T2 Distribution Research Articles

Experimental Study on Fluid Dissipation Effects in Core Samples by NMR Measurement

Laboratory core nuclear magnetic resonance (NMR) relaxation measurements offer geological information, including rock porosity and oil saturation, relevant to logging. When core samples drilled from wells are exposed to air, the fluids within their pores inevitably dissipate. This phenomenon may lead to discrepancies between the results of nuclear magnetic resonance relaxation experiments and the actual situation underground. To deeply explore the impact of fluid dissipation on NMR core analysis experimental results, a series of simulated dissipation experiments were designed under constant temperature and humidity conditions. Variations in one-dimensional and two-dimensional NMR measurement results of oil-saturated samples were examined under varying crude oil viscosities and dissipation times. The experimental results indicate that as exposure time increases, the T2 distribution of oil-saturated cores decreases, and the amplitude of the T2 distribution peaks decreases. Both oil and water relaxation components show a decreasing trend; however, the dissipation rate of the bounding water component significantly exceeds that of the crude oil component. By employing two-dimensional NMR relaxation time distribution fluid quantitative analysis technology, the relationship between the dissipation rates of various phase fluids and exposure time during the stable dissipation stage was analyzed. This offers a reference for adjusting the oil saturation of exposed cores based on NMR measurements.

The Saturation Calculation of NMR Logging Based on Constructing Water Spectrum Function

Tight sandstone oil reservoirs are characterized by complex structures, poor pore connectivity, and strong heterogeneity, with features such as low porosity and ultra-low permeability. Conventional methods for calculating saturation cannot accurately evaluate the hydrocarbon saturation of these reservoirs. To address this, a study was conducted from the perspective of non-electrical logging methods, focusing on the inherent nuclear magnetic resonance (NMR) characteristics of different fluids to develop a saturation calculation method that avoids the influence of the rock matrix, thus enabling precise saturation measurement in tight sandstone oil reservoirs. The traditional NMR porosity model was modified by segmenting it using the clay-bound water cutoff value, aiming to identify the distribution pattern of fluids in pores outside the clay-bound water zone. Through theoretical derivation and water spectrum function simulation, a water spectrum function and its parameter range suitable for the NMR T2 distribution in tight sandstone reservoirs were determined. Using core-sealed core saturation as a reference, the particle swarm optimization (PSO) algorithm was applied to optimize the parameter range and construct the final water spectrum function tailored to tight sandstone oil reservoirs. The accuracy and practicality of this method were validated by applying the derived water spectrum function to NMR logging in the exploration block, allowing for precise saturation calculations and the accurate evaluation of tight reservoir saturation.

Advanced Nuclear Magnetic Resonance, Fourier Transform–Infrared, Visible-NearInfrared and X-ray Diffraction Methods Used for Characterization of Organo-Mineral Fertilizers Based on Biosolids

Biosolids from stabilized sludge present a high fertilization potential, due to their rich content of nutrients and organic matter. The intrinsic and subtle properties of such fertilizers may greatly influence the fertilization efficiency. In this sense, the utility, advantages and limitations of advanced characterization methods, for the investigation of structural and dynamic properties at the microscopic scale of slightly different formulations of fertilizers were assessed. For that, three formulas of organo-mineral fertilizers based on biosolids (V1, V2 and V3), having at least 2% N, 2% P2O5, and 2% K2O, were characterized by advanced methods, such as 1H NMR relaxometry, 1H MAS and 13C CP-MAS NMR spectroscopy, 1H double-quantum NMR and FT-IR spectroscopy. Advanced structural characterization was performed using SEM, EDX and X-ray diffraction. Four dynamical components were identified in the NMR T2 distribution showing that the rigid component has a percentage larger than 90%, which explains the broad band of NMR spectra confirmed by the distributions of many components in residual dipolar coupling as were revealed by 1H DQ-NMR measurements. SEM and EDX measurements helped the identification of components from crystalline-like X-ray diffraction patterns. To evaluate the release properties of organo-mineral fertilizers, dynamic measurements of classical electric conductivity and pH were performed by placing 0.25 g of the formulas (V1, V2 and V3) in 200 mL of distilled water. The content of N and P were quantified using specific reactants, combined with VIS-nearIR spectroscopy. Two release mechanisms were observed and characterized. It was found that V3 presents the smallest release velocity but releases the largest number of fertilizers.

A modified surface to volume (SVR) method to calculate nuclear magnetic resonance (NMR) surface relaxivity: Theory and a case study in shale reservoirs

Surface relaxivity (ρ2) is a critical parameter for converting nuclear magnetic resonance (NMR) T2 data to pore size distribution (PSD). The surface-to-volume ratio (SVR) method, known for its simplicity and ease of operation, has been widely used for ρ2 calculation in unconventional reservoirs. However, previous studies often overlooked the equivalence of pore ranges characterized when directly applying the classical SVR model. Moreover, shale reservoirs generally develop layered fractures, whose ρ2 values are different from matrix pores. The logarithmic mean value of the T2 distribution (T2LM) is significantly influenced by layered fractures, therefore, relying solely on the T2LM value of a whole sample under fluid-saturated state will lead to inaccurate ρ2 values of matrix pores, particularly in laminated shales where fractures are well developed. However, insufficient attention has been paid to the effect of fractures on the ρ2 calculation. In this study, a modified SVR method based on the theory of NMR relaxation in partially fluid-saturated pores was proposed to characterize the ρ2 of shale matrix pores. Twenty-four shale core samples from the Shahejie Formation in the Jiyang Depression, China were selected, and subjected to series of NMR experiments at varying oil-bearing conditions, and low-temperature nitrogen adsorption (LTNA) analysis. The results indicate a strong linear correlation (R2 > 0.85) between the inverse T2LM (1/T2LM) and the inverse fluid saturation (1/f) when oil molecules across the entire surface layer participate in the exchange process. For a whole core sample, ρ2 values obtained using the modified SVR model are higher than those obtained using the classical SVR model, especially in samples with numerous fractures. The modified SVR method effectively reduces the impact of fractures on the characterization of ρ2 of matrix pores. For shale pore ρ2 characterization, the classical SVR model may be more suitable for pores smaller than 300 nm, with a recommended T2 range of <33 ms. Additionally, ρ2 values for different pore ranges (<25 nm, 25–100 nm, and >100 nm) within individual samples were estimated. It is found that the ρ2 values of smaller pores is greater than those of larger pores, which may be due to differences in mineralogy of the pores across various size ranges. The small pores are more associated with clay minerals while large pores are surrounded by quartz and rigid minerals. In addition, ρ2 is lower in larger pores and fractures that do not contain organic matter and clays, thus the underestimation of ρ2 by the classical SVR method can be corrected by modified SVR method. This study represents the first attempt to examine ρ2 variations across different pore ranges in shale reservoirs. The methodology presented can be applied to other formations, enhancing NMR data application in both laboratory settings and well logging.

Water-soluble chitosan polymer for enhanced oil recovery in the carbonate reservoir

Numerous surfactants, nanoparticles and polymers have been developed and utilized for enhanced oil recovery applications, irrespective of their environmental impact. Most of these oilfield chemicals were prepared through multi-steps from fossil-based starting materials using hazardous solvents. However, there is a desire to advance eco-friendly and sustainable materials to reduce CO2 emissions and enhance the sustainability of oil production. Herein, we propose the development of chitosan salt, a solely green polymer, prepared in water in the presence of acetic acid (0.1% v/v). The resulting water-soluble polymer demonstrated excellent stability under reservoir conditions and was tested for enhanced oil recovery in the carbonate reservoir. The oil-wet rock wettability was significantly reduced after using chitosan salt solution. Nuclear magnetic resonance (NMR) experiments were used to show the oil displacement at different pores regions using relaxation time (T2 distribution). Imbibition and coreflooding experiments showed that the chitosan salt is able to increase the enhanced oil recovery by extra 16.2% which surpass the recovery obtained from commercial surfactants such as α-olefin sulfonate (AOS) and cetrimonium bromide (CTAB). This study shows that green materials are promising candidates for oil recovery and upstream applications.

Low-field MRI study of the 1H distribution and migration in porous sediments during natural gas conversion from methane hydrate

Gas hydrates, crystalline compounds formed from water and guest molecules like methane, are gaining attention as a promising clean energy source. While research has extensively focused on the extraction and transport of natural gas hydrates from offshore marine sediments, the dynamic processes in the porous sediments remain under explored. This study employs low-field Magnetic Resonance Imaging (MRI) to investigate the in-situ formation and dissociation of methane hydrate within a partially saturated stack of glass beads. By integrating advanced MRI techniques, including 1D dhk SPRITE, bulk T1 distribution, and 2D spatial T2 imaging, this research provides a comprehensive analysis of fluid distribution and migration during phase transitions in the porous sediments. Three key findings emerged from the study. First, SE-SPI measurements successfully quantified hydrate and residual water saturation, aligning with previous X-ray CT and high-field MRI studies and validating low-field MRI for hydrate research. Secondly, this study introduced a volumetric approach to T1 and T2 measurements, distinguishing between free and bound water, with characteristic relaxation times for each, confirming the technique's capability to differentiate types of residual water. Finally, spatially resolved T2 relaxation time distributions revealed vertical fluid migration within the pore spaces, identifying an equilibrium zone where inflow and outflow rates were balanced. Overall, this study underscores the effectiveness of low-field MRI as a noninvasive tool for analyzing hydrate-bearing sediments. The findings lay the groundwork for further exploration of hydrate in porous sediments, enhancing our understanding of gas production dynamics in hydrate-rich environments.

Modified Low-Field NMR Method for Improved Pore Space Analysis in Tight Fe-Bearing Siliciclastic and Extrusive Rocks

Abstract Understanding the filtration and storage properties of tight reservoirs is crucial for efficient resource exploitation, particularly in unconventional formations. This study presents two low-field nuclear magnetic resonance (LF-NMR) techniques: standard cut-off and modified differential approaches combined with mercury injection capillary pressure (MICP) and X-ray diffraction (XRD) studies to evaluate porosity and pore size distribution (PSD) in such formations. The differential technique involves subtracting the dry sample signal from a 100% water-saturated one, allowing the chemically bound water compound to be eliminated and facilitating PSD analysis. Through the application of the percolation theory, we established a power–law relationship between LF-NMR transverse relaxation time (T2) and MICP pore-throat diameter, enabling the derivation of PSD and pseudo capillary pressure curves. Our methodology was validated on a sample set representing tight sandstones, conglomerates, and extrusive rocks with high clay and iron mineral content, demonstrating the superior accuracy of the modified differential method in estimating effective porosity and absolute PSD in comparison with the standard approach. While the use of the percolation theory in PSD conversion was successful for rocks with unimodal distributions, it often failed for rocks with larger voids. The study also revealed that the relationship between the LF-NMR transverse relaxation times and MICP pore sizes is both nonlinear and challenging to describe with a universal equation, especially in the presence of para- and ferro-magnetic elements in the rock matrix. Despite obstacles to the complete elimination of the influence of these minerals on the T2 distribution, employing the modified differential LF-NMR method significantly mitigated this effect and offered a precise and noninvasive way of characterizing the petrophysical properties of tight reservoir rocks. Consequently, our studies offer a significant step toward a more precise assessment of pore structures in unconventional reservoirs that could be translated into more efficient strategies for locating geothermal heat and hydrocarbon resources.

Slaughterhouse Wastewater Properties Assessment by Modern and Classic Methods

Advanced 1H Nuclear Magnetic Resonance (NMR) relaxometry and diffusometry methods and VIS-nearIR spectroscopy combined with pH, electrical conductivity (EC) and totally dissolved solids (TDSSs) measurements were used to assess the properties of wastewater collected from a chicken slaughterhouse in each step of the treatment process (wastewater before treatment, biologically treated wastewater, chemically treated wastewater and discharged wastewater) and from sludge. The 1H NMR Carr–Purcell–Meiboom–Gill (CPMG) and Pulsed-Gradient-Stimulated-Echo (PGSE) decay curves recorded for all samples of wastewater were analyzed by inverse Laplace transform (ILT) to obtain the distributions of transverse relaxation times T2 and diffusion coefficient D. The VIS-nearIR total absorbance, T2-values, D-values, pH, EC and TDSS parameters were used for statistical analysis in principal component (PCA). The 1H T2-distributions measured for the slaughterhouse wastewater lie in two main regions reflecting the number of dissolved solids or the distribution of undissolved solids. The PCA analysis successfully differentiates between polluted and less polluted wastewaters and sludge. The wastewater treatment applied by the slaughterhouse is efficient. The recommended methods for wastewater monitoring are the NMR T2- and D-distributions and EC, TDSSs and NMR-D diffusion coefficient. Finally, Machine Learning algorithms are used to provide prediction maps of wastewater treatment stage.

Benzimidazole based electron-transport hosts for efficient pure blue narrowband OLED device

Two electron-transport host materials are synthesized by linking anthracene with benzimidazole derivatives through a unit of methyl substituted phenyl. The methyl substitution generates a large dihedral angle between the benzimidazole plane and bridging phenyl, keeping the excited state distribution and energy levels of T1 and S1 unchanged. The electron-only devices reveal that the two hosts have obviously enhanced electron transport ability than that of Ph-AN-MBP without benzimidazole. As a result, the devices with Ph-AN-BIZ and N1-AN-BIZ as hosts and a blue multiple resonance material of tBuCz-DABNA as emitter exhibit high external quantum efficiency of 10.1 % and 9.1 %, respectively, and low turn-on voltage of 2.7 V, which is better than those of Ph-AN-MBP based device (7.9 %, 3.4 V). And their electroluminescence spectra have a very small full-width at half-maximum of 16.2 nm and pure blue color with CIE coordinates of (0.12, 0.11).

Estimation of porosity distribution from formation image logs and comparing the results with NMR log analysis: Implications for the heterogeneity analysis of carbonate reservoirs with an example from the Asmari reservoir, southwest Iran

Estimating heterogeneity in carbonate rocks is the most important parameter in identifying reservoir and non-reservoir areas. Diagenetic and sedimentary processes directly control reservoir heterogeneity. In this regard, the high hydrocarbon production rate and the reduction of the complexity of the carbonate reservoirs require the evaluation of a new architecture of the reservoir, in which the simultaneous impact of the diagenetic-sedimentary processes on the petrophysical logs is investigated. The current study studies the Oligocene-Miocene Asmari Formation Iran's giant carbonate reservoir. Based on petrographic studies, sedimentary facies, depositional environment and diagenetic processes were characterized. Formation evaluation was conducted to determine lithology, water saturation, fluid volume, and effective porosity. The estimated porosity from the evaluation of the conventional logs (full suite) was compared with the results of estimating the porosity from the NMR T2 distribution curve and the porosity histogram of the image logs. Lorenz's coefficient of heterogeneity was used to understand the heterogeneity of the reservoir. Diagenetic-sedimentary processes and petrophysical logs were used to investigate the pore type and their distribution. The results of petrographic studies, NMR T2 distribution curve, and porosity histogram show that the diagenetic-sedimentary process is the most important factor enhancing the reservoir heterogeneity. Diagenetic and sedimentary processes were traced by evaluating NMR and Image logs. Based on the results, the porosity distribution using the T2 curve and Image show a good agreement. Diagenetic processes mainly dissolution and dolomitization increased the heterogeneity of the main production zones (zones 3 and 4) of the Asmari reservoir that was confirmed using NMR and Image logs.

Swelling pressure of phyllite residual soil during saturation

Phyllite residual soil is a typical regional soil formed from the weathering of phyllite rock formations, characterized by poor engineering properties. The swelling pressure could pose a threat to roadbed stability and other geological engineering disasters during the rainy season. Therefore, studying the swelling pressure of phyllite residual soil is critical for ensuring the sustainable development of both human society and the natural environment. In this study, a series of swelling pressure tests were conducted on the phyllite residual soil to determine its swelling pressure, and nuclear magnetic resonance (NMR) test was applied to assess the evolution of soil fabric in both the initial unsaturated state and saturated state. The results indicate that the swelling rate of phyllite residual soil is negatively correlated with the initial water content and positively correlates with the dry density. The denser or drier the phyllite residual soil is in its initial state, the higher the equilibrium swelling pressure will be. The analysis of T2 distribution curves reveals that during the wetting process in phyllite residual soil, water fills micropores prior to macropores until water fills up all pores.

Evolution of pore structure and analysis of freeze damage in granite during cyclic freeze-thaw using NMR technique

Understanding the changes in a rock's pore structure and unfrozen water content during the freeze-thaw (F-T) process is crucial for unraveling the F-T damage mechanism of rock masses. This study employs nuclear magnetic resonance (NMR) tests to resolve the pore structure characteristics of granite specimens subjected to varying numbers of F-T cycles (0, 50, 100, and 200 cycles). Throughout the F-T process, unfrozen water (comprising bound water and free water) is quantified through T2 distribution curves, and the freeze-induced strain at different subzero temperatures is investigated. The results reveal that F-T cycles lead to the expansion of pore sizes from small to large, reducing the complexity of the pore structure. Moreover, an increased proportion of meso- and macro-pores accelerates the rate of water-ice phase transition in granite specimens, resulting in intensified freeze damage and greater maximum freeze-induced strain. Additionally, when previously damaged granite is refrozen, the presence of free water induces higher levels of freeze-induced strain. This research comprehensively analyzes the F-T damage process in granite, laying a crucial theoretical foundation for understanding freeze damage mechanisms in rock engineering.

Two-dimensional spectrum characteristics and oil movability study of the shale oil reservoir

Shale oil is mainly stored in the nano–micro-pores of shale in the form of adsorption or in a free state. Among them, only free-state oil is the main contributor to shale oil production under natural elastic energy. Therefore, it is crucial to evaluate the movability of crude oil effectively. In this paper, focusing on the Jurassic shale oil reservoir core in the middle-eastern Sichuan region of China, low-field nuclear magnetic resonance (NMR) technology is used to analyze the basic characteristics of shale oil core samples. Experiments on the low-field NMR one-dimensional and two-dimensional spectrum characteristics of the original core, heat-treated core, and thermogravimetric-treated shale core are carried out. The effects of the TG-MS method, T2 method, and the volatilization of light oil components on the movability of shale oil reservoirs are analyzed, and the movability characteristics of shale oil reservoirs in the middle-eastern Sichuan region are preliminarily clarified. The results show that under thermal treatment, the distribution range of the two-dimensional spectrum of the core oil occurrence area is significantly reduced, and the T1 and T2 distribution ranges are reduced by 10.9% and 60.7%, respectively. According to the TG-MS method, the mobile oil, bound oil, and adsorbed oil account for 74.7%, 8.1%, and 17.2%, respectively. The quantitative calculation of movable oil saturation by NMR combined with heat treatment is 65.6%, which is lower than that calculated using the thermogravimetric method. In order to calculate the movability more accurately, the scale effect between different samples should be considered. This study could provide a theoretical basis for the subsequent shale oil development program.

Radiomic- and dosiomic-based clustering development for radio-induced neurotoxicity in pediatric medulloblastoma

BackgroundTexture analysis extracts many quantitative image features, offering a valuable, cost-effective, and non-invasive approach for individual medicine. Furthermore, multimodal machine learning could have a large impact for precision medicine, as texture biomarkers can underlie tissue microstructure. This study aims to investigate imaging-based biomarkers of radio-induced neurotoxicity in pediatric patients with metastatic medulloblastoma, using radiomic and dosiomic analysis.MethodsThis single-center study retrospectively enrolled children diagnosed with metastatic medulloblastoma (MB) and treated with hyperfractionated craniospinal irradiation (CSI). Histological confirmation of medulloblastoma and baseline follow-up magnetic resonance imaging (MRI) were mandatory. Treatment involved helical tomotherapy (HT) delivering a dose of 39 Gray (Gy) to brain and spinal axis and a posterior fossa boost up to 60 Gy. Clinical outcomes, such as local and distant brain control and neurotoxicity, were recorded. Radiomic and dosiomic features were extracted from tumor regions on T1, T2, FLAIR (fluid-attenuated inversion recovery) MRI-maps, and radiotherapy dose distribution. Different machine learning feature selection and reduction approaches were performed for supervised and unsupervised clustering.ResultsForty-eight metastatic medulloblastoma patients (29 males and 19 females) with a mean age of 12 ± 6 years were enrolled. For each patient, 332 features were extracted. Greater level of abstraction of input data by combining selection of most performing features and dimensionality reduction returns the best performance. The resulting one-component radiomic signature yielded an accuracy of 0.73 with sensitivity, specificity, and precision of 0.83, 0.64, and 0.68, respectively.ConclusionsMachine learning radiomic-dosiomic approach effectively stratified pediatric medulloblastoma patients who experienced radio-induced neurotoxicity. Strategy needs further validation in external dataset for its potential clinical use in ab initio management paradigms of medulloblastoma.

The Influence of Lyophilization Pretreatment and Whey Content on Whey and Gelatin-Based Hydrogels.

Whey and gelatin, natural polymers within the protein category, find widespread use in hydrogel formulations applied across the food, medical, and pharmaceutical industries. This study presents new characteristics of hydrogels based on whey, gelatin, and copper sulfate as a consequence of the additional steps in the preparation method, specifically refrigeration and freezing storage followed by lyophilization. The water state in hydrogels prior to lyophilization impacts the morphological appearance, with refrigerated hydrogels exhibiting a more regular and dense pore distribution, as shown by the Scanning Electron Microscopy (SEM) images. This observation aligns with the higher mobility of polymer chains indicated by T2 distributions in 1H nuclear magnetic resonance (RMN) relaxometry measurements. Changes in the intensity and amide-specific wavenumbers of the FTIR spectra of whey and gelatin proteins are evident in the Fourier Transformed Infrared (FTIR) spectra of crosslinked and frozen hydrogels before lyophilization. Moreover, the reinforcing effect in the hydrogel matrix, noted in mechanical tests, is attributed to increased polymer chain content and copper sulfate crosslinking.

Bayesian NMR petrophysical characterization

Identification of reservoir rock types is necessary for the exploration and recovery of oil and gas. It involves determining the petrophysical properties of rocks such as porosity and permeability which play a significant role in developing reservoir models, estimating the volumes of oil and gas reserves, and planning production methods. Nuclear magnetic resonance (NMR) technology is a fast and accurate tool for petrophysical rock characterization. The distributions of relaxation times (T2 distributions) offer valuable insights into the distribution of pore sizes in rocks, and these distributions are closely linked to important petrophysical parameters like porosity, permeability, and bound fluid volume (BFV).This work introduces a Bayesian estimation method for analyzing NMR data. The Bayesian approach uses prior knowledge of T2 distributions in the form of the prior mean and covariance. The Bayesian approach combines prior knowledge with observed data to obtain improved estimation. We use the Bayesian estimation method where prior information regarding the rock sample type, for example shale, is available.The estimators were evaluated on decay data simulated from synthesized distributions that replicate the features of experimental T2 distributions of three types of reservoir rocks. We compared the performance of the Bayesian method with two existing methods using porosity, bound fluid volume (BFV) geometric mean (T2LM) and root mean square error (RMSE) of the estimated T2 distribution as evaluation criteria. Additional experiments were carried out using experimental T2 distributions to validate the results.The performance of the Bayesian methods was also tested using mismatched priors.The experimental results illustrate that the Bayesian estimator outperforms other estimators in estimating the T2 distribution. The Bayesian method also outperforms the ILT method in estimating derived petrophysical properties except in cases where the noise level is below 0.1 and the T2 distributions are associated with short relaxation times.

Pore-scale physics of ice melting within unconsolidated porous media revealed by non-destructive magnetic resonance characterization

Melting of ice in porous media widely exists in energy and environment applications as well as extraterrestrial water resource utilization. In order to characterize the ice-water phase transition within complicated opaque porous media, we employ the nuclear magnetic resonance (NMR) and imaging (MRI) approaches. Transient distributions of transverse relaxation time T2 from NMR enable us to reveal the substantial role of inherent throat and pore confinements in ice melting among porous media. More importantly, the increase in minimum T2 provides new findings on how the confinement between ice crystal and particle surface evolves inside the pore. For porous media with negligible gravity effect, both the changes in NMR-determined melting rate and our theoretical analysis of melting front confirm that conduction is the dominant heat transfer mode. The evolution of mushy melting front and 3D spatial distribution of water content are directly visualized by a stack of temporal cross-section images from MRI, in consistency with the corresponding NMR results. For heterogeneous porous media like lunar regolith simulant, the T2 distribution shows two distinct pore size distributions with different pore-scale melting dynamics, and its maximum T2 keeps increasing till the end of melting process instead of reaching steady in homogeneous porous media.

On the microstructure, texture and electrochemical properties of severely deformed and artificially aged lightweight AA2050 Al–Cu–Li alloy

Lightweight 3rd generation Al–Cu–Li alloy AA2050 was severely deformed via Multi Axial Forging (MAF) at 170 °C followed by artificial aging at 150 °C. Effect of MAF and post MAF aging on microstructure and precipitation was investigated using transmission electron microscopy (TEM). Formation of deformation bands and large dislocation cells were evident on MAF processed samples. Post MAF peak aging resulted in the distribution of fine T1 precipitates in grain interiors with reduction in grain boundary precipitation. Bulk texture studies reveal the formation of strong Goss and S texture components upon MAF processing. Further, low temperature artificial aging doesn’t exhibit significant changes in texture characteristics, either in terms of texture intensities or texture components. Polarization studies showed that peak aged samples exhibited better corrosion resistance compared to un-aged samples. Overall, 12 pass MAF processed and peak aged samples showed higher corrosion resistance. Further, corrosion surface morphologies examination revealed the change in corrosion mechanisms with thermomechanical treatments. Improved corrosion resistance after MAF and peak aging widens the requirements in aerospace and aircraft applications for such engineering alloys.

Experimental study on gas slippage effect in coal at different temperatures based on nuclear magnetic resonance

Coalbed methane (CBM) can be recovered more effectively through heat injection mining. The slippage effect in coal becomes more significant as CBM is exploited, essential for maintaining consistent production of CBM wells. By “slippage effect,” we mean that gas molecules exhibiting non–zero velocity near the wall surface of coal pores, leading to higher gas permeability than liquid permeability. To explore the slippage effect and its control mechanism during heat injection mining, methane seepage experiments with constant effective stress were conducted under five different temperatures and seven pore pressures. An analysis was conducted on the mechanisms by which pore pressure and temperature affect gas slippage effect. Furthermore, the correlation between coal pore structure and the gas slippage effect was revealed using the nuclear magnetic resonance (NMR) technique. The results appear that, first, as pore pressure increases, the slippage effect is suppressed due to the influence of the average molecular free path, despite the positive impact of adsorption–induced matrix expansion. Second, as temperature rises, the average molecular free path and thermal expansion have a positive impact on gas slippage, while matrix shrinkage caused by desorption has a negative impact. The positive impact is stronger, resulting in a continuous enhancement of the slippage effect. Finally, a new slippage factor calculation based on NMR T2 distribution of micropores and transitional pores (&amp;lt;100 nm, T2 &amp;lt; 8.33 ms) was provided, and the method was verified by slippage factor fitted by permeability experimental data. The heat injection mining of CBM can be theoretically guided by the research results.

Petrophysical insights into pore structure in complex carbonate reservoirs using NMR data

The study delves into pore structure attributes within the complex Eocene carbonate of an Indian offshore field, encompassing pore throat, radius and their characteristics. Nuclear Magnetic Resonance (NMR) experimental data reveals crucial insights into pore structures and fluid states. This study compares the NMR T2 distribution curve with capillary pressure data from the Mercury Injection Capillary Pressure (MICP) technique, deriving linear and nonlinear conversion coefficients to transform NMR T2 spectra into equivalent pore radius distribution. Pore radius-dependent porosity partitioning, linked to permeability and the distribution of irreducible water, is conducted utilizing NMR-derived data. Following the T2 cut-off analysis, a two-segment fractal analysis of NMR T2 distribution is also carried out. This analysis unveils associations between fractal dimensions and various petrophysical parameters, including permeability, porosity, T2LM, irreducible water saturation and R50. The NMR-derived pore radius distribution is mostly unimodal, occasionally slightly bimodal. Six different pore size classes (less than 0.05 μm to more than 5 μm) are analysed in relation to permeability, porosity and irreducible water. Small pores (<1 μm) contribute more to irreducible water with low porosity and permeability. The fractal dimension of large pores correlates strongly with porosity, permeability, T2LM, irreducible water and R50 suggesting significant impact on reservoir seepage capacity. In addition to porosity partitioning, the current study demonstrates effectiveness in modelling modified permeability and correlating it with in situ permeability when applied to field NMR log data from the study area. While numerous studies focus on sandstone, our study marks the pioneering attempt at a comprehensive analysis on complex carbonate reservoirs.