Fluid identification and tight oil layer classification for the southwestern Mahu Sag,Junggar Basin using NMR logging-based spectrum decomposition

The intricate distribution of oil and water in tight rocks makes pinpointing oil layers challenging.While conventional identification methods offer potential solutions,their limited accuracy precludes them from being effective in their applications to unconventional reservoirs.This study employed nuclear magnetic resonance(NMR)spectrum decomposition to dissect the NMR T_(2)spectrum into multiple subspectra.Furthermore,it employed laboratory NMR experiments to ascertain the fluid properties of these sub-spectra,aiming to enhance identification accuracy.The findings indicate that fluids of distinct properties overlap in the T_(2)spectra,with bound water,movable water,bound oil,and movable oil appearing sequentially from the low-value zone to the high-value zone.Consequently,an oil layer classification scheme was proposed,which considers the physical properties of reservoirs,oil-bearing capacity,and the characteristics of both mobility and the oil-water two-phase flow.When applied to tight oil layer identification,the scheme's outcomes align closely with actual test results.A horizontal well,deployed based on these findings,has produced high-yield industrial oil flow,underscoring the precision and dependability of this new approach.

Thin Layer Identification of Jiedu Shengxue Granules and Determination of Notoginsenoside R1 Content

[Objectives]To establish the quality standard of hospital preparation Jiedu Shengxue granules.[Methods]Scleromitrion diffusum and Prunella vulgaris in Jiedu Shengxue granules were qualitatively identified by thin layer chromatography(TLC).A high performance liquid chromatography(HPLC)was established to determine the content of notoginsenoside R1 in the granule.[Results]The traditional Chinese medicinal materials in Jiedu Shengxue granules could be identified by TLC,and the characteristic spots were stable and clear.Notoginsenoside R1 had a good linear relationship in the range of 10.45-104.5μg/mL,with an average recovery of 98.52%and RSD=2.36%.[Conclusions]TLC and HPLC,as the quality control methods of Jiedu Shengxue granules,have high accuracy and good repeatability,which lays a foundation for the quality control of this mixture.

A Cross Layer Protocol for Fast Identification of Blocked Tags in Large-Scale RFID Systems

Blocker tag attack is one of the denial-of-service(DoS)attacks that threatens the privacy and security of RFID systems.The attacker interferes with the blocked tag by simulating a fake tag with the same ID,thus causing a collision of message replies.In many practical scenarios,the number of blocked tags may vary,or even be small.For example,the attacker may only block the important customers or high-value items.To avoid the disclosure of privacy and economic losses,it is of great importance to fast pinpoint these blocked ones.However,existing works do not take into account the impact of the number of blocked tags on the execution time and suffer from incomplete identification of blocked tags,long identification time or privacy leakage.To overcome these limits,we propose a cross layer blocked tag identification protocol(CLBI).CLBI consists of multiple rounds,in which it enables multiple unblocked tags to select one time slot and concurrently verify them by using tag estimation in physical layer.Benefiting from the utilization of most collision slots,the execution time can be greatly reduced.Furthermore,for efficient identification of blocked tags under different proportions,we propose a hybrid protocol named adaptive cross layer blocked tag identification protocol(A-CLBI),which estimates the remaining blocked tag in each round and adjusts the identification strategy accordingly.Extensive simulations show that our protocol outperforms state-of-the-art blocked tags identification protocol.

Auto Identification of Rolling Layers in Roller-Compacted Concrete Dam

A scheme for identifying rolling layers in roller-compacted concrete (RCC) dam automatically was presented. First, a conceptual model was developed. Second, by using a computational geometry method, the auto identification of rolling layers and auto matching between rolling compaction machines and rolling layers were realized based on spatial control points. An application to the construction of Guandi RCC dam showed that the auto identification of rolling layers played an important role in ensuring the engineering quality.

Identification of Tibetan and Qiang Edible and Medicinal Herbs Cardamine tangutorum and Cardamine macrophylla

[Objectives]To study the original plants,characters,tissue structure,powder characteristics and thin-layer chromatography(TLC)characteristics of Cardamine tangutorum and Cardamine macrophylla as Tibetan and Qiang edible and medicinal herbs,and to provide the basis for the identification of C.tangutorum and C.macrophylla.[Methods]The identification of C.macrophyll and C.tangutorum was carried out by original plant identification,character identification,microscopic identification and TLC identification.[Results]C.tangutorum and C.macrophylla can be distinguished according to the shape of rhizome and stem,the difference of stem leaves and leaflets,and the difference of flower color;there is no obvious difference between the characteristics of the shape and the powder;the thin layer chromatography shows that in the thin layer chromatography of C.tangutorum and C.macrophylla,spots with the same color are shown on the corresponding positions of the ground part and the reference substance quercetin;the underground part and the position corresponding to the reference substanceβ-sitosterol all show the same color spots.[Conclusions]This study provides a reference for the identification of C.tangutorum and C.macrophylla.

Identification of Citric Acid in Wuhuang Oral Liquid by Thin Layer Chromatography

[Objectives] To screen the identification conditions of citric acid in Wuhuang Oral Liquid by thin layer chromatography,and establish the quality control method for citric acid in Wuhuang Oral Liquid.[Methods] Different treatment methods were adopted for test sample,developing agent,and drying time,thin layer chromatography separation condition and spot definition were taken as indicators to conduct experiment,to select optimal thin layer identification method. [Results] Methanol was used as the extraction solvent,ultrasonic treatment,ether extraction,dissolution by anhydrous ethanol as treatment conditions of test sample; upper solution of butyl acetate-formic acid-water(4 ∶ 2 ∶ 2) after placing one hour was taken as developing agent; 0. 1% bromocresol green(BCG) as the developer; when developing the color in 3 hours after development,in thin layer chromatograph,there appeared the same strip in the same position of test sample of Wuhuang ORAL Liquid and control substance,no obvious trailing phenomenon,and the color was uniform and clear.[Conclusions]The thin layer chromatography identification conditions can be used as the method for quality control of Wuhuang Oral Liquid.

An Improved SPSA Algorithm for System Identification Using Fuzzy Rules for Training Neural Networks

Simultaneous perturbation stochastic approximation （SPSA） belongs to the class of gradient-free optimization methods that extract gradient information from successive objective function evaluation. This paper describes an improved SPSA algorithm, which entails fuzzy adaptive gain sequences, gradient smoothing, and a step rejection procedure to enhance convergence and stability. The proposed fuzzy adaptive simultaneous perturbation approximation （FASPA） algorithm is particularly well suited to problems involving a large number of parameters such as those encountered in nonlinear system identification using neural networks （NNs）. Accordingly, a multilayer perceptron （MLP） network with popular training algorithms was used to predicate the system response. We found that an MLP trained by FASPSA had the desired accuracy that was comparable to results obtained by traditional system identification algorithms. Simulation results for typical nonlinear systems demonstrate that the proposed NN architecture trained with FASPSA yields improved system identification as measured by reduced time of convergence and a smaller identification error.

Pharmacognosy Identification of Xiaohuangcao (Dendrobium loddigesi Rolfe)

[Objectives]Pharmacognosy identification was performed on Xiaohuangcao ( Dendrobium loddigesi Rolfe).[Methods]The medicinal materials were identified through original plants,characters,microscopic structure and thin-layer identification characteristics.[Results]D.loddigesi has obvious plant morphology,characters,microscopic structure and thin-layer identification characteristics.The stem of Xiaohuangcao is slender and cylindrical,and the surface is golden yellow;and the fiber bundles outside the vascular bundles are crescent-shaped or semi-circular in the stem transection.For the powder,crystal fiber can be observed;the vascular bundles are embedded with siliceous block cells;and there are more starch grains.In the thin layer chromatography,petroleum ether-ethyl acetate-butanone-glacial acetic acid (8.5∶ 3.5∶ 1.5∶ 5 d) was used as a developing solvent,and 10% sulfuric acid ethanol solution was used as a color developing agent.[Conclusions]The research results provide reference for the application of the medicinal material and the formulation of its related quality standards.

Quantitative evaluation methods for waterflooded layers of conglomerate reservoir based on well logging data

The rapid changing near source, multi-stream depositional environment of conglomerate reservoirs leads to severe heterogeneity, complex lithology and physical properties, and large changes of oil layer resistivity. Quantitative evaluation of water-flooded layers has become an important but difficult focus for secondary development of oilfields. In this paper, based on the analysis of current problems in quantitative evaluation of water-flooded layers, the Kexia Group conglomerate reservoir of the Sixth District in the Karamay Oilfield was studied. Eight types of conglomerate reservoir lithology were identified effectively by a data mining method combined with the data from sealed coring wells, and then a multi-parameter model for quantitative evaluation of the water-flooded layers of the main oil-bearing lithology was developed. Water production rate, oil saturation and oil productivity index were selected as the characteristic parameters for quantitative evaluation of water-flooded layers of conglomerate reservoirs. Finally, quantitative evaluation criteria and identification rules for water-flooded layers of main oil-bearing lithology formed by integration of the three characteristic parameters of water-flooded layer and undisturbed formation resistivity. This method has been used in evaluation of the water-flooded layers of a conglomerate reservoir in the Karamay Oilfield and achieved good results, improving the interpretation accuracy and compliance rate. It will provide technical support for avoiding perforation of high water-bearing layers and for adjustment of developmental programs.

Improvement of X-Band Polarization Radar Melting Layer Recognition by the Bayesian Method and ITS Impact on Hydrometeor Classification

Using melting layer(ML)and non-melting layer(NML)data observed with the X-band dual linear polarization Doppler weather radar(X-POL)in Shunyi,Beijing,the reflectivity(ZH),differential reflectivity(ZDR),and correlation coefficient(CC)in the ML and NML are obtained in several stable precipitation processes.The prior probability density distributions(PDDs)of the ZH,ZDR and CC are calculated first,and then the probabilities of ZH,ZDR and CC at each radar gate are determined(PBB in the ML and PNB in the NML)by the Bayesian method.When PBB>PNB the gate belongs to the ML,and when PBB<PNB the gate belongs to the NML.The ML identification results with the Bayesian method are contrasUsing melting layer(ML)and non-melting layer(NML)data observed with the X-band dual linear polarization Doppler weather radar(X-POL)in Shunyi,Beijing,the reflectivity(ZH),differential reflectivity(ZDR),and correlation coefficient(CC)in the ML and NML are obtained in several stable precipitation processes.The prior probability density distributions(PDDs)of the ZH,ZDR and CC are calculated first,and then the probabilities of ZH,ZDR and CC at each radar gate are determined(PBB in the ML and PNB in the NML)by the Bayesian method.When PBB>PNB the gate belongs to the ML,and when PBB<PNB the gate belongs to the NML.The ML identification results with the Bayesian method are contrasted under the conditions of the independent PDDs and joint PDDs of the ZH,ZDR and CC.The results suggest that MLs can be identified effectively,although there are slight differences between the two methods.Because the values of the polarization parameters are similar in light rain and dry snow,it is difficult for the polarization radar to distinguish them.After using the Bayesian method to identify the ML,light rain and dry snow can be effectively separated with the X-POL observed data.ted under the conditions of the independent PDDs and joint PDDs of the ZH,ZDR and CC.The results suggest that MLs can be identified effectively,although there are slight differences between the two methods.Because the values of the polarization parameters are similar in light rain and dry snow,it is difficult for the polarization radar to distinguish them.After using the Bayesian method to identify the ML,light rain and dry snow can be effectively separated with the X-POL observed data.

VIBRATION CONTROL OF FLUID-FILLED PRISMATIC SHELL WITH ACTIVE CONSTRAINED LAYER DAMPING TREATMENTS

Active constrained layer damping （ACLD） combines the simplicity and reliability of passive damping with the light weight and high efficiency of active actuators to obtain high damping over a wide frequency band. A fluid-filled prismatic shell is set up to investigate the validity and efficiency of ACLD treatments in the case of fluid-structure interaction. By using state subspace identification method, modal parameters of the ACLD system are identified and a state space model is established subsequently for the design of active control laws. Experiments are conducted to the fluid-filled prismatic shell subjected to random and impulse excitation, respectively, For comparison, the shell model without fluid interaction is experimented as well. Experimental results have shown that the ACLD treatments can suppress vibration of the fluid-free and fluid-filled prismatic shell effectively. Under the same control gain, vibration attenuation is almost the same in both cases.

A Physical Layer Network Coding Based Tag Anti-Collision Algorithm for RFID System

In RFID(Radio Frequency IDentification)system,when multiple tags are in the operating range of one reader and send their information to the reader simultaneously,the signals of these tags are superimposed in the air,which results in a collision and leads to the degrading of tags identifying efficiency.To improve the multiple tags’identifying efficiency due to collision,a physical layer network coding based binary search tree algorithm(PNBA)is proposed in this paper.PNBA pushes the conflicting signal information of multiple tags into a stack,which is discarded by the traditional anti-collision algorithm.In addition,physical layer network coding is exploited by PNBA to obtain unread tag information through the decoding operation of physical layer network coding using the conflicting information in the stack.Therefore,PNBA reduces the number of interactions between reader and tags,and improves the tags identification efficiency.Theoretical analysis and simulation results using MATLAB demonstrate that PNBA reduces the number of readings,and improve RFID identification efficiency.Especially,when the number of tags to be identified is 100,the average needed reading number of PNBA is 83%lower than the basic binary search tree algorithm,43%lower than reverse binary search tree algorithm,and its reading efficiency reaches 0.93.

Study of Cuscuta chinensis Lam. in Nuhuang Fuzheng Oral Liquid by Thin Layer Chromatography

[Objectives] To better control the quality of Nuhuang Fuzheng Oral Liquid and study the main component Cuscuta chinensis Lam.by Thin Layer Chromatography. [Methods] Through changing the treatment methods of the test sample solution,proportion of the developing solvent and sample application volume,taking the spot resolution,definition,and Rf value,optimal Thin Layer Chromatography conditions were screened for Cuscuta chinensis Lam. [Results] After the test sample solution passing the neutral alumina column,it was extracted two times using the ethyl acetate. Methanol was added to dissolve. Benzene-ethyl acetate-formic acid( 5∶5∶2.5) was used as developing solvent.And ammonia fumigation was carried out to develop color. In the thin layer chromatograph obtained through these conditions,Nuhuang Fuzheng Oral Liquid test sample solution showed the same stripe in the same position of the control drug chromatogram and there was no obvious tailing phenomenon and the spot was clear. [Conclusions] The thin layer chromatography identification conditions can be used as the method for quality control of Cuscuta chinensis Lam. in Nuhuang Fuzheng Oral Liquid.

Thin Layer Chromatography Screening for Glycyrrhiza uralensis

[Objectives] To establish a simple and rapid,specific and reproducible thin layer chromatography( TLC) method,and accordingly establish a thin layer identification method for quality control of Glycyrrhiza uralensis. [Methods] According to the physical and chemical properties,components of Glycyrrhiza uralensis were identified by thin layer chromatography. According to Veterinary Pharmacopoeia of the People's Republic of China 2010( Volume Ⅱ) and related literature report,the thin layer chromatography identification method was studied and improved for Glycyrrhiza uralensis.[Results] When the preparation method for test sample solution was 6g Glycyrrhiza uralensis added with 30 mL saturated n-butanol,ultrasonic processing 20 min,filtered,filtrate dried,added 3 mL methanol and obtained Glycyrrhiza uralensis test sample solution. Then,chloroform-methanol-formic acid-ethyl acetate( 10∶ 3∶ 2∶ 3) as developing solvent,clear spot with high degree of separation and reproducibility could be obtained,and can be used for thin layer chromatography identification of ammonium glycyrrhetate in Glycyrrhiza uralensis.[Conclusions] The modified method omitted the step of ether treatment of samples,and directly adopted saturated n-butanol to extract components. It does not influence the detection of chromatographic spots,and solves the issue of sample gelatinizing sticking and filtration,simplifies the test process,and reduces the harm to human body.

A Semi-Vectorial Morphological Segmentation Multi-Component Images of Coumarins on Thin Layer Combined with Laser for Better Separation

In this work, we propose an approach for the separation of coumarins from thin-layer morphological segmentation based on the acquisition of multicomponent images integrating different types of coumarins. The first step is to make a segmentation by region, by thresholding, by contour, etc. of each component of the digital image. Then, we proceeded to the calculations of parameters of the regions such as the color standard deviation, the color entropy, the average color of the pixels, the eccentricity from an algorithm on the matlab software. The mean color values atR = 91.20 in red, atB = 213.21 in blue showed the presence of samidin in the extract. The color entropy values HG = 5.25 in green and HB = 4.04 in blue also show the presence of visnadine in the leaves of Desmodium adscendens. These values are used to consolidate the database of separation and discrimination of the types of coumarins. The relevance of our coumarin separation or coumarin recognition method has been highlighted compared to other methods, such as the one based on the calculation of frontal ratios which cannot discriminate between two coumarins having the same frontal ratio. The robustness of our method is proven with respect to the separation and identification of some coumarins, in particular samidin and anglicine.

炒僵蚕鉴别方法研究

目的:基于显微鉴别技术、微量升华技术和薄层色谱技术,建立炒僵蚕饮片的鉴别方法。方法:依据显微鉴别法,对炒僵蚕粉末的显微特征进行描述;采用微量升华法,对炒僵蚕升华物结晶状态进行描述;采用薄层色谱法,僵蚕对照药材和伪品为对照,对炒僵蚕进行薄层色谱鉴别。结果:炒僵蚕粉末呈黄褐色,在显微镜下清晰可见菌丝体、体壁碎片、刚毛、未消化的桑叶组织、草酸钙簇晶、草酸钙方晶及导管等结构,与僵蚕对照药材类似;炒僵蚕的升华物呈霜花状、羽状结晶,与僵蚕对照药材类似;TLC图中,斑点清晰、专属性好。结论:该方法快速、易操作、专属性好,可作为炒僵蚕饮片的鉴别方法,并为提高鉴别标准提供参考。

基于灰色关联度分析-极限学习机的低阻油层及水淹层测井识别——以渤海P区块馆陶组为例

历经近20的开发,渤海P区块进入高含水期,馆陶组发育的大量低阻油层与水淹层在测井曲线形态上差异不明显。为了精确进行水淹层识别以及水淹层等级划分,采用了机器学习算法。首先采用灰色关联度分析,筛选低阻油层和水淹层识别的敏感参数曲线;其次构建了极限学习机水淹层识别模型,对模型进行训练,获取最优参数。将其应用于实际资料处理,结果表明,基于灰色关联度分析极限学习机的低阻油层及水淹层测井识别方法对低阻油层与水淹层的预测精度较高,符合率达89.3%,远远优于未经过灰色关联度分析筛选的预测结果,具有实际应用价值。

风化店地区低阻油层成因分析及识别

针对风化店地区孔店组低阻油层识别困难、测井解释难度大的特点,充分利用测井、录井等资料研究分析低阻油层形成原因。研究认为该区低阻油层受黏土矿物含量、地层水矿化度、薄互层三个方面影响。在系统分析储层四性关系的基础上,分区块、分层位建立了储层参数模型和高精度、适用性强的油、水解释图版标准,准确识别低阻油层,及时应用于现场生产中,取得了明显的效果,为进一步开展老油田低阻油层识别、挖潜上产提供了借鉴和技术保障。

基于多层全连接神经网络的6C地震波极化向量识别研究

利用机器学习原理,提出一种基于多层全连接(multi-layer fully connected, MFC)神经网络的六分量(six-component, 6C)地震波极化向量识别方法。首先利用6C地震波各波型极化向量数学模型和一系列仿真参数得到5种波型和噪声波型各5 000个极化向量数据集,然后随机选取其中5 000个作为测试集,其余划分为训练集,进行MFC神经网络与支持向量机(support vector machine, SVM)的综合辨识性能对比实验。结果表明,MFC神经网络模型识别5种极化向量类型(SH波和Love波视为一类)和6种极化向量类型的效果均显著优于SVM模型,平均识别率分别达到99.786%和87.940%。

一种基于PSO-ELM的低渗透砂岩水淹层测井识别方法

水淹层测井识别对油田开发方案部署及提高采收率有着重要意义。新疆陆梁油田作业区某区块油层水淹类型主要为污水水淹,测井响应特征复杂多变,传统识别图版方法难以对水淹层有效识别。文中基于测井、地质、试油等资料,在水淹层测井响应特征分析基础上,提出了一种利用改进粒子群优化算法(Particle Swarm Optimization,PSO)及极限学习机(Extreme Learning Machine,ELM)的水淹层识别方法。首先,利用相关系数优选6个主控因素:RD,RS,GR,SP,DEN,AC。其次,采用改进粒子群算法对极限学习机模型进行参数寻优;最后,利用优化后的模型对研究区水淹层进行预测。结果表明,利用PSO-ELM模型识别水淹层,识别符合率达到91.7%,应用效果优于ELM模型及传统识别图版,为水淹层测井识别提供了新思路。