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相关概念视频

Design Example: Aggregate Gradation01:24

Design Example: Aggregate Gradation

91
The right type and quality of aggregates are crucial for concrete as they significantly influence its properties, mix proportions, and cost-effectiveness. If different sources are available for sand, the commonly used fine aggregate in concrete, the selection of sand is primarily based on its gradation.
The grading, or particle-size distribution, of sand is determined using sieve analysis, with standard sizes ranging from 150 μm to 10 mm (ASTM No. 100 sieve to 3⁄8 in. sieve). Sand is...
91
Aggregates Classification01:29

Aggregates Classification

309
Aggregate classification is generally based on its size, petrographic characteristics, weight, and source. Size classification ranges from coarse to fine aggregates, defined by the size of the particles. Coarse aggregates are particles that do not pass through ASTM sieve No. 4, and aggregates that pass through the sieve are fine aggregates.
Petrographic classification groups aggregates based on common mineralogical characteristics. Some of the common mineral groups found in aggregates are...
309
Typical Model Studies01:30

Typical Model Studies

349
Fluid mechanics model studies often utilize scaled-down systems to predict fluid behavior in full-scale environments, such as river flows, dam spillways, and structures interacting with open surfaces. Maintaining Froude number similarity in river models is crucial, as it replicates surface flow features like wave patterns and velocities.
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相关实验视频

Updated: Jun 14, 2025

Pore-scale Imaging and Characterization of Hydrocarbon Reservoir Rock Wettability at Subsurface Conditions Using X-ray Microtomography
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基于机器学习的紧密砂岩水库的定量分类评估模型.

Xinglei Song1,2, Congjun Feng3,4, Teng Li5,6,7

  • 1State Key Laboratory of Continental Dynamics, Northwest University, Xi'an, 710069, China.

Scientific reports
|September 5, 2024
PubMed
概括
此摘要是机器生成的。

这项研究开发了一种新的双合模型,以根据孔隙结构和形状参数对紧密的砂岩水库进行分类. 该模型准确地预测了水库质量,指导了奥尔多斯盆地的勘探.

关键词:
高压水银注射高压水银注射图像识别 图像识别 图像识别机器学习是机器学习.毛孔结构 毛孔结构定量评价 定量评价 定量评价 定量评价狭窄的砂岩是一个狭窄的砂岩.

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Automatic Image Processing to Determine the Community Size Structure of Riverine Macroinvertebrates
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科学领域:

  • 石油地质学 石油地质学
  • 沉积物学的沉积物学
  • 储水库工程 储水库工程

背景情况:

  • 狭窄的砂岩水库对于石油勘探至关重要,但由于异质性而难以分类.
  • 现有的分类方法对复杂的微孔结构的适用性有限.

研究的目的:

  • 开发一个对紧密的砂岩水库的定量分类和评估系统.
  • 建立一个双合模型,整合孔隙结构和形状参数,以改善预测.
  • 在8密集水库内确定有利的勘探区域.

主要方法:

  • 使用高压入侵,造薄切片和扫描电子显微镜.
  • 图像识别技术提取了孔隙形状参数.
  • 灰色关系分析,分析层次过程和权方法用于定量分析.

主要成果:

  • 开发了一种双合模型,在分类紧密的砂岩水库中获得了93.3%的准确性.
  • 最初的生产率与毛孔度,透度和毛孔形状参数 (周长,圆度,主要轴长度) 有正相关.
  • 在研究区域的西北部发现了I型水库,表明其潜力很高,建议优先进行勘探.

结论:

  • 开发的模型提供了一种新且有效的方法来分类和评估紧密的砂岩水库.
  • 该研究成功地确定了有利的勘探区域,该区域基于对孔状特征的定量分析.
  • 这项研究为全球紧密的砂岩水库的未来勘探和开发提供了宝贵的指导.