Geomechanical characterization of volcanic rocks using empirical systems and data mining techniques

This paper tries to characterize volcanic rocks through the development and application of an empirical geomechanical system. Geotechnical information was collected from the samples from several Atlantic Ocean islands including Madeira, Azores and Canarias archipelagos. An empirical rock classification system termed as the volcanic rock system(VRS) is developed and presented in detail. Results using the VRS are compared with those obtained using the traditional rock mass rating(RMR) system. Data mining(DM) techniques are applied to a database of volcanic rock geomechanical information from the islands.Different algorithms were developed and consequently approaches were followed for predicting rock mass classes using the VRS and RMR classification systems. Finally, some conclusions are drawn with emphasis on the fact that a better performance was achieved using attributes from VRS.

Isolation and Structural Characterization of a New Minor Penta β-D-Glucopyranosyl Diterpene from Stevia rebaudiana Bertoni

From the commercial extract of the leaves of Stevia rebaudiana Bertoni, a new minor ent-kaurane diterpene glycoside having five β-D-glucopyranosyl units has been isolated. The chemical structure of the new compound was characterized as 13-[(2-O-β-D-glucopyranosyl-β-D-glucopyranosyl)oxy] ent-kaur-16-en-19-oic acid-(2-O-β-D-glucopyranosyl-6-O-β-D-glucopyranosyl-β-D-glucopyranosyl) ester (1) on the basis of extensive 1D (1H & 13C) and 2D NMR (TOCSY, HMQC, and HMBC), and High Resolution (HR) mass spectroscopic data as well as hydrolysis studies.

Enzymatic Synthesis and Structural Characterization of Rebaudioside D3, a Minor Steviol Glycoside of <i>Stevia rebaudiana</i>Bertoni

Rebaudioside D3, a novel steviol glycoside, is produced by specific UDP-glycosyltransferase of rebaudioside E, a minor steviol glycoside of Stevia rebaudiana Bertoni. The complete proton and carbon NMR spectral assignments of rebaudioside D3, 13-[(2-O-β-D-glucopyranosyl-6-O-β-D-glucopyranosyl-β-D-glucopyranosyl) oxy] ent-kaur-16-en-19-oic acid-(2-O-β-D-glucopyranosyl-β-D-glucopyranosyl) ester, was achieved by the extensive 1D and 2D NMR (1H and 13C, TOCSY, HMQC, HMBC) as well as mass spectral data. Further, hydrolysis studies were performed on rebaudioside D3 using acid and enzymatic studies to identify aglycone and sugar residues in its structure. Rebaudioside D3 is detected in the commercial extract of the leaves of Stevia rebaudiana by LC-MS analysis, suggesting rebaudioside D3 is a natural steviol glycoside.

“Second quantitative characterization”and its application in fractured-vuggy carbonate reservoirs

The Ordovician fracture-vug carbonate reservoirs of Tarim Basin,are featured by developed vugs,caves and fractures.The strong heterogeneity results in huge uncertainty when these reservoirs are quantitatively characterized using merely static seismic data.The effective quantitative characterization of the reservoirs has been an urgent problem to be solved.This study creatively proposes the"second quantitative characterization"technique with the combination of dynamic and static data based on the primary static quantitative characterization and fully considering lots of key influence factors when conducting characterization.In this technique,dynamic analysis methods such as well testing,production rate transient analysis,dynamic reserve evaluation and dynamic connectivity evaluation are used to get understandings on this kind of reservoir.These understandings are used as statistical parameters to constrain the inversion of seismic wave impedance to improve the relationship between wave impedance and porosity and determine the fracture-vug morphology,calculate dynamic reserves,and then a more accurate fracture-vugmodel can be selected and used to calculate the oil-water contact inversely based on the results of"second quantitative characterization".This method can lower the uncertainties in the primary quantitative characterization of fracture-vug reservoirs,enhance the accuracy of characterization results significantly,and has achieved good application results in the fracture-vug carbonate reservoirs of Tarim Basin.

PhiBench 2.0: characterizing data analytics workloads on Intel Knights Landing

With high computational capacity, e.g. many-core and wide floating point SIMD units, Intel Xeon Phi shows promising prospect to accelerate high-performance computing(HPC) applications. But the application of Intel Xeon Phi on data analytics workloads in data center is still an open question. Phibench 2.0 is built for the latest generation of Intel Xeon Phi(KNL, Knights Landing), based on the prior work PhiBench(also named BigDataBench-Phi), which is designed for the former generation of Intel Xeon Phi(KNC, Knights Corner). Workloads of PhiBench 2.0 are delicately chosen based on BigdataBench 4.0 and PhiBench 1.0. Other than that, these workloads are well optimized on KNL, and run on real-world datasets to evaluate their performance and scalability. Further, the microarchitecture-level characteristics including CPI, cache behavior, vectorization intensity, and branch prediction efficiency are analyzed and the impact of affinity and scheduling policy on performance are investigated. It is believed that the observations would help other researchers working on Intel Xeon Phi and data analytics workloads.

Characterizing big data analytics workloads on POWER8 SMT processors

Big data analytics is emerging as one kind of the most important workloads in modern data centers. Hence,it is of great interest to identify the method of achieving the best performance for big data analytics workloads running on state-of-the-art SMT( simultaneous multithreading) processors,which needs comprehensive understanding to workload characteristics. This paper chooses the Spark workloads as the representative big data analytics workloads and performs comprehensive measurements on the POWER8 platform,which supports a wide range of multithreading. The research finds that the thread assignment policy and cache contention have significant impacts on application performance. In order to identify the potential optimization method from the experiment results,this study performs micro-architecture level characterizations by means of hardware performance counters and gives implications accordingly.

中国石油精细油藏描述技术新进展与展望

精细油藏描述研究是油田开发基础工作之一,其研究精度的不断提高,极大地促进了油田开发水平的提升。“十二五”和“十三五”期间,中国石油精细油藏描述研究针对多层砂岩油藏、复杂断块油藏、低渗透砂岩油藏、砾岩油藏、稠油油藏、特殊岩性油藏分别开展了技术攻关,形成了不同类型油藏配套技术系列。为了支撑剩余经济可采储量(SEC)储采平衡、老油田“压舱石”、采收率再提高、页岩油革命等“四大工程”,系统梳理中国石油精细油藏描述研究在5个方面的最新进展,分别是井震结合构造精细解释技术实现低级序断层定量描述,基于储层构型研究的单砂体刻画技术实现米级砂体描述预测,室内实验、数字岩心、物理模拟和数值模拟等方法技术实现综合剩余油表征,精细油藏描述成果平台建设实现研究过程协同共享和成果规范化存储管理,建章立制制定系列标准规范实现精细油藏描述研究规范化。通过系统总结精细油藏描述存在的8个方面问题,提出精细油藏描述的发展方向。

AI辅助电池材料表征与数据分析

随着锂离子电池(LIBs)的快速发展,传统实验方法在处理复杂数据和优化设计时面临挑战。近年来,人工智能(AI)技术在数据处理、模式识别和预测分析方面展现出巨大潜力,为LIBs的研发提供了新的解决方案。本文综述了AI在锂离子电池材料表征中的应用,包括谱学和成像表征技术。AI通过特征提取和数据分析,提高了谱学分析的准确性和效率;结合先进成像技术,研究者能够以前所未有的精度和速度探索材料内部结构。AI在图像识别、分类和分割中的应用,进一步提升了数据处理的效率和准确性。未来,AI将通过技术创新和跨学科合作,在电池材料科学领域发挥重要作用,推动高性能电池的研发和应用。

基于光谱特征和图像处理的真丝织物光泽研究

在评价织物品质与风格时需要对织物的光泽感进行评价,基于图像处理的织物光泽评价技术较其他评价技术具有诸多优点,但在关键的织物图像光泽特征的构建上,仍需要进行研究。本文选用本白色真丝素绉缎织物作为浅色样本,蓝色和黑色真丝素绉缎织物作为深色样本,粉红色和棕色样本验证分析结论。通过真丝织物的光谱数据分析对光泽度主观评价的影响因素,并建立有效的织物光泽图像特征对织物光泽评价。本文通过对真丝织物的光谱数据分析,发现织物的颜色明度与主观评分相关性很低,颜色的色相显著影响主观评分结果。并且织物的波长反射率在530~560 nm改变时,对织物光泽的主观评分影响最大。以此建立的织物光泽图像特征,表明织物表面亮点与整体表面背景亮度的对比度是基于图像处理评价技术的关键之一。

吸入制剂微细粒子空气动力学粒径分布评价方法研究

目的评估吸入制剂的空气动力学粒径分布(APSD),提高药品质量和安全有效性。方法通过对不同国家药典收载的检测APSD的方法以及相关标准进行比较与总结,用多种计量学参数来表征APSD,通过微细粒子剂量的大小和在总收集剂量中所占的比例作为评估吸入产品的关键指标。结果安德森撞击器(ACI)和新一代撞击器(NGI)是目前应用最广泛也是《美国药典》中所收载的方法,《中华人民共和国药典》又额外收载了玻璃二级撞击器,《欧洲药典》除以上3种装置外还收载了多级液体撞击器。空气动力学质量中值经(MMAD)是控制颗粒在肺部沉积位置的重要变量,几何标准偏差(GSD)表征的是药物颗粒粒度分布曲线形状,越接近于1说明粒度分布越窄。有效数据分析(EDA)中大粒子质量(LPM)与小粒子质量(SPM)的比值以及撞击粒子总质量(ISM)可检测APSD的变化。药物微粒的大小及分布很大程度上决定了粒子在呼吸系统中的沉积部位和沉积量,进而影响药物的疗效。所以若使吸入制剂中的活性药物成分(API)能够经由呼吸系统递送至肺,其气溶胶的空气动力学粒径应在1~5μm。结论合适的测试方法能够保证吸入产品的质量、安全性和有效性,合理的给药剂量和药物颗粒大小是决定吸入制剂性能的关键指标。不断改进细颗粒的测试方法,深入研究体内外的相关性,能够为吸入产品的进一步研究与开发创造有利条件。

基于Transformer网络特征融合的色纺织物颜色表征模型

针对色纺织物特有的呈色结构以及常用单一颜色测量工具导致的数据特征局限的问题,基于Transformer网络建立多源异构数据融合颜色表征模型。从分光计数据与图像数据中分别提取光谱特征与纹理特征,使用Transformer网络融合多源异构数据特征,充分利用其互补特性,有效完备地表征色纺织物颜色信息。结果表明,本文构建的颜色表征模型能够对在较大变化范围内的染色纤维质量配比差异和由于染色纤维表面不均匀分布的颜色变化进行有效表征;在分光光度仪6、10和25 mm测量孔径下,融合特征差异与纤维配比差异的相关系数均高于85%;相较于单一光谱特征和单一图像特征,本文方法的相关系数提升10%以上,具有理想的鲁棒性。

Evaluation of Hydrocarbon Potential Using AVO Analysis in the FORMAT Field, Niger Delta Basin, Nigeria

The study involved the evaluation of the hydrocarbon potential of FORMAT Field, coastal swamp depobelt Niger delta, Nigeria to obtain a more efficient reservoir characterization and fluid properties identification. Despite advances in seismic data interpretation using traditional 3D seismic data interpretation, obtaining adequate reservoir characteristics at the finest level had proved very challenging with often disappointing results. A method that integrates the amplitude variation with offfset (AVO) analysis is hereby proposed to better illuminate the reservoir. The Hampson Russell 10.3 was used to integrate and study the available seismic and well data. The reservoir of interest was delineated using the available suite of petrophysical data. This was marked by low gamma ray, high resistivity, and low acoustic impedance between a true subsea vertical depth (TVDss) range of 10,350 - 10,450 ft. The AVO fluid substitution yielded a decrease in the density values of pure gas (2.3 - 1.6 g/cc), pure oil (2.3 - 1.8 g/cc) while the Poisson pure brine increased (2.3 to 2.8 g/cc). Result from FORMAT 26 plots yielded a negative intercept and negative gradient at the top and a positive intercept and positive gradient at the Base which conforms to Class III AVO anomaly. FORMAT 30 plots yielded a negative intercept and positive gradient at the top and a positive intercept and negative gradient at the Base which conforms to class IV AVO anomaly. AVO attribute volume slices decreased in the Poisson ratio (0.96 to - 1.0) indicating that the reservoir contains hydrocarbon. The s-wave reflectivity and the product of the intercept and gradient further clarified that there was a Class 3 gas sand in the reservoir and the possibility of a Class 4 gas sand anomaly in that same reservoir.

Angular unconformity in Pennsylvanian strata from 3-D seismic interpretation,Goldsmith Field,West Texas

The Pennsylvanian unconformity,which is a detrital surface,separates the beds of the Permian-aged strata from the Lower Paleozoic in the Central Basin Platform.Seismic data interpretation indicates that the unconformity is an angular unconformity,overlying multiple normal faults,and accompanied with a thrust fault which maximizes the region's structural complexity.Additionally,the Pennsylvanian angular unconformity creates pinch-outs between the beds above and below.We computed the spectral decomposition and reflector convergence attributes and analyzed them to characterize the angular unconformity and faults.The spectral decomposition attribute divides the broadband seismic data into different spectral bands to resolve thin beds and show thickness variations.In contrast,the reflector convergence attribute highlights the location and direction of the pinch-outs as they dip south at angles between 2° and 6°.After reviewing findings from RGB blending of the spectrally decomposed frequencies along the Pennsylvanian unconformity,we observed channel-like features and multiple linear bands in addition to the faults and pinch-outs.It can be inferred that the identified linear bands could be the result of different lithologies associated with the tilting of the beds,and the faults may possibly influence hydrocarbon migration or act as a flow barrier to entrap hydrocarbon accumulation.The identification of this angular unconformity and the associated features in the study area are vital for the following reasons:1)the unconformity surface represents a natural stratigraphic boundary;2)the stratigraphic pinch-outs act as fluid flow connectivity boundaries;3)the areal extent of compartmentalized reservoirs'boundaries created by the angular unconformity are better defined;and 4)fault displacements are better understood when planning well locations as faults can be flow barriers,or permeability conduits,depending on facies heterogeneity and/or seal effectiveness of a fault,which can affect hydrocarbon production.The methodology utilized in this study is a further step in the characterization of reservoirs and can be used to expand our knowledge and obtain more information about the Goldsmith Field.

Turbidite Dynamics and Hydrocarbon Reservoir Formation in the Tano Basin: A Coastal West African Perspective

This study examines the turbidite dynamics and hydrocarbon reservoir formation in Ghana’s Tano Basin, which is located in coastal West Africa. Through an exploration of geological processes spanning millions of years, we uncover key factors shaping hydrocarbon accumulation, including source rock richness, temperature, pressure, and geological structures. The research offers valuable insights applicable to exploration, management, and sustainable resource exploitation in coastal West Africa. It facilitates the identification of exploration targets with higher hydrocarbon potential, enables the anticipation of reservoir potential within the Tano Basin, and assists in tailoring exploration and management strategies to specific geological conditions of the Tano Basin. Analysis of fluvial channels sheds light on their impact on landscape formation and hydrocarbon exploration. The investigation into turbidite systems unveils intricate interactions involving tectonics, sea-level fluctuations, and sedimentation patterns, influencing the development of reservoirs. An understanding of sediment transport and depositional settings is essential for efficient reservoir management. Geomorphological features, such as channels, submarine canyons, and distinct channel types, are essential in this situation. A detailed examination of turbidite channel structures, encompassing canyons, channel complexes, convex channels, and U-shaped channels, provides valuable insights and aids in identifying exploration targets like basal lag, channel levees, and lobes. These findings underscore the enduring significance of turbidite systems as conduits for sediment transport, contributing to enhanced reservoir management and efficient hydrocarbon production. The study also highlights how important it is to examine the configuration of sedimentary layers, stacking patterns, and angular laminated facies to identify turbidites, understand reservoir distribution, and improve well design. The dynamic nature of turbidite systems, influenced by basin characteristics such as shape and slope, is highlighted. The research provides valuable insights essential for successful hydrocarbon exploration, reservoir management, and sustainable resource exploitation in coastal West Africa.

基于五维地震数据的火山机构刻画及岩相识别——以准噶尔盆地石炭系火山岩为例

五维地震数据可以更好地分析地震波在各向异性介质中传播的旅行时间、速度、振幅、频率和相位等属性随方位角的变化,而且炮检距信息与目标地质体的尺度、地层岩性和流体成分等存在相关性,方位角信息则与地层中的断裂、裂缝等的发育特征相关。为此,提出了基于五维地震资料的火山机构刻画和岩相识别技术。考虑到地下构造在垂直于走向方向的响应更明显的特点,通过构建方位分析窗提取优势方位信息,利用倾角成像增强处理的地震资料预测火山机构,利用倾角及方位角的变化计算相邻道的相似性,提高了地震资料的横向信噪比,明确了火山机构宏观分布范围;通过定义方位时窗,结合地震道反距离加权算法,提取每个方位对断裂最敏感的信息,提高了火山机构刻画精度,得到的火山形态更清晰;再结合核主成分分析(KPCA)融合优势属性预测火山岩有利岩相,精细预测了准噶尔盆地KM1井区的三期火山岩有利区带,为高效勘探、开发该区的火山岩储层奠定了基础。

Performance of Continuous Wavelet Transform over Fourier Transform in Features Resolutions

This study presents a comparative analysis of two image enhancement techniques, Continuous Wavelet Transform (CWT) and Fast Fourier Transform (FFT), in the context of improving the clarity of high-quality 3D seismic data obtained from the Tano Basin in West Africa, Ghana. The research focuses on a comparative analysis of image clarity in seismic attribute analysis to facilitate the identification of reservoir features within the subsurface structures. The findings of the study indicate that CWT has a significant advantage over FFT in terms of image quality and identifying subsurface structures. The results demonstrate the superior performance of CWT in providing a better representation, making it more effective for seismic attribute analysis. The study highlights the importance of choosing the appropriate image enhancement technique based on the specific application needs and the broader context of the study. While CWT provides high-quality images and superior performance in identifying subsurface structures, the selection between these methods should be made judiciously, taking into account the objectives of the study and the characteristics of the signals being analyzed. The research provides valuable insights into the decision-making process for selecting image enhancement techniques in seismic data analysis, helping researchers and practitioners make informed choices that cater to the unique requirements of their studies. Ultimately, this study contributes to the advancement of the field of subsurface imaging and geological feature identification.

巴西桑托斯盆地S油田盐下地层的OBN地震数据与拖缆地震数据的对比

相较于拖缆地震数据,OBN地震数据品质较高,但OBN地震采集施工复杂、费用高昂,因此有必要厘清拖缆地震数据和OBN地震数据在成像质量以及构造和储层的刻画能力,了解OBN地震数据的相对优势,进而指导油气勘探、开发地震数据的优选。深入对比了针对深水盐下目标的OBN地震数据和拖缆地震数据:首先根据二者观测方式的特点,对比分析二者在偏移距、方位范围、照明度、信噪比和地震速度场方面的差异;然后针对复杂盐下地层成像难的特点,全面分析了两种数据的绕射波成像、断层成像、基底成像、纵横向分辨率等数据特征以及构造深度、地震反演等解释结果特征;最后针对OBN地震数据低频信号丰富的特点,通过测井数据滤波分析了丰富的低频信号对地质体轮廓刻画的作用,并提出了利用统计子波计算地震分辨率的方法。研究发现相较于拖缆地震,OBN地震作为大偏移距、宽方位的采集方式,使得其地震照明度更好和速度场精度更高,OBN地震数据品质更好;拖缆地震数据和OBN地震数据在盐下的构造形态和地震反演趋势大体一致,但OBN地震数据在构造和储层细节刻画上优势明显。OBN地震数据具有成像效果佳、断层反射清楚、基底响应清晰、地震分辨率高、地震频带宽且低频信号丰富、构造深度误差小、地震反演细节多等优点,研究结果可为同类型油田研究和应用拖缆地震和OBN地震提供较高的参考价值。

基于杂波和噪声联合稀疏特性的直接数据域STAP方法

针对机载预警雷达空时自适应处理(space-time adaptive processing,STAP)所面临的异构杂波环境,基于杂波和噪声的联合稀疏特性提出了一种直接数据域(direct data domain,D3)STAP方法。首先通过子孔径平滑技术扩充训练样本集合;然后基于杂波谱二阶表征理论构造STAP功率字典矩阵、导出目标函数,并解得待检测单元信号的空时功率谱;最后根据杂波先验信息重构无孔径损失的杂波加噪声协方差矩阵。数值实验验证了所提方法的协方差矩阵估计精度高于传统的稀疏恢复D3-STAP算法,且在理想情况和存在阵列误差的情况下,所提方法皆具备更好的低速目标检测性能。

刮板输送装备数据信息采集与处理系统设计

针对矿用刮板输送装备对传动系统和冷却系统温度、压力、振动等参数实时监控、故障判断、潜在风险预判提醒的实际需要,以RK3568作为核心处理器,设计了刮板输送装备数据信息采集与处理系统。该系统主要涉及数据信息可靠采集、表征数据提取、多信息融合的潜在风险预判模型及历史数据存储等内容,为全生命周期刮板输送装备研究奠定了基础。

云网融合中分布式网络入侵路径跟踪检测方法

随着云计算和网络虚拟化的快速发展,云网融合环境下的分布式网络较普通网络更加复杂和庞大,导致网络入侵路径跟踪的查全率难以得到保障,为此提出云网融合环境下分布式网络入侵路径跟踪检测方法;结合云网融合环境下分布式网络的特性,构建了分布式网络模型,将网络数据流信息转化为统一的格式后,考虑到干扰因素对于网络数据流信息带来的影响,对处理后的信息进行滤波处理,利用网络数据流信息计算云网融合环境下分布式网络的入侵信息特征因子,利用入侵信息特征因子实现对入侵路径的跟踪检测;在测试结果中,网络入侵路径跟踪检测准确性可达99.9%,F_(1)值始终大于0.85,明显优于对照组,具有较高的查全性能。