pulse-sequence was used at two different magnetic field strengths: high-field at 4.70 T and low-field at 0.28 T. Axial images of the core plugs were also acquired with the RAREst sequence at high magnetic field strength. Thin-sections of the core plugs were prepared for optical imaging and SEM analysis, and provided qualitative information on the porosity and quantification of the elemental composition of the rock material. The content of iron varied from 4 wt. % to close to zero in the rock samples. Nevertheless, the effective T2 distributions obtained at low-field were used to successfully predict the porosity of the core plugs. Severe signal attenuations from internal magnetic gradients resulted in an underestimation of the porosity at high-field. No definitive trend was identified on the evolution of discrete relaxation time components between magnetic field strengths. The low-field measurements demonstrate that NMR is a powerful quantitative tool for petrophysical rock analysis as compared to thin-section analysis. The results of this study are of interest to the research community who characterizes natural gas hydrates in tight heterogeneous core plugs, and who typically relies on MR imaging to distinguish between solid hydrates and fluid phases. It further exemplifies the importance of selecting appropriate magnetic field strengths when employing NMR/MRI for porosity calculation in tight rock.

Non-negative least squares computation for in vivo myelin mapping using simulated multi-echo spin-echo T2 decay data.

Multi-compartment T2 mapping has gained particular relevance for the study of myelin water in the brain. As a facilitator of rapid saltatory axonal signal transmission, myelin is a cornerstone indicator of white matter development and function. Regularized non-negative least squares fitting of multi-echo T2 data has been widely employed for the computation of the myelin water fraction (MWF), and the obtained MWF maps have been histopathologically validated. MWF measurements depend upon the quality of the data acquisition, B1+ homogeneity and a range of fitting parameters. In this special issue article, we discuss the relevance of these factors for the accurate computation of multi-compartment T2 and MWF maps. We generated multi-echo spin-echo T2 decay curves following the Carr-Purcell-Meiboom-Gill approach for various myelin concentrations and myelin T2 scenarios by simulating the evolution of the magnetization vector between echoes based on the Bloch equations. We demonstrated that noise and imperfect refocusing flip angles yield systematic underestimations in MWF and intra-/extracellular water geometric mean T2 (gmT2 ). MWF estimates were more stable than myelin water gmT2 time across different settings of the T2 analysis. We observed that the lower limit of the T2 distribution grid should be slightly shorter than TE1 . Both TE1 and the acquisition echo spacing also have to be sufficiently short to capture the rapidly decaying myelin water T2 signal. Among all parameters of interest, the estimated MWF and intra-/extracellular water gmT2 differed by approximately 0.13-4 percentage points and 3-4 ms, respectively, from the true values, with larger deviations observed in the presence of greater B1+ inhomogeneities and at lower signal-to-noise ratio. Tailoring acquisition strategies may allow us to better characterize the T2 distribution, including the myelin water, in vivo.

Nuclear Magnetic Resonance (NMR) mapping of remaining oil distribution during sequential rate waterflooding processes for improving oil recovery

At the conclusion of waterflooding phase, significant volume of oil still remains in reservoir formations. In this paper, waterflooding was performed at a designed sequential rate mode with an aim to further reduce the remaining oil saturation (Sor). Waterflooding process was monitored continuously by a low-field Nuclear Magnetic Resonance (NMR) spectrometer attempting to map pore-scale displacing behaviors and also quantify the reduction in Sorin-situ. The results showed that the main pore size of the cores ranged from 1.6 μm to 63.0 μm inferred by T2 (transverse relaxation time) distributions. The value of Sor in the cores increased towards the outlet face during waterflooding because of capillary end effect, which became more significant for heavy oil. At the termination of this waterflooding process, Sor was found to be further reduced by approximately 5.0% in the presence of thief water pathways as a result of the improved viscous forces. Water fingering and capillary imbibition effects were clearly visualized in the NMR images. These observations are expected to be useful for heavy oil waterflooding operations especially in post-breakthrough phase.

Interactions between cadmium and multiple precipitates in an Al-Li-Cu alloy: Improving aging kinetics and precipitation hardening

This work demonstrates significant improvements in both the aging kinetics and precipitation hardening of an Al-Li-Cu alloy with the minor addition of Cd (0.06 at.%). The precipitation hardening effect of T1 precipitates in casting Al-Li-Cu alloys has long been ignored since it is difficult to achieve a high number density of fine precipitates without a large number of dislocations. A detailed transmission electron microscopy investigation shows that the Cd addition has changed the distribution of T1 precipitates from the conventional uneven distribution near dislocations or grain boundaries to a more homogeneous manner. Most of the Cd-rich nanoparticles were observed at the broad face and/or terminal of the T1 platelets. It is highly likely that these nanoparticles act as heterogeneous nucleation sites, which consequently leads to a higher number density of T1 precipitates. Moreover, Cd atoms were preferentially segregated within δ′ precipitates, which can be attributed to the strong bonding between Li and Cd. The interactions between Cd and the T1 (Al2CuLi) and δ′ (Al3Li) precipitates in Al-Li-Cu alloy are first reported. The present study may propose a new mechanism to effectively improve precipitation kinetics and therefore the age-hardening effect of Al-Li-Cu alloys.

Characterization of moisture states and transport in MUF resin-impregnated poplar wood using low field nuclear magnetic resonance

In this study, the spin–spin relaxation time (T2) distributions of free water and bound water, as well as the moisture content (MC) profiles of MUF resin-impregnated poplar wood (Populous tomentosa) sample (RI) were investigated by low-field nuclear magnetic resonance, with the aim of providing insights into how MUF resin impregnation affects the moisture states and moisture transport in modified poplar wood during drying. The T2 curves demonstrated that the resin treatment did not increase the number of peaks in the T2 distributions, but affected the T2 value as compared to the control. Above the fiber saturation point (FSP), the T22 (corresponds to the free water in wood rays and wood fibers) of the RI sample exhibited an increase compared to the control, while the T23 (corresponds to the free water in the vessels) was almost unchanged. Below the FSP, a shorter T21 (corresponding to the bound water) of the RI sample was observed compared to the control. The drying curves and MC profiles indicated a significant difference in the moisture transport in the RI sample as compared to the control. The gradually cured resin system in the wood surface layer during drying provided a barrier for the transfer of water in the center layer toward to the surface, causing the resin curing reactions in the surface and core layers to be out of sync. Therefore, a more significant MC gradient was observed for the resin-impregnated sample.

Study on the Effects of Heterogeneous Distribution of Methane Hydrate on Permeability of Porous Media Using Low‐Field NMR Technique

AbstractThe permeability of sediments is an important parameter that effects flow characteristics of the gas and water in the process of natural gas hydrates development. The distribution of gas hydrate is generally heterogeneous in porous media. It poses a great challenge to the permeability measurement of hydrate‐bearing sediments. To study the effect of heterogeneous distribution of methane hydrate on the permeability of porous media, methane hydrate formation in the sandstone and permeability measurement was carried out using a low‐field nuclear magnetic resonance (NMR) measurement system in situ conditions. The spatial distribution of methane hydrate in the core samples was determined by combining the T2 distribution with magnetic resonance imaging. The results show that the distribution of methane hydrate is heterogeneous in the core samples. The temporal and spatial variation of permeability happens in the process of hydrate dissociation. The heterogeneity of methane hydrate distribution severely affects the analysis of permeability change. Considering the heterogeneity of methane hydrate distribution, a new method was proposed to obtain the quantitative relationship between hydrate saturation and relative permeability based on magnetic resonance imaging and the equivalent seepage capacity method. The results show that the relative permeability models obtained by this method agree better with experimental results. The optimum coefficients of relative permeability models obtained by equivalent seepage capacity method change significantly in contrast with the direct fitting method. The variation of the optimum coefficient is up to 300% in this study. The model coefficients are related to the pore characteristic of hydrate‐free porous media.

Nuclear Magnetic Resonance Characterization of Petrophysical Properties in Tight Sandstone Reservoirs

AbstractPermeability and bound water saturation (Swb) are key parameters reflecting the petrophysical properties of porous rocks. Nuclear magnetic resonance (NMR) has proved to be effective in investigating the properties of porous media. However, estimating Swb and the permeability in tight sandstone reservoirs based on conventional NMR methods, which requires the inversion of NMR echo data to obtain the transverse relaxation time (T2) distribution, proves to be a challenging task. In this study, a method is proposed to estimate Swb and the permeability in tight sandstone reservoirs based on the direct analysis of NMR echo data, thus avoiding the inversion process. A total of 20 tight sandstone samples from the Ordos Basin in China was taken for laboratory NMR measurements. The kernel function of the echo data was used to characterize the ratio distribution of bound water volume to pore volume for different pore sizes. Following this, an echo data calibration method was applied to estimate Swb without the inversion of the T2 distribution, and the window method was used to reduce the impact of noise in the echo data. Furthermore, models for estimating permeability were proposed based on the determined windows of the NMR echo data in the Swb estimation. The reliability of the proposed method for estimating Swb and permeability was verified by comparing the estimated and experimental results. Our study provides an efficient method for the estimation of petrophysical parameters in porous rocks based on the direct analysis of NMR echo data.

Hydrocarbon saturation in shale oil reservoirs by inversion of dielectric dispersion logs

Hydrocarbon saturation is an important petrophysical parameter in reservoir evaluation and reserve calculation. Dielectric dispersion logs have been widely used to estimate the hydrocarbon saturation, especially in high salinity shale formations. However, there is still room to improve the accuracy of interpretation of dielectric dispersion logs. In this paper, we used two interpretation models combined four dielectric permittivity and four conductivity logs measured by Array Dielectric Tool (ADT) at four frequencies to predict the hydrocarbon saturation in shale oil reservoirs, Triassic Yanchang Formation, Ordos Basin, China. The logs measured at the highest frequency are interpreted by the Complex Refractive Index (CRIM) model. And the other three frequencies measured logs are processed by the shaly sandstone (SHSD) model. Based on the two models, simulated annealing algorithm is selected to calculate water saturation and rock textual parameter, the dispersive phase fraction, and water salinity. Besides, accurate porosity, dielectric permittivity of rock matrix, and temperature are input information to the proposed method. The proposed method is applied to shale oil reservoirs of Triassic Yanchang Formation in two wells. The effectiveness and reliability of proposed model is verified by synthetic log responses. The mean relative error between synthetic and field logs is small. The predicted hydrocarbon saturation is consistent with core data, and its variation is consistent with characteristics of NMR T2 distributions, verifying the accuracy and reliability of proposed method and inversion results. Our estimated hydrocarbon saturation of the two wells is about 30%, showing a good oil generation potential of the studied shale oil reservoirs.

A study of pine resin in softwood by 1D and 2D time-domain NMR

Abstract Time-domain nuclear magnetic resonance (TD-NMR) is widely used in the investigation of wood-water relationship. However, some ambiguities between the NMR signals and the components in wood remain unresolved, particularly the effect of pine resin on NMR signals. To clarify these ambiguities and increase the use of TD-NMR in wood research, different sample treatment methods were studied, including air-drying, low-temperature vacuum-drying, diethyl ether extraction and moisture isothermal adsorption. The corresponding one-dimensional (1D) T1, T2 and two-dimensional (2D) T1-T2 correlation relaxation time distributions of radiata pine and Douglas fir samples were investigated. The NMR signals accounted for “longer relaxation-time components” below the fiber saturation point (FSP), but overlaped in parts of the 1D relaxation time distributions making it difficult to distinguish between pine resin and moisture. The 2D T1-T2 correlation relaxation time distributions produced a better distinction between pine resin and bound water. This distinction established a quantitative relationship between pine resin, moisture and 2D NMR signal amplitudes.

Glutathione S-transferase T1 and M1 null genotype distribution among non-alcoholic fatty liver disease patients and its association with cytokine and adipokine profiles

Aim of the studyAmong the key genes involved in the development of non-alcoholic fatty liver disease (NAFLD) are genes encoding the synthesis of glutathione S-transferase (GST).Material and methodsDeletion polymorphism of GSTT1 and GSTM1 genes was investigated in 104 NAFLD patients and 45 healthy individuals. Biochemical blood analysis, tumor necrosis factor-α (TNF-α), interleukin-10, leptin and adiponectin plasma levels were studied.ResultsThe distribution of deletion vs. non-deletion genotypes of the GSTT1 gene in NAFLD patients was 18 (17.3%) vs. 86 (82.7%) patients and in healthy people it was 6 (13.3%) vs. 39 (86.7%) individuals. The genotype distribution of the GSTM1 gene was as follows: 52 (50.0%) NAFLD patients had null genotype vs. 52 patients (50.0%) with non-deletion genotype; in the control group – 23 (51.1%) vs. 22 (48.9%) individuals. Deletion of the GSTT1 gene in NAFLD patients was associated with twice as high (p = 0.01) TNF-α level in the blood as compared to patients with normal genotype. Higher concentration of leptin in blood by 37.1% (p = 0.04) was observed in patients with null genotype of the GSTM1 gene, as compared to those with normal genotype.ConclusionsDeletion polymorphism of GSTT1 and GSTM1 genes distribution among NAFLD patients did not differ as compared to healthy individuals. Null-genotype GSTT1 gene carriers were characterized by higher TNF-α concentration and null-genotype GSTM1 gene carriers were characterized by elevated leptin level as compared to normal genotype carriers.