Reservoir heterogeneity analysis using multi-directional textural attributes from deep learning-based enhanced acoustic impedance inversion:A study from Poseidon,NW shelf Australia

Reservoir heterogeneities play a crucial role in governing reservoir performance and management.Traditionally,detailed and inter-well heterogeneity analyses are commonly performed by mapping seismic facies change in the seismic data,which is a time-intensive task.Many researchers have utilized a robust Grey-level co-occurrence matrix(GLCM)-based texture attributes to map reservoir heterogeneity.However,these attributes take seismic data as input and might not be sensitive to lateral lithology variation.To incorporate the lithology information,we have developed an innovative impedance-based texture approach using GLCM workflow by integrating 3D acoustic impedance volume(a rock propertybased attribute)obtained from a deep convolution network-based impedance inversion.Our proposed workflow is anticipated to be more sensitive toward mapping lateral changes than the conventional amplitude-based texture approach,wherein seismic data is used as input.To evaluate the improvement,we applied the proposed workflow to the full-stack 3D seismic data from the Poseidon field,NW-shelf,Australia.This study demonstrates that a better demarcation of reservoir gas sands with improved lateral continuity is achievable with the presented approach compared to the conventional approach.In addition,we assess the implication of multi-stage faulting on facies distribution for effective reservoir characterization.This study also suggests a well-bounded potential reservoir facies distribution along the parallel fault lines.Thus,the proposed approach provides an efficient strategy by integrating the impedance information with texture attributes to improve the inference on reservoir heterogeneity,which can serve as a promising tool for identifying potential reservoir zones for both production benefits and fluid storage.

Long-Term Impacts of Tree Architectures and Branch Configurations on Tree Growth, Yield, Fruit Quality Attributes, and Leaf Minerals in “Aztec Fuji” Apple

Canopy and branch architectures in high-density orchards can be crucial in production and fruit quality. The influence of two canopy orientations (Upright and Tilted) in combination with two arm (branch) architectures (Shortened or Overlapped) on tree growth, yield components, fruit quality, and leaf mineral nutrients in an “Aztec Fuji” apple (Malus domestica Bork.) high-density orchard was studied over five years. Tilted trees with shortened arm configuration (TilShArm) always had significantly larger trunk cross-sectional area (TCSA) than Upright trees with an Overlapped arm configuration (UpOverArm) every year from 2012 to 2016. Trees with a TilShArm system had more cumulative fruit per tree than those with an Upright orientation. Trees with a tilted canopy (TilShArm and TilOverArm) tended to have higher yield per tree and yield per hectare than those with an upright system. Trees with a TilShArm system were more precocious and had more yield per tree than those with an upright canopy orientation in 2012. When values were polled over five years, trees with an upright canopy-shortened arm system (UpShArm) treatment had a lower biennial bearing index (BBI) than those with an upright canopy-overlapped system (UpOverArm). Trees receiving an arm shortening (UpShArm or TilShArm) configuration often had larger fruits than those with overlapped arms (UpOverArm and TilOverArm). Fruit from trees receiving an UpOverArm had higher fruit firmness than those from trees with other canopy-branch arrangements at harvest due to their smaller size. Fruit from trees with a TilShArm and TilOverArm had significantly higher water core and bitter pit but lower sunburn than trees with an upright canopy (UpShArm and UpOverArm). Leaves from trees with an UpOverArm canopy-branch configuration had the lowest leaf Ca but the highest leaf K and Fe concentrations among all treatments.

Machine learning for carbonate formation drilling: Mud loss prediction using seismic attributes and mud loss records

Due to the complexity and variability of carbonate formation leakage zones, lost circulation prediction and control is one of the major challenges of carbonate drilling. It raises well-control risks and production expenses. This research utilizes the H oilfield as an example, employs seismic features to analyze mud loss prediction, and produces a complete set of pre-drilling mud loss prediction solutions. Firstly, 16seismic attributes are calculated based on the post-stack seismic data, and the mud loss rate per unit footage is specified. The sample set is constructed by extracting each attribute from the seismic trace surrounding 15 typical wells, with a ratio of 8:2 between the training set and the test set. With the calibration results for mud loss rate per unit footage, the nonlinear mapping relationship between seismic attributes and mud loss rate per unit size is established using the mixed density network model.Then, the influence of the number of sub-Gausses and the uncertainty coefficient on the model's prediction is evaluated. Finally, the model is used in conjunction with downhole drilling conditions to assess the risk of mud loss in various layers and along the wellbore trajectory. The study demonstrates that the mean relative errors of the model for training data and test data are 6.9% and 7.5%, respectively, and that R2is 90% and 88%, respectively, for training data and test data. The accuracy and efficacy of mud loss prediction may be greatly enhanced by combining 16 seismic attributes with the mud loss rate per unit footage and applying machine learning methods. The mud loss prediction model based on the MDN model can not only predict the mud loss rate but also objectively evaluate the prediction based on the quality of the data and the model.

Aboveground biomass stocks of species-rich natural forests in southern China are influenced by stand structural attributes,species richness and precipitation

Forests,the largest terrestrial carbon sinks,play an important role in carbon sequestration and climate change mitigation.Although forest attributes and environmental factors have been shown to impact aboveground biomass,their influence on biomass stocks in species-rich forests in southern China,a biodiversity hotspot,has rarely been investigated.In this study,we characterized the effects of environmental factors,forest structure,and species diversity on aboveground biomass stocks of 30 plots(1 ha each) in natural forests located within seven nature reserves distributed across subtropical and marginal tropical zones in Guangxi,China.Our results indicate that forest aboveground biomass stocks in this region are lower than those in mature tropical and subtropical forests in other regions.Furthermore,we found that aboveground biomass was positively correlated with stand age,mean annual precipitation,elevation,structural attributes and species richness,although not with species evenness.When we compared stands with the same basal area,we found that aboveground biomass stock was higher in communities with a higher coefficient of variation of diameter at breast height.These findings highlight the importance of maintaining forest structural diversity and species richness to promote aboveground biomass accumulation and reveal the potential impacts of precipitation changes resulting from climate warming on the ecosystem services of subtropical and northern tropical forests in China.Notably,many natural forests in southern China are not fully stocked.Therefore,their continued growth will increase their carbon storage over time.

A risk assessment method considering risk attributes and work safety informational needs and its application

The technological revolution has spawned a new generation of industrial systems,but it has also put forward higher requirements for safety management accuracy,timeliness,and systematicness.Risk assessment needs to evolve to address the existing and future challenges by considering the new demands and advancements in safety management.The study aims to propose a systematic and comprehensive risk assessment method to meet the needs of process system safety management.The methodology first incorporates possibility,severity,and dynamicity(PSD)to structure the“51X”evaluation indicator system,including the inherent,management,and disturbance risk factors.Subsequently,the four-tier(risk point-unit-enterprise-region)risk assessment(RA)mathematical model has been established to consider supervision needs.And in conclusion,the application of the PSD-RA method in ammonia refrigeration workshop cases and safety risk monitoring systems is presented to illustrate the feasibility and effectiveness of the proposed PSD-RA method in safety management.The findings show that the PSD-RA method can be well integrated with the needs of safety work informatization,which is also helpful for implementing the enterprise's safety work responsibility and the government's safety supervision responsibility.

A Study on Multivariable Interactions Concerning Radar Cross Section Reduction through Geometric Attributes

This resolution 5 (25−1 factorial) study aimed to ascertain an understanding of the interactions between different geometries on the resulting Radar Cross Section (RCS) of a target. The results of the study are in line with the general understanding of the impact different geometries have on RCS but show that geometries can also influence the variance of measured RCS, and typical attributes that reduce RCS increase the variance of the measured RCS. Notably, an increased angle between the front face of a plate and the direction of the radar signal decreased RCS but increased the variance of the RCS measured.

Attributes of Domestic Spaces for Contemporary Habitation-A Secondary Publication

The domestic space can be defined as the sphere that articulates the needs for subjective containment and contextual stimuli.In this sense,questions arise about the indispensable attributes that spaces must possess for this articulation to take place adequately.Architecture,as the discipline in charge of satisfying the specific spatial needs of those who inhabit these spaces and,in a broader sense,as a concrete contribution to society,must address this relationship in all its complexity and generate concrete responses that incorporate the appropriate spatial attributes during the design processes.The design processes that shape living spaces confront this dialectic,and the manner in which they do so brings identity and character to them.It is believed that the higher the level of variables that are contemplated and weighted,the greater the adequacy of spaces to the changing dynamics of the people who inhabit them.This article focuses on a thorough analysis of these spatial attributes,in parallel to the definition of each one as a particular condition for design,based on their conceptualization,breakdown,and articulation.Conceptually,the following attributes are addressed:flexibility,adaptability,variability,versatility,multiplicity,plurality,integrality,gradualness,incrementality,progressiveness,independence,connectivity,intimacy,and privacy.Each of these attributes is valued as a contribution to creating adequate habitability in contextual terms,with consideration to possible integrations and combinations.

Research on the Influence of Anchor Attributes on Consumers’Online Behaviors in Social E-Commerce Platforms:The Moderating Effect of Platform Contextual Factors

As e-commerce continues to mature,the advantages of live streaming within the industry have become increasingly apparent,offering significant growth opportunities.Social e-commerce platforms,which are user-centered,integrate social networks with e-commerce by leveraging social interactions to drive product sales and enhance the overall consumer shopping experience.This type of e-commerce fosters engagement and promotes products by merging online communities with shopping behavior,creating a more interactive and dynamic marketplace.It not only retains the traditional e-commerce trading and marketing functions but also adds a social dimension,making live stream anchors crucial figures connecting consumers with products.These anchors can attract consumers with their appearance and charm,and use their expertise on live streaming platforms to guide consumers by recommending live content.They can also interact with their audiences and potentially influence them to purchase the recommended goods.It is evident that the attributes of anchors in live streaming rooms significantly impact consumers’online behavior.Therefore,researching how platform contextual factors regulate consumers’online behavior is of great practical significance.This study employs multilevel regression analysis to support its hypotheses using data.The findings indicate that contextual factors of the platform significantly influence online behavior,enhancing the positive relationship between user attachment and online activities.

Quantitative evaluation of gas hydrate reservoir by AVO attributes analysis based on the Brekhovskikh equation

AVO (Amplitude variation with offset) technology is widely used in gas hydrate research. BSR (Bottom simulating reflector), caused by the huge difference in wave impedance between the hydrate reservoir and the underlying free gas reservoir, is the bottom boundary mark of the hydrate reservoir. Analyzing the AVO attributes of BSR can evaluate hydrate reservoirs. However, the Zoeppritz equation which is the theoretical basis of conventional AVO technology has inherent problems: the Zoeppritz equation does not consider the influence of thin layer thickness on reflection coefficients;the approximation of the Zoeppritz equation assumes that the difference of wave impedance between the two sides of the interface is small. These assumptions are not consistent with the occurrence characteristics of natural gas hydrate. The Brekhovskikh equation, which is more suitable for thin-layer reflection coefficient calculation, is used as the theoretical basis for AVO analysis. The reflection coefficients calculated by the Brekhovskikh equation are complex numbers with phase angles. Therefore, attributes of the reflection coefficient and its phase angle changing with offset are used to analyze the hydrate reservoir's porosity, saturation, and thickness. Finally, the random forest algorithm is used to predict the reservoir porosity, hydrate saturation, and thickness of the hydrate reservoir. In the synthetic data, the inversion results based on the four attributes of the Brekhovskikh equation are better than the conventional inversion results based on the two attributes of Zoeppritz, and the thickness can be accurately predicted. The proposed method also achieves good results in the application of Blake Ridge data. According to the method proposed in this paper, the hydrate reservoir in the area has a high porosity (more than 50%), and a medium saturation (between 10% and 20%). The thickness is mainly between 200m and 300m. It is consistent with the previous results obtained by velocity analysis.

Structural attributes,evolution and petroleum geological significances of the Tongnan negative structure in the central Sichuan Basin,SW China

The Tongnan secondary negative structure in central Sichuan Basin has controls and influences on the structural framework and petroleum geological conditions in the Gaoshiti-Moxi area.To clarify the controls and influences,the deformation characteristics,structural attributes and evolution process of the Tongnan negative structure were investigated through a series of qualitative and quantitative methods such as balanced profile restoration,area-depth-strain(ADS)analysis,and structural geometric forward numerical simulation,after comprehensive structural interpretation of high-precision 3D seismic data.The results are obtained in three aspects.First,above and below the P/AnP(Permian/pre-Permian)unconformity,the Tongnan negative structure demonstrates vertical differential structural deformation.It experiences two stages of structural stacking and reworking:extensional depression(from the Sinian Dengying Formation to the Permian),and compressional syncline deformation(after the Jurassic).The multi-phase trishear deformation of the preexisting deep normal faults dominated the extensional depression.The primary depression episodes occurred in the periods from the end of Late Proterozoic to the deposition of the 1st–2nd members of the Dengying Formation,and from the deposition of Lower Cambrian Longwangmiao Formation–Middle–Upper Cambrian until the Ordovician.Second,the multi-stage evolution process of the Tongnan negative structure controlled the oil and gas migration and adjustment and present-day differential gas and water distribution between the Tongnan negative structure and the Gaoshiti and Moxi-Longnüsi structural highs.Third,the Ordovician,which is limitedly distributed in the Tongnan negative structure and is truncated by the P/AnP unconformity on the top,has basic geological conditions for the formation of weathering karst carbonate reservoirs.It is a new petroleum target deserving attention.

Profiling the effects of microwave-assisted and soxhlet extraction techniques on the physicochemical attributes of Moringa oleifera seed oil and proteins

There is a constant search for biomaterials from natural products like plants for food and industrial applications.The work embodied in this report aimed at investigating the effects of microwave-assisted and soxhlet extraction(MAE and SE) techniques on the functional physicochemical quality characteristics of Moringa oleifera seed oil and proteins extracts. M. oleifera seeds were ground to fine powders and oil was extracted by microwave-assisted and soxhlet extraction techniques using petroleum ether. Quality attributes including yield percent, moisture content,iodine, saponification, specific gravity, viscosity, p H, thiobarbituric acid, acid and peroxide values were measured. Mineral and vitamin contents, chemical/functional groups, fatty acid(FA) composition, and reducing power of the oil were evaluated. Metabolomics of protein extracted from the defatted powders were analyzed by nuclear magnetic resonance(NMR). M. oleifera oil from MAE and SE methods had good yield(34.25 ± 0.0%,28.75 ± 0.0%), low moisture content(0.008 ± 0.0%, 0.011 ± 0.0%), non-drying and unsaturated, moderately saponified, less dense(0.91 ± 0.01, 0.92 ± 0.02 g m L^(-1)), had Newtonian flow, were weakly acidic, showed good content of FAs, recorded strong potential for long shelf-life, showed stability against oxidative rancidity and enzymatic hydrolysis, had very rich deposits of micro-and macro-nutrients as well as water-soluble and lipidsoluble vitamins, and functional groups in the oil were reflective of its content of long-and medium-chain triglycerides(LCT and MCT). Monounsaturated and saturated fatty acids(MUFA and SFA) were detected and the oil has excellent ferric ion reducing power. NMR metabolomic assay revealed the presence of nine essential amino acids(EAAs) in the protein extract. MAE technique is a feasible and acceptable alternative for high throughput extraction of M. oleifera oil with high yield and excellent quality attributes. The study revealed that MAE did not impart any remarkable advantage(s) on the physicochemical properties of M. oleifera seed oil and protein compared to SE technique.

Modelling of Active and Latent Attributes Based on Traveler Perspectives: Case of Port City of Douala

A growing stream of study stresses the relevance of subjective elements in understanding the hierarchy of preferences that underpin individual travel behavior. The purpose of this study is to evaluate the impact of various factors on mode choice. To achieve this, a multinomial logit model (MNL) was used to analyze the relationships between mode choice and three classes of attributes;Combined Active and Latent, Active only and Latent only attributes. The data used are derived from surveys in the port city of Douala, Cameroon as a case study. Results stipulated that, the combined attributes model performed better than both active only attributes and latent only attributes models. Likewise, latent only attributes model performed better than active only attributes model. The advantage of modelling all three groups is for better selection of the most relevant attributes, and this is very relevant in understanding travel behavior of individuals and mode choice decisions.

Classifying Big Medical Data through Bootstrap Decision Forest Using Penalizing Attributes

Decision forest is a well-renowned machine learning technique to address the detection and prediction problems related to clinical data.But,the tra-ditional decision forest(DF)algorithms have lower classification accuracy and cannot handle high-dimensional feature space effectively.In this work,we pro-pose a bootstrap decision forest using penalizing attributes(BFPA)algorithm to predict heart disease with higher accuracy.This work integrates a significance-based attribute selection(SAS)algorithm with the BFPA classifier to improve the performance of the diagnostic system in identifying cardiac illness.The pro-posed SAS algorithm is used to determine the correlation among attributes and to select the optimum subset of feature space for learning and testing processes.BFPA selects the optimal number of learning and testing data points as well as the density of trees in the forest to realize higher prediction accuracy in classifying imbalanced datasets effectively.The effectiveness of the developed classifier is cautiously verified on the real-world database(i.e.,Heart disease dataset from UCI repository)by relating its enactment with many advanced approaches with respect to the accuracy,sensitivity,specificity,precision,and intersection over-union(IoU).The empirical results demonstrate that the intended classification approach outdoes other approaches with superior enactment regarding the accu-racy,precision,sensitivity,specificity,and IoU of 94.7%,99.2%,90.1%,91.1%,and 90.4%,correspondingly.Additionally,we carry out Wilcoxon’s rank-sum test to determine whether our proposed classifier with feature selection method enables a noteworthy enhancement related to other classifiers or not.From the experimental results,we can conclude that the integration of SAS and BFPA outperforms other classifiers recently reported in the literature.

可撤销属性加密的区块链数据访问控制方法

针对区块链数据共享中存在的粗粒度访问控制问题,提出一种基于属性撤销密文策略属性基加密的区块链数据访问控制方法。在现有方案基础上进行改造,引入预解密过程,结合属性撤销列表实现属性实时撤销;基于非对称群下的DBDH困难问题假设进行安全性证明;基于超级账本Fabric进行系统设计,结合星际文件系统采用链上链下存储方式解决区块链容量不足和系统效率问题。实验结果表明,所提方案撤销属性时无需更新密钥密文重复上链,仅需要6次Pairing操作进行预解密和解密,且在大规模属性集下,预解密时间和解密时间平均保持在百毫秒左右的常量级上,实现区块链数据高效、细粒度的访问控制。

职业教育如何增强“教育性”——基于英国改革经验与启示

职业教育的属性之争是持续关注的热点,增强“教育性”是职业教育的本真回归。为应对发展困境,英国以托尼范式为基本指导,在新职业主义背景下开启改革,持续至今。以核心技能为引领,依托证书课程和T level行动计划,凸显职业教育“教育性”是改革趋向。基于英国经验,我国应以“全人”教育为导向,转变职业教育发展理念;以培养目标为载体,渗透核心素养;以“整合观”为原则,发展职业能力。

海南岛抱板杂岩记录的多期构造热事件:锆石和独居石U-Pb年代学的制约

抱板杂岩(抱板群)是海南岛目前已发现的最古老前寒武纪结晶基底,记录了多期构造热事件,是研究海南岛大地构造属性的重要窗口。本文通过对海南岛冲卒岭地区抱板杂岩变质沉积岩、变质基性岩和伟晶岩脉的锆石和独居石LA-ICP-MS U-Pb年代学研究,来确定抱板杂岩所经历的多期构造热事件及其所代表的构造意义。研究结果显示,抱板杂岩主要由中元古代变质沉积岩、花岗质片麻岩和变质基性岩组成,经历了中元古代晚期-新元古代早期(1.3~0.9Ga)、早古生代(470~440Ma)、三叠纪(~230Ma)等多期构造热事件的改造。中元古代晚期-新元古代早期构造热事件与罗迪尼亚超大陆的汇聚有关;早古生代构造热事件与东冈瓦纳古陆北缘的增生造山作用有关;三叠纪构造热事件是印支陆块与华南陆块碰撞拼合的远程响应。综合上述研究成果和区域对比分析,认为海南岛与印支陆块具有相似的前寒武纪结晶基底和多期构造热事件的记录,表明二者具有明显的亲缘关系。

水资源-能源-粮食-生态系统耦合协调及驱动力分析

为加深对我国水资源、能源、粮食、生态系统协同演变趋势的认识,构建水资源-能源-粮食-生态多维系统指标体系,运用耦合协调度模型对我国2005—2020年水资源-能源-粮食-生态系统耦合协调度进行评价,并采用多因素归因分析法进行驱动力分析。结果表明:我国水资源-能源-粮食-生态系统耦合协调度从2005年的0.55增长到2020年的0.84,各地区耦合协调度从勉强协调发展水平过渡到中级协调发展水平,各子系统对耦合协调度上升的驱动分别经历了由粮食子系统到生态子系统再到水资源子系统主导的过程;能源子系统的贡献率虽然比较小,但是未来可能是各地区提升水资源-能源-粮食-生态系统多维系统协调发展水平的突破口。

省级中药饮片炮制规范法律属性探析

目的为省级中药饮片炮制规范法律地位的明确以及《药品管理法》中“药品标准”法律表述的立法技术完善提供参考。方法结合我国药品地方标准法律渊源,对中药饮片国家药品标准构成要件以及现行省级中药饮片炮制规范构成进行分析,同时基于法律解释的方法,对《药品管理法》中省级中药饮片炮制规范的法律内涵进行探讨。结果与结论在药品监管实务中,省级中药饮片炮制规范实质为地方药品标准,2019年新修订的《药品管理法》对药品标准进行了专门规定,但对于省级中药饮片炮制规范的药品标准法律属性并未作出规定,存在一定的立法技术瑕疵。建议在《药品管理法》修正时,对省级中药饮片炮制规范的药品标准法律属性予以明确。

认知诊断评估中Q矩阵理论及应用

Q矩阵是认知心理学与心理计量学结合的重要载体,Q矩阵在认知诊断中发挥着十分重要的作用。Q矩阵理论和应用研究近年来取得了重要进展。众多研究者从结构化到非结构化、属性二值到多值、简单到复杂模型、独立到一般结构、0-1到多级评分方面不断深入和拓展Q矩阵理论。Q矩阵理论也广泛应用于测验构念效度评价、计算机化自适应测验选题策略设计、Q矩阵学习和标定、认知诊断测验组卷等。与模型无关的Q矩阵理论和适合特定认知诊断模型下Q矩阵理论,以及最新Q矩阵理论的应用都值得深入研究。

我国学校武术发展的审视与救赎

中国武术自1916年进入学校教育体系至今,已有100多年学校武术发展史,从最初的“强国强种”“尚武精神”到新中国成立后的“强身健体”“活跃身心”再到新世纪力图走出国门的“奥运武术”,几经风雨,走到现在实属不易。越是优秀的东西越能走的更远,武术代表着中国独特的民族文化,理应传承下去,但是,武术发展也并非一帆风顺,特别是学校武术的发展,现状越来越令人担忧。学校武术“操化”“泛竞技化”严重制约武术的个性发展,教学内容、模式的单一枯燥和武术教育的文化缺失等问题,使学校武术教育“渐行渐远”,以至“名存实亡”。本文采用文献资料等方法,对当前学校武术发展中存在的问题进行梳理,并试图提出解决方案,以期为学校武术健康发展提供理论依据。