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The numerical dispersion phenomenon in the finite-difference forward modeling simulations of the wave equation significantly affects the imaging accuracy in acoustic reflection logging. This issue is particularly pronounced in the reverse time migration (RTM) method used for shear-wave (S-wave) logging imaging. This not only affects imaging accuracy but also introduces ambiguities in the interpretation of logging results. To address this challenge, this study proposes the use of a least-squares difference coefficient optimization algorithm aiming to suppress the numerical dispersion phenomenon in the RTM of S-wave reflection imaging logging. By optimizing the difference coefficients, the high-precision finite-difference algorithm serves as an effective operator for both forward and backward RTM processes. This approach is instrumental in eliminating migration illusions, which are often caused by numerical dispersion. The effectiveness of this optimized algorithm is demonstrated through numerical results, which indicate that it can achieve more accurate forward imaging results across various conditions, including high- and low-velocity strata, and is effective in both large and small spatial grids. The results of processing real data demonstrate that numerical dispersion optimization effectively reduces migration artifacts and diminishes ambiguities in logging interpretations. This optimization offers crucial technical support to the RTM method, enhancing its capability for accurately modeling and imaging S-wave reflections. [ABSTRACT FROM AUTHOR]

We have established a set of laboratory measurements which is used for capturing element gammma spectrum. Standard captured gamma ray spectra for ten elements, including Si, Ca, Fe, are obtained using the measurements for the first time in China. We also simulated the capture gamma ray spectra of the ten elements using Monte Carlo methodology with the same parameters of our experimental measurements. Comparing the experiment and simulation results with the data from the International Atomic Energy Agency's Nuclear Data Center, we obtained the standard captured gamma ray spectra of the ten elements, which, as calibration spectra, are used to calibrate the raw spectrum in data processing. This method solved the key problem during the conversion from the original measuring spectrum to the yield of each element in the data processing. The method can effectively improve the accuracy of the element yield calculation. [ABSTRACT FROM AUTHOR]

In this study, the gamma-ray spectrum of single elemental capture spectrum log was simulated. By numerical simulation we obtain a single-element neutron capture gamma spectrum. The neutron and photon transportable processes were simulated using the Monte Carlo N-Particle Transport Code System (MCNP), where an Am-Be neutron source generated the neutrons and thermal neutron capture reactions with the stratigraphic elements. The characteristic gamma rays and the standard gamma spectra were recorded, from analyzing of the characteristic spectra analysis we obtain the ten elements in the stratum, such as Si, Ca, Fe, S, Ti, Al, K, Na, Cl, and Ba. Comparing with single elemental capture gamma spectrum of Schlumberger, the simulated characteristic peak and the spectral change results are in good agreement with Schlumberger. The characteristic peak positions observed also consistent with the data obtained from the National Nuclear Data Center of the International Atomic Energy Agency. The neutron gamma spectrum results calculated using this simple method have practical applications. They also serve as an reference for data processing using other types of element logging tools. [ABSTRACT FROM AUTHOR]

Buiding data-driven models using machine learning methods has gradually become a common approach for studying reservoir parameters. Among these methods, deep learning methods are highly effective. From the perspective of multi-task learning, this paper uses six types of logging data—acoustic logging (AC), gamma ray (GR), compensated neutron porosity (CNL), density (DEN), deep and shallow lateral resistivity (LLD) and shallow lateral resistivity (LLS) —that are inputs and three reservoir parameters that are outputs to build a porosity saturation permeability network (PSP-Net) that can predict porosity, saturation, and permeability values simultaneously. These logging data are obtained from 108 training wells in a medium-low permeability oilfield block in the western district of China. PSP-Net method adopts a serial structure to realize transfer learning of reservoir-parameter characteristics. Compared with other existing methods at the stage of academic exploration to simulating industrial applications, the proposed method overcomes the disadvantages inherent in single-task learning reservoir-parameter prediction models, including easily overfitting and heavy model-training workload. Additionally, the proposed method demonstrates good anti-overfitting and generalization capabilities, integrating professional knowledge and experience. In 37 test wells, compared with the existing method, the proposed method exhibited an average error reduction of 10.44%, 27.79%, and 28.83% from porosity, saturation, permeability calculation. The prediction and actual permeabilities are within one order of magnitude. The training on PSP-Net are simpler and more convenient than other single-task learning methods discussed in this paper. Furthermore, the findings of this paper can help in the re-examination of old oilfield wells and the completion of logging data. [ABSTRACT FROM AUTHOR]

Background: Intracerebral translocator protein 18 kDa (TSPO) mediates the transport of cholesterol from cytoplasm to mitochondria and activation of microglia. The change of TSPO and the dysfunction of microglia are closely related to the pathogenesis of Alzheimer's disease (AD).Aims: This study aimed to investigate the effects of microglial TSPO and its selective ligand YL-IPA08 on the cognitive function of transgenic mice in 5 × familial Alzheimer's disease (FAD) mouse model of AD.Methods: The TSPO knockout 5 × FAD transgenic mice were bred, and tested by Morris water maze. The effects of YL-IPA08 on cognitive abilities and expression of Aβ in 5 × FAD mice were also explored into.Results: The latency of escape by TSPO knockout 5 × FAD mice was significantly prolonged compared with the 5 × FAD group, indicating that the cognitive impairment of mice aggravated. With the attenuated phagocytic ability of microglia, the deposition of Aβ in prefrontal cortex of TSPO knockout 5 × FAD mice increased, and the expression of proinflammatory factors (IL-1β, TNF-α, IL-6) were upregulated. In addition, YL-IPA08 significantly reduced the latency of escape by 5 × FAD mice, increased the number of times of crossing over the platform by mice, and inhibited the deposition of Aβ in the prefrontal cortex of 5 × FAD mice without affecting the cleavage of APP.Conclusion: Our findings suggested that TSPO knockout in 5 × FAD mice inhibited microglial phagocytosis, promoted Aβ deposition and neuroinflammation, and aggravated cognitive dysfunction in AD mice. YL-IPA08 had a significant cognition-enhancing effect in 5 × FAD transgenic mice, which might provide a new basis for potential drug candidates in AD treatment. [ABSTRACT FROM AUTHOR]

Calculating the mineral composition is a critical task in log interpretation. Elemental capture spectroscopy (ECS) log provides the weight percentages of twelve common elements, which lays the foundation for the accurate calculation of mineral compositions. Previous processing methods calculated the formation composition via the conversion relation between the formation chemistry and minerals. Thus, their applicability is limited and the method precision is relatively low. In this study, we present a multimineral optimization processing method based on the ECS log. We derived the ECS response equations for calculating the formation composition, then, determined the logging response values for the elements of common minerals using core data and theoretical calculations. Finally, a software module was developed. The results of the new method are consistent with core data and the mean absolute error is less than 10%. [ABSTRACT FROM AUTHOR]

In this paper, wavefield storage optimization strategies are discussed with respect to reverse-time migration (RTM) imaging in reflection-acoustic logging, considering the problem of massive wavefield data storage in RTM itself. In doing so, two optimization methods are proposed and implemented to avoid wavefield storage. Firstly, the RTM based on the excitation-amplitude imaging condition uses the excitation time to judge the imaging time, and accordingly, we only need to store a small part of wavefield, such as the wavefield data of dozens of time points, the instances prove that they can even be imaged by only two time points. The traditional RTM usually needs to store the wavefield data of thousands of time points, compared with which the data storage can be reduced by tens or even thousands of times. Secondly, the RTM based on the random boundary uses the idea that the wavefield scatters rather than reflects in a random medium to reconstruct the wavefield source and thereby directly avoid storing the forward wavefield data. Numerical examples show that compared with other migration algorithms and the traditional RTM, both methods can effectively reduce wavefield data storage as well as improve data-processing efficiency while ensuring imaging accuracy, thereby providing the means for high-efficiency and high-precision imaging of fractures and caves by boreholes. [ABSTRACT FROM AUTHOR]

To identify reflector fractures near borehole by using dipole-source reflected-shear-wave logging, we need to understand the relation between the amplitude of the reflected shear wave and the source radiation, borehole conditions, and attenuation owing to the surrounding formations. To assess the effect of these factors on the amplitude of the reflected waves, we first studied the radiation performance and radiation direction of the dipole source in fast, medium, and slow formations by using the asymptotic solution in the far field of the borehole. Then, the relation between the fracture parameters, and the reflected-shear-wave amplitude as well as the ratio of the reflected-shear-wave amplitude to the direct-wave amplitude (relative amplitude, RA) was evaluated by the three-dimensional finite-difference (3D FDTD) method. Finally, the fracture detection capability of the dipole reflected-shear-wave logging tool in different formations was analyzed by using the RA. The results suggest that the radiation amplitude of the SH-wave in the slow formation is weaker than those in the fast and medium formations, and the amplitude of the reflected shear wave is lower. However, the RA in the slow formation is close to or even greater than in the fast and medium formations, which means that dipole-source shear-wave logging has the same or even better fracture detection capability in the slow formation as in the fast and medium formations. In addition, when RA is small, there is a good correlation between the RA and the various fracture parameters in the different types of formation, which can be used in determining the lower limit of the fracture parameters identified by reflection logging. [ABSTRACT FROM AUTHOR]

Aim: Aldehyde dehydrogenase 2 (ALDH2) is a key enzyme that metabolizes acetaldehyde to acetic acid.ALDH2gene polymorphism modifies its activity and the mutation ofALDH2gene has been reported to be associated with the protection against ischemic stroke. However, the potential association of allelic variation ofALDH2with intracranial vascular stenosis and the clinical characteristics of ischemic stroke without coronary artery disease remains unclear.Methods: In this study, ischemic stroke patients were recruited, National Institutes of Health Stroke Scale scores were analyzed, intracranial arterial stenosis were evaluated by magnetic resonance angiography and gene typing ofALDH2was determined by polymerase chain reaction and sequencing.Results: We found that the rate of heavy drinking was significantly lower in theALDH2mutation group (*1/*2and*2/*2) than in wild-type group (*1/*1) (18.6% vs. 38.0%,p= 0.01). Plasma homocysteine (Hcy) levels were significantly different in the two groups (15.45 ± 6.39 vs. 13.14 ± 4.45,p= 0.015). TheALDH2mutation genotype was negatively correlated with severe intracranial vascular stenosis (OR, 0.34;p= 0.002), even after adjustment for high-density lipoprotein cholesterol, Hcy, and heavy drinking (adjusted OR, 0.44;p= 0.03).Conclusion:ALDH2*2could be a protective factor and negative predictor for severe intracranial vascular stenosis in ischemic stroke in Han Chinese. [ABSTRACT FROM PUBLISHER]

Fracture identification is important for the evaluation of carbonate reservoirs. However, conventional logging equipment has small depth of investigation and cannot detect rock fractures more than three meters away from the borehole. Remote acoustic logging uses phase-controlled array-transmitting and long sound probes that increase the depth of investigation. The interpretation of logging data with respect to fractures is typically guided by practical experience rather than theory and is often ambiguous. We use remote acoustic reflection logging data and high-order finite-difference approximations in the forward modeling and prestack reverse-time migration to image fractures. First, we perform forward modeling of the fracture responses as a function of the fracture-borehole wall distance, aperture, and dip angle. Second, we extract the energy intensity within the imaging area to determine whether the fracture can be identified as the formation velocity is varied. Finally, we evaluate the effect of the fracture-borehole distance, fracture aperture, and dip angle on fracture identification. [ABSTRACT FROM AUTHOR]

Vuggy reservoirs are the most common, albeit important heterogeneous carbonate reservoirs in China. However, saturation calculations using logging data are not well developed, whereas Archie method is more common. In this study, electrical conduction in a vuggy reservoir is theoretically analyzed to establish a new saturation equation for vuggy reservoirs. We found that vugs have a greater effect on saturation than resistivity, which causes inflection in the rock-electricity curve. Using single-variable experiments, we evaluated the effects of vug size, vug number, and vug distribution on the rock-electricity relation. Based on the general saturation model, a saturation equation for vuggy reservoirs is derived, and the physical significance of the equation parameters is discussed based on the seepage-electricity similarity. The equation parameters depend on the pore structure, and vugs and matrix pore size distribution. Furthermore, a method for calculating the equation parameters is proposed, which uses nuclear magnetic resonance (NMR) data to calculate the capillary pressure curve. Field application of the proposed equation and parameter derivation method shows good match between calculated and experimental results, with an average absolute error of 5.8%. [ABSTRACT FROM AUTHOR]

Phytochemical analysis of isolates from the aerial parts of Clausena lansium Lour. Skeels (Rutaceae) led to the identification of 14 alkaloids, including two indole alkaloids (1 and 2), one quinoline alkaloid (3), two pyridine alkaloids (4 and 5), four carbazole alkaloids (6 – 9) and five amides alkaloids (10 – 14). The phytochemical structures of the alkaloids were established by means of NMR and MS spectral analyses. Compounds (4 , 5 , 14) were three new natural products, while 1 – 3 and 10 were firstly reported from the genus Clausena and 8 and 9 were isolated from this species for the first time. The chemotaxonomic significance of these isolated alkaloids has also been discussed. All the isolated alkaloids were tested for their cytotoxic activity against Hela cancer cell line. Among them, four carbazole alkaloids 6 – 9 exhibited weak cytotoxicity with IC 50 values ranging from 69.31 to 138.32 μ M. • 14 alkaloids were isolated from the aerial parts of Clausena lansium Lour. Skeels (Rutaceae). • The chemotaxonomic significance of these isolated alkaloids has also been discussed. • Compounds 6 – 9 exhibited weak cytotoxicity with IC 50 values ranging from 69.31 to 138.32 μ M. [ABSTRACT FROM AUTHOR]