Seismic low-frequency-based calculation of reservoir fluid mobility and its applications

Low frequency content of seismic signals contains information related to the reservoir fluid mobility. Based on the asymptotic analysis theory of frequency-dependent reflectivity from a fluid-saturated poroelastic medium, we derive the computational implementation of reservoir fluid mobility and present the determination of optimal frequency in the implementation. We then calculate the reservoir fluid mobility using the optimal frequency instantaneous spectra at the low-frequency end of the seismic spectrum. The methodology is applied to synthetic seismic data from a permeable gas-bearing reservoir model and real land and marine seismic data. The results demonstrate that the fluid mobility shows excellent quality in imaging the gas reservoirs. It is feasible to detect the location and spatial distribution of gas reservoirs and reduce the non-uniqueness and uncertainty in fluid identification.

Preparation of novel Ni-Ir/γ-Al_2O_3 catalyst via high-frequency cold plasma direct reduction process

The novel Ni-Ir/γ-Al2O3 catalyst, denoted as NIA-P, was prepared by high-frequency cold plasma direct reduction method under ambient conditions without thermal treatment, and the conventional sample, denoted as NIA-CR, was prepared by impregnation, thermal calcination, and then by H2 reduction method. The effects of reduction methods on the catalysts for ammonia decomposition were studied, and they were characterized by XRD, N2 adsorption, XPS, and H2-TPD. It was found that the plasma-reduced NIA-P sample showed a better catalytic performance, over which ammonia conversion was 68.9%, at T = 450℃, P = 1 atm, and GHSV = 30, 000 h^-1. It was 31.7% higher than that of the conventional NIA-CR sample. XRD results showed that the crystallite size decreased for the sample with plasma reduction, and the dispersion of active components was improved. There were more active components on the surface of the NIA-P sample from the XPS results. This effect resulted in the higher activity for decomposition of ammonia. Meanwhile, the plasma process significantly decreased the time of preparing catalyst.

Reverse time migration based on normalized wavefield decomposition imaging condition

With the increasing complexity of prospecting objectives,reverse time migration( RTM) has attracted more and more attention due to its outstanding imaging quality. RTM is based on two-way wave equation,so it can avoid the limits of angle in traditional one-way wave equation migration,image reverse branch,prism waves and multi-reflected wave precisely and obtain accurate dynamic information. However,the huge demands for storage and computation as well as low frequency noises restrict its wide application. The normalized cross-correlation imaging conditions based on wave field decomposition are derived from traditional cross-correlation imaging condition,and it can eliminate the low-frequency noises effectively and improve the imaging resolution. The practical procedure includes separating source and receiver wave field into one-way components respectively,and conducting cross-correlation imaging condition to the post-separated wave field. In this way,the resolution and precision of the imaging result will be promoted greatly.

Hippocampal High-Frequency Stimulation Inhibites the Progression of Rapid Kindling-Induced Seizure in Rats

Epilepsy is one of the most common serious neurological disorders. Pharmacoresistant epilepsy patients are poorly controlled or their seizures are refractory to drug treatment. Resective surgery is frequently a promising therapy in this population, however, not all the patients meet the eligibility criteria for the surgical treatment. Deep brain stimulation has been investigated in clinical studies and animal studies as an alternative treatment, but the optimal stimulation parameters remain an issue. The present study was designed to investigate the effect of unilateral high-frequency stimulation (HFS) of hippocampus on seizure development by using the hippocampal rapid kindling method (hRK) in rats, and compared the results with those of low-frequency stimulation previously published by our group. We used male Wistar rats implanted with electrodes in the ventral hippocampus. All rats underwent hRK (biphasic square wave pulses, 20 Hz for 10 seconds) during three consecutive days (twelve stimulations per day). The control group (hRK;n = 7) received only RK stimulus, while the treated group (HFS-hRK;n = 9) received also HFS (biphasic square wave pulses, 130 Hz for 30 seconds) immediately before the RK stimulus, during three consecutive days. At the end of behavioral testing 78% (p 0.01) of the animals receiving HFS treatment were still not fully kindled staying in stages 0 -III (p 0.01). HFS group needed a higher number of stimulations to achieve stage III (p 0.05) with respect to control group. However, no significant differences in the cumulative daily afterdischarge duration were observed. HFS did not present significant differences compared with LFS in any of studied parameters. The findings suggest that unilateral HFS applied on hippocampus effectively inhibited the epileptogenic process induced by hippocampal rapid kindling. According to the comparative results about hippocampal rapid kindled animals stimulated with HFS and LFS (5 Hz), we found no conclusive information on which treatment is most efficient.

Contribution of glial cells to the neuroprotective effects triggered by repetitive magnetic stimulation:a systematic review

Repetitive transcranial magnetic stimulation has been increasingly studied in different neurological diseases,and although most studies focus on its effects on neuronal cells,the contribution of nonneuronal cells to the improvement trigge red by repetitive transcranial magnetic stimulation in these diseases has been increasingly suggested.To systematically review the effects of repetitive magnetic stimulation on non-neuronal cells two online databases.Web of Science and PubMed were searched fo r the effects of high-frequency-repetitive transcranial magnetic stimulation,low-frequencyrepetitive transcranial magnetic stimulation,intermittent theta-bu rst stimulation,continuous thetaburst stimulation,or repetitive magnetic stimulation on non-neuronal cells in models of disease and in unlesioned animals or cells.A total of 52 studies were included.The protocol more frequently used was high-frequency-repetitive magnetic stimulation,and in models of disease,most studies report that high-frequency-repetitive magnetic stimulation led to a decrease in astrocyte and mic roglial reactivity,a decrease in the release of pro-inflammatory cyto kines,and an increase of oligodendrocyte proliferation.The trend towards decreased microglial and astrocyte reactivity as well as increased oligodendrocyte proliferation occurred with intermittent theta-burst stimulation and continuous theta-burst stimulation.Few papers analyzed the low-frequency-repetitive transcranial magnetic stimulation protocol,and the parameters evaluated were restricted to the study of astrocyte reactivity and release of pro-inflammatory cytokines,repo rting the absence of effects on these paramete rs.In what concerns the use of magnetic stimulation in unlesioned animals or cells,most articles on all four types of stimulation reported a lack of effects.It is also important to point out that the studies were developed mostly in male rodents,not evaluating possible diffe rential effects of repetitive transcranial magnetic stimulation between sexes.This systematic review supports that thro ugh modulation of glial cells repetitive magnetic stimulation contributes to the neuroprotection or repair in various neurological disease models.Howeve r,it should be noted that there are still few articles focusing on the impact of repetitive magnetic stimulation on non-neuronal cells and most studies did not perform in-depth analyses of the effects,emphasizing the need for more studies in this field.

Eye on the Sky: A UAP Research and Field Study off New York’s Long Island Coast

A ten-month field research study was meticulously conducted at Robert Moses State Park (RMSP) on the south shore of Long Island, NY. The objective was to determine if aerial phenomena of an unknown nature exist over a coastal location and to characterize their properties and behaviors. Primary and secondary field observation methods were utilized in this data-centric study. Forensic engineering principles and methodologies guided the study. The challenges set forward were object detection, observation, and characterization, where multispectral electro-optical devices and radar were employed due to limited visual acuity and intermittent presentation of the phenomena. The primary means of detection utilized a 3 cm X-band radar operating in two scan geometries, the X- and Y-axis. Multispectral electro-optical devices were utilized as a secondary means of detection and identification. Data was emphasized using HF and LF detectors and spectrum analyzers incorporating EM, ultrasonic, magnetic, and RF field transducers to record spectral data in these domains. Data collection concentrated on characterizing VIS, NIR, SWIR, LWIR, UVA, UVB, UVC, and the higher energy spectral range of ionizing radiation (alpha, beta, gamma, and X-ray) recorded by Geiger-Müller counters as well as special purpose semiconductor diode sensors.

High Order Deep Domain Decomposition Method for Solving High Frequency Interface Problems

This paper proposes a high order deep domain decomposition method(HOrderDeepDDM)for solving high-frequency interface problems,which combines high order deep neural network(HOrderDNN)with domain decomposition method(DDM).The main idea of HOrderDeepDDM is to divide the computational domain into some sub-domains by DDM,and apply HOrderDNNs to solve the high-frequency problem on each sub-domain.Besides,we consider an adaptive learning rate annealing method to balance the errors inside the sub-domains,on the interface and the boundary during the optimization process.The performance of HOrderDeepDDM is evaluated on high-frequency elliptic and Helmholtz interface problems.The results indicate that:HOrderDeepDDM inherits the ability of DeepDDM to handle discontinuous interface problems and the power of HOrderDNN to approximate high-frequency problems.In detail,HOrderDeepDDMs(p>1)could capture the high-frequency information very well.When compared to the deep domain decomposition method(DeepDDM),HOrderDeepDDMs(p>1)converge faster and achieve much smaller relative errors with the same number of trainable parameters.For example,when solving the high-frequency interface elliptic problems in Section 3.3.1,the minimum relative errors obtained by HOrderDeepDDMs(p=9)are one order of magnitude smaller than that obtained by DeepDDMs when the number of the parameters keeps the same,as shown in Fig.4.

Effects of different frequencies of repetitive transcranial magnetic stimulation on the recovery of upper limb motor dysfunction in patients with subacute cerebral infarction

Studies have confirmed that low-frequency repetitive transcranial magnetic stimulation can decrease the activity of cortical neurons, and high-frequency repetitive transcranial magnetic stimulation can increase the excitability of cortical neurons. However, there are few studies concerning the use of different frequencies of repetitive transcranial magnetic stimulation on the recovery of upper-limb motor function after cerebral infarction. We hypothesized that different frequencies of repetitive transcranial magnetic stimulation in patients with cerebral infarction would produce different effects on the recovery of upper-limb motor function. This study enrolled 127 patients with upper-limb dysfunction during the subacute phase of cerebral infarction. These patients were randomly assigned to three groups. The low-frequency group comprised 42 patients who were treated with 1 Hz repetitive transcranial magnetic stimulation on the contralateral hemisphere primary motor cortex （M1）. The high-frequency group comprised 43 patients who were treated with 10 Hz repetitive transcranial magnetic stimulation on ipsilateral M1. Finally, the sham group comprised 42 patients who were treated with 10 Hz of false stimulation on ipsilateral M1. A total of 135 seconds of stimulation was applied in the sham group and high-frequency group. At 2 weeks after treatment, cortical latency of motor-evoked potentials and central motor conduction time were significantly lower compared with before treatment. Moreover, motor function scores were significantly improved. The above indices for the low- and high-frequency groups were significantly different compared with the sham group. However, there was no significant difference between the low- and high-frequency groups. The results show that low- and high-frequency repetitive transcranial magnetic stimulation can similarly improve upper-limb motor function in patients with cerebral infarction.

A mathematical model of synaptotagmin 7 revealing functional importance of short-term synaptic plasticity

Synaptotagmin 7(Syt7), a presynaptic calcium sensor, has a significant role in the facilitation in shortterm synaptic plasticity: Syt7 knock out mice show a significant reduction in the facilitation. The functional importance of short-term synaptic plasticity such as facilitation is not well understood. In this study, we attempt to investigate the potential functional relationship between the short-term synaptic plasticity and postsynaptic response by developing a mathematical model that captures the responses of both wild-type and Syt7 knock-out mice. We then studied the model behaviours of wild-type and Syt7 knock-out mice in response to multiple input action potentials. These behaviors could establish functional importance of short-term plasticity in regulating the postsynaptic response and related synaptic properties. In agreement with previous modeling studies, we show that release sites are governed by non-uniform release probabilities of neurotransmitters. The structure of non-uniform release of neurotransmitters makes shortterm synaptic plasticity to act as a high-pass filter. We also propose that Syt7 may be a modulator for the long-term changes of postsynaptic response that helps to train the target frequency of the filter. We have developed a mathematical model of short-term plasticity which explains the experimental data.

Heart Rate Variability, Standard of Measurement, Physiological Interpretation and Clinical Use in Mountain Marathon Runners during Sleep and after Acclimatization at 3480 m

Fluctuations in autonomic cardiovascular regulation during exposure to high altitude may increase the risk of heart attack during waking and sleep. This study compared heart rate variability (HVR) and its components during sleep at low altitude and after 30 - 41 hours of acclimatization at high altitude (3480 m) in five mountain marathon runners controlled for diet, drugs, light-dark cycle and jet lag. In comparison to sea level, RR-intervals during sleep at high altitude decreased significantly (P 0.001). The significant increase in sympathetic autonomic cardiovascular modulation at high altitude protects against excessive oxygen deprivation during sleep. Increases in R-R intervals can require longer periods of acclimatization at3480 m to mitigate the effects of altitude/hypoxia on sympathetic tone, thus reducing cardiovascular distress at rest during waking and sleep and probably before during and after athletic performance at altitude.

Super Resolution Perception for Improving Data Completeness in Smart Grid State Estimation

The smart grid is an evolving critical infrastructure,which combines renewable energy and the most advanced information and communication technologies to provide more economic and secure power supply services.To cope with the intermittency of ever-increasing renewable energy and ensure the security of the smart grid,state estimation,which serves as a basic tool for understanding the true states of a smart grid,should be performed with high frequency.More complete system state data are needed to support high-frequency state estimation.The data completeness problem for smart grid state estimation is therefore studied in this paper.The problem of improving data completeness by recovering highfrequency data from low-frequency data is formulated as a super resolution perception(SRP)problem in this paper.A novel machine-learning-based SRP approach is thereafter proposed.The proposed method,namely the Super Resolution Perception Net for State Estimation(SRPNSE),consists of three steps:feature extraction,information completion,and data reconstruction.Case studies have demonstrated the effectiveness and value of the proposed SRPNSE approach in recovering high-frequency data from low-frequency data for the state estimation.

Simulation method of near-fault pulse-type ground motion

The two characteristics of near-fault ground motions, i.e., the forward directivity effect and permanent displacement effect, result in long period and large velocity pulse in the velocity time history and large step pulse in the displacement time history. Considering the two effects, a simple expression of continuous function for equivalent velocity pulse time history is presented in this paper. The equivalent pulse model, in which the pulse period, peak velocity and pulse shape are described by five parameters, is highly advantageous to fit and simulate the pulse-type velocity time history. The equivalent pulse model comprises only one low-frequency component while the high-frequency component of a pulse-type earthquake record cannot be considered. Based on 28 records of 11 earthquakes, the pulse frequency of pulse-type records is generally less than 1 Hz. Therefore the low-frequency component and high-frequency component are simulated respectively and combined them together to generate a pulse-type ground motion.

Experimental and numerical investigations on wave motions over platform reef-flat

Previous studies have shown that high-frequency(HF)waves,low-frequency(LF)waves and wave set-up coexist on shallow coral reef-flat and jointly contribute to potential floods and subsequent damages of infrastructures and islands on it.To better understand the reef-flat wave dynamics with incident waves and still water level,a wave-flume experiment was performed based on an idealized platform reef composed of a steep reef-face(1:4),a relatively mild reef-rim(1:14)and a horizontal reef-flat.Also,the non-hydrostatic phase-resolving model SWASH was validated against the experiment and then applied to further numerically investigate the effects of reef-rim topographic features on the reef-flat wave motions.The results show that incident waves of a larger wave height and a longer wave period can generate larger LF waves and wave set-up,thereby inducing greater HF waves on the reef-flat.Higher still water level can lead to larger HF waves but result in smaller wave set-up.In contrast to HF waves and wave set-up,LF waves are minimally affected by the still water level.A rim of milder slope and larger edge depth will induce smaller HF and LF waves and set-up on the reef-flat,and thus provide better protection for the reef-flat region.Furthermore,on the reef-flat,the ratio of HF significant wave height to water depth H_(s_h)/(h_(r)+η^(-))is approximately constant;the dimensionless LF significant wave height Hs_l/H_(s0) and the dimensionless wave set-upη^(-)/[T_(p)(gH_(s0))1/2]can be related to the inverse wave steepness parameter gT_(p)^(2)/H_(s0) and the relative reef-flat submergence(h_(r)+η^(-))/H_(s0) respectively.