Search Results (45)

To investigate the flow characteristics of movable water in coal under the influence of micro-nano pore fractures with multiple fractal structures, this study employed nuclear magnetic resonance (NMR) and multifractal theory to analyze gas–water seepage under different injection pressures. Then, the scale threshold for mobile water entering coal pores and fractures was determined by clarifying the relationship among “injection pressure-T₂ dynamic multiple fractal parameter seepage resistance-critical pore scale”. The results indicate that coal samples from Yiwu (YW) and Wuxiang (WX) enter the nanoscale pore size range at an injection pressure of 8 MPa, while the coal sample from Malan (ML) enters the nanoscale pore size range at an injection pressure of 9 MPa. During the water injection process, there is a significant linear relationship between the multiple fractal parameters log X(q, ε) and log(ε) of the sample. The generalized fractal dimension D(q) decreases monotonically with increasing q in an inverse S-shape. This decrease occurs in two distinct stages: D(q) decreases rapidly in the low probability interval q < 0; D(q) decreases slowly in the high probability interval q > 0. The multiple fractal singularity spectrum function f(α) has an asymmetric upward parabolic convex function relationship with α, which is divided into a rapidly increasing left branch curve and a slowly decreasing right branch curve with α₀ as the boundary. Supporting evidence indicates the feasibility of a methodology for identifying the variation in multiple fractal parameters of gas–water NMR seepage and the critical scale transition conditions. This investigation establishes a methodological foundation for analyzing gas–water transport pathways within porous media materials. Full article

Shallow gas reservoirs exhibit low formation pressure and gas injection levels, leading to low-resistivity contrast between gas-bearing reservoirs and fully water-saturated layers. Gas-bearing formation identification and water saturation estimation face great challenges. To improve the accuracy of shallow gas reservoir identification and logging evaluation, it is essential to analyze the genesis mechanisms underlying the low-resistivity contrast. This study used the HJ Formation, a typical shallow gas reservoir located in the BY Sag of the eastern South China Sea Basin as an example. Combining the results of nuclear magnetic resonance (NMR), full rock mineral analysis and X-ray diffraction of clay minerals in the laboratory, it was determined that the genesis mechanism for the low-resistivity contrast in the gas-bearing reservoir was due to the high irreducible water saturation (S_wi) and the cation-induced supplementary conductivity. Afterwards, we integrated three methods, density–neutron correlation, calculation of the apparent formation water resistivity, and cross-plots of conventional and gas-logging curves, to identify shallow gas reservoirs. In addition, we also established a Waxman–Smits-based model to estimate water saturation. Compared with the typical Archie’s equation, the predicted water saturation curve using the Waxman–Smits-based model was more reasonable. The established methods and models can be used in target shallow gas reservoir evaluations, and it also has reference value for other types of oilfields with similar physical characteristics. Full article

This study focuses on the complex pore structure and pronounced heterogeneity of tight sandstone reservoirs in the Linxing area of the Ordos Basin and develops a multi-scale quantitative characterization approach to investigate the coupling mechanism between pore structure and reservoir properties. Six core samples were selected from the Shiqianfeng Formation (depth interval: 1326–1421 m) for detailed analysis. Cast thin sections and scanning electron microscopy (SEM) experiments were employed to characterize pore types and structural features. Nuclear magnetic resonance (NMR) experiments were conducted to obtain T₂ spectra, which were used to classify bound and movable pores, and their corresponding fractal dimensions were calculated separately. In addition, NMR logging data from the corresponding well intervals were integrated to assess the applicability and consistency of the fractal characteristics at the logging scale. The results reveal that the fractal dimension of bound pores shows a positive correlation with porosity, whereas that of movable pores is negatively correlated with permeability, indicating that different scales of pore structural complexity exert distinct influences on reservoir performance. Mineral composition affects the evolution of pore structures through mechanisms such as framework support, dissolution, and pore-filling, thereby further enhancing reservoir heterogeneity. The consistency between logging responses and experimental observations verifies the regional applicability of fractal analysis. Bound pores dominate within the studied interval, and the vertical variation of the PMF/BVI ratio aligns closely with both the NMR T₂ spectra and fractal results. This study demonstrates that fractal dimension is an effective descriptor of structural characteristics across different pore types and provides a theoretical foundation and methodological support for the evaluation of pore complexity and heterogeneity in tight sandstone reservoirs. Full article

The advancement of non-thermal disinfection technologies represents a critical pathway for ensuring food safety, meeting environmental sustainability requirements, and meeting consumer preferences for clean-label products. This study systematically evaluated the combined preservation effect of ultrasonic-assisted slightly acidic electrolyzed water (US+SAEW) on mirror carp fillets during refrigeration. Results demonstrated that US+SAEW exhibited superior antimicrobial efficacy compared to individual US or SAEW, achieving reductions of 0.73, 0.74, and 0.79 log CFU/g in total viable counts (TVC), Aeromonas bacteria, and lactic acid bacteria counts compared to the control, respectively. Furthermore, the combined intervention significantly suppressed microbial proliferation throughout the refrigeration period while simultaneously delaying protein and lipid degradation/oxidation induced by spoilage bacteria, thereby inhibiting the formation of alkaline nitrogenous compounds. Consequently, lower levels of pH, total volatile basic nitrogen (TVB-N), protein carbonyl, and thiobarbituric acid reactive substances (TBARS) were observed in US+SAEW compared to the other treatments. Multimodal characterization through low-field nuclear magnetic resonance (LF-NMR), texture, and color analysis confirmed that US+SAEW effectively preserved quality characteristics, extending the shelf life of mirror carp fillets by four days. This study provides a novel non-thermal preservation strategy that combines microbial safety maintenance with quality retention, offering particular advantages for thermolabile food. Full article

The strong heterogeneity of carbonate reservoirs poses significant technical challenges in reservoir classification and permeability evaluation. This study proposes a new method for reservoir classification based on nuclear magnetic resonance (NMR) logging data for the Asmari formation of the Middle East M Oilfield, a carbonate reservoir. By integrating NMR T₂ spectrum characteristic parameters (such as T₂ geometric mean, T_2R35/R50/R65, and pore volume fraction) with principal component analysis (PCA) for dimensionality reduction and an improved slope method, this study achieves fine reservoir type classification. The results are compared with core pressure curves and petrographic pore types. This study reveals that the Asmari reservoir can be divided into four categories (RT1 to RT4). RT1 reservoirs are characterized by large pore throats (maximum pore throat radius >3.8 μm), low displacement pressure (<0.2 MPa), and high permeability (average 22.16 mD), corresponding to a pore structure dominated by intergranular dissolution pores. RT4 reservoirs, on the other hand, exhibit small pore throats (<1 μm), high displacement pressure (>0.7 MPa), and low permeability (0.66 mD) and are primarily composed of dense dolostone or limestone. The classification results show good consistency with capillary pressure curves and petrographic pore types, and the pore–permeability relationships of each reservoir type have significantly higher fitting goodness (R² = 0.48~0.68) compared with the unclassified model (R² = 0.24). In the new well application, the root mean square error (RMSE) of permeability prediction decreased from 0.34 mD using traditional methods to 0.21 mD, demonstrating the method’s effectiveness. This approach does not rely on a large number of mercury injection experiments and can achieve reservoir classification solely through NMR logging. It provides a scalable technological paradigm for permeability prediction and development scheme optimization of highly heterogeneous carbonate reservoirs, offering valuable references for similar reservoirs worldwide. Full article

The accurate determination of acid/base constants (proton dissociation constants—pK_a, or equivalently protonation constants—logK) is essential for the physicochemical characterization of new molecules, especially in drug design and development, as these parameters thoroughly influence the pharmacokinetics and pharmacodynamics of drug action. While pH/potentiometric titration remains the gold standard method for determining acid/base constants, spectroscopic techniques—particularly nuclear magnetic resonance spectroscopy (as NMR/pH titrations)—have emerged as powerful alternatives for specific challenges in analytical chemistry, providing also information on the structure and site of protonation. In this study, we performed a comprehensive meta-analysis of protonation constants reported in the literature, measured using both potentiometry and NMR titrations. Our analysis compiled the available literature data and assessed the agreement between the two methods, taking into consideration various experimental conditions, such as temperature and ionic strength. The results provide insights into the reliability and applicability of NMR titrations compared with potentiometry, offering guidance for selecting appropriate methodologies in drug design. Full article

Accurate evaluation of permeability parameters is critical for the exploration and development of oil and gas fields. Among the available techniques, permeability assessment based on nuclear magnetic resonance (NMR) logging data is one of the most widely used and precise methods. However, the rapid biochemical variations in marine environments give rise to complex pore structures and strong reservoir heterogeneity, which diminish the effectiveness of traditional SDR and Timur–Coates models. To address these challenges in complex carbonate reservoirs, this study proposes a high-precision permeability evaluation method that integrates the Gaussian distribution model with the Thomeer model for more accurate permeability calculations using NMR logging data. Multimodal Gaussian distributions more accurately capture the size and distribution of multiscale pores. In this study, we innovatively employ the Gaussian distribution function to construct NMR-derived pseudo-pore size distribution curves. Subsequently, Thomeer model parameters are derived from Gaussian distribution parameters, enabling precise permeability calculation. The application of this method to the marine dolomite intervals of the Asmari Formation, Section A, within Oilfield A in southeastern Iraq, demonstrates its superior performance under both bimodal and unimodal pore size distributions. Compared to traditional models, this approach significantly reduces errors, providing crucial support for the accurate evaluation of complex reservoirs and the development of hydrocarbon resources. Full article

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. Full article

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. Full article

The viscosity of crude oil plays a pivotal role in the exploration and development of oil fields. The predominant reliance on laboratory measurements, which are constrained by manual expertise, represents a significant limitation in terms of efficiency. Two-dimensional nuclear magnetic resonance (NMR) logging offers a number of advantages over traditional methods. It is capable of providing faster measurement rates, as well as insights into fluid properties, which can facilitate timely adjustments in oil and gas development strategies. This study focuses on the loose sandstone reservoirs with high porosity and permeability containing heavy oil in the Huabei oilfield. Two-dimensional nuclear magnetic resonance (NMR) measurements and analyses were conducted on saturated rocks with different-viscosity crude oils and varying oil saturation levels, in both natural and artificial rock samples. This study elucidates the distribution patterns of different-viscosity crude oils within the two-dimensional NMR spectra. Furthermore, the T₁ and T₂ peak values of the extracted oil signals were employed to establish a model correlating oil viscosity with NMR parameters. Consequently, a criterion for determining oil viscosity based on two-dimensional NMR was formulated, providing a novel approach for estimating oil viscosity. The application of this technique in the BQ well group of the Huabei oilfield region yielded an average relative error of 15% between the actual oil viscosity and the computed results. Furthermore, the consistency between the oil types and the oil discrimination chart confirms the reliability of the method. The final outcomes meet the precision requirements for practical log interpretation and demonstrate the excellent performance of two-dimensional nuclear magnetic resonance (NMR) logging in calculating oil viscosity. The findings of this study have significant implications for subsequent exploration and development endeavors in the research area’s oilfields. Full article

Evaluating irreducible water saturation is crucial for estimating reservoir capacity and developing effective extraction strategies. Traditional methods for predicting irreducible water saturation are limited by their reliance on specific logging data, which affects accuracy and applicability. This study introduces a predictive method based on fractal theory and deep learning for assessing irreducible water saturation in complex carbonate reservoirs. Utilizing the Mishrif Formation of the Halfaya oilfield as a case study, a new evaluation model was developed using the nuclear magnetic resonance (NMR) fractal permeability model and validated with surface NMR and mercury injection capillary pressure (MICP) data. The relationship between the logarithm mean of the transverse relaxation time (T_2lm) and physical properties was explored through fractal theory and the Thomeer Function. This relationship was integrated with conventional logging curves and an advanced deep learning algorithm to construct a T_2lm prediction model, offering a robust data foundation for irreducible water saturation evaluation. The results show that the new method is applicable to wells with and without specialized NMR logging data. For the Mishrif Formation, the predicted irreducible water saturation achieved a coefficient of determination of 0.943 compared to core results, with a mean absolute error of 2.37% and a mean relative error of 8.46%. Despite introducing additional errors with inverted T_2lm curves, it remains within acceptable limits. Compared to traditional methods, this approach provides enhanced predictive accuracy and broader applicability. Full article

Fluid components in cores are crucial parameters in evaluating the quality of a shale reservoir in both laboratory analyses and log interpretation. In the Gulong area, shale reservoirs are characterized by a high clay content, with clay spaces hosting both oil and water phases, complicating the occurrence mechanism of fluid components, as a result, traditional research methods are no longer applicable. As an advanced technique, nuclear magnetic resonance (NMR) has been applied in oilfields to determine the specific petrophysical properties of rocks. To more accurately identify the types of fluid components, this study carried out a new, well-designed 2D NMR experiment, rock pyrolysis experiment, and quantitative oil and water detection experiment (QOWDE) to study the Gulong shale. This study measured the 2D NMR map of the original state, saturation state, centrifugal state, and pyrolysis at different temperatures, and conducted mutual verification between the QOWDE and 2D NMR pyrolysis experiments to obtain the distribution of different components of Gulong shale on the 2D NMR map. Based on the experimental results, this study developed a component identification template suitable for the Gulong area and calculated the 2D NMR porosity and saturation from it. This lays a foundation for the analysis and application of fluid components in the Gulong region and provides a new experimental basis and methodological support for porosity and saturation calculations. Full article

The Upper Paleozoic tight sandstone reservoirs on the eastern margin of the Ordos Basin exhibit strong heterogeneity and complex pore structures, leading to poor correlation between porosity and permeability and insufficient accuracy in permeability calculations to meet the requirements of reservoir fine evaluation. Therefore, a new method for high-precision permeability calculation based on flow zone index (FZI) reservoir classification is proposed. This method determines the number of reservoir classifications based on the characteristics of the FZI normal probability distribution plot and establishes FZI division criteria for reservoir types. Classified reservoirs exhibit similar flow characteristics, significantly improving the correlation between permeability and porosity. Based on nuclear magnetic resonance (NMR) combined with mercury injection capillary pressure (MICP) experiments, a modeling method for calculating the flow zone index based on the geometric mean of NMR T₂ is proposed. This method realizes continuous calculation of FZI based on NMR logging, reservoir classification, and permeability for the entire wellbore, thereby constructing a new permeability prediction method for tight sandstone reservoirs based on NMR logging and FZI classification. Actual application results demonstrate that the permeability calculated using NMR logging is in high agreement with the permeability analyzed from core data, with an average relative error of 45.8%, proving the effectiveness of the proposed method in this study. Full article

Reservoir permeability is an important parameter for reservoir characterization and the estimation of current and future production from hydrocarbon reservoirs. Logging data is an important means of evaluating the continuous permeability curve of the whole well section. Nuclear magnetic resonance logging measurement results are less affected by lithology and have obvious advantages in interpreting permeability. The Coates model, SDR model, and other complex mathematical equations used in NMR logging may achieve a precise approximation of the permeability values. However, the empirical parameters in those models often need to be determined according to the nuclear magnetic resonance experiment, which is time-consuming and expensive. Machine learning, as an efficient data mining method, has been increasingly applied to logging interpretation. XGBoost algorithm is applied to the permeability interpretation of carbonate reservoirs. Based on the actual logging interpretation data, with the proportion of different pore components and the logarithmic mean value of T2 in the NMR logging interpretation results as the input variables, a regression prediction model is established through XGBoost algorithm to predict the permeability curve, and the optimization of various parameters in XGBoost algorithm is discussed. The determination coefficient is utilized to check the overall fitting between measured permeability versus predicted ones. It is found that XGBoost algorithm achieved overall better performance than the traditional models. Full article

This research is an exploratory study on the sesquiterpenes and flavonoid present in the leaves of Artemisia tridentata subsp. tridentata. The leaf foliage was extracted with 100% chloroform. Thin-layer chromatography (TLC) analysis of the crude extract showed four bands. Each band was purified by column chromatography followed by recrystallization. Three sesquiterpene lactones (SLs) were isolated—leucodin, matricarin and desacetylmatricarin. Of these, desacetylmatricarin was the major component. In addition, a highly bio-active flavonoid, quercetagetin 3,6,4′-trimethyl ether (QTE), was also isolated. This is the first report on the isolation of this component from the leaves of Artemisia tridentata subsp. tridentata. All the components were identified and isolated by TLC, high-performance liquid chromatography (HPLC) and mass spectrometry (MS) techniques. Likewise, the structure and stereochemistry of the purified components were characterized by extensive spectroscopic analysis, including 1D and 2D nuclear magnetic resonance (NMR) and Fourier transform infrared spectroscopy (FTIR) studies. The antioxidant activities of crude extract were analyzed, and their radical-scavenging ability was determined by Ferric reducing antioxidant power (FRAP) and 2,2-diphenyl-1-picrylhydrazyl (DPPH) assay. The crude extract showed antioxidant activity of 18.99 ± 0.51 and 11.59 ± 0.38 µmol TEg⁻¹ FW for FRAP and DPPH assay, respectively, whereas the activities of matricarin, leucodin, desacetylmatricarin and QTE were 13.22, 13.03, 14.90 and 15.02 µmol TEg⁻¹ FW, respectively, for the FRAP assay. The antitumor properties were probed by submitting the four isolated compounds to the National Cancer Institute (NCI) for NCI-60 cancer cell line screening. Overall, the results of the one-dose assay for each SL were unremarkable. However, the flavonoid’s one-dose mean graph demonstrated significant growth inhibition and lethality, which prompted an evaluation of this compound against the 60-cell panel at a five-dose assay. Tests from two separate dates indicate a lethality of approximately 75% and 98% at the log⁻⁴ concentration when tested against the melanoma cancer line SK-Mel 5. This warrants further testing and derivatization of the bioactive components from sagebrush as a potential source for anticancer properties. Full article