Oilsand slurry image and video analysis

油砂浆图像和视频分析

• 批准号: 492823-2015
• 负责人: Zhang, Hong
• 金额: $ 7.07万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=618842
• 关键词: Oilsand; slurry; image; video; analysis

In oil sands mining, mined ore which is rich in bitumen is crushed, screened, mixed with water, and transported in a pipeline before extraction takes place to separate bitumen from sand. Recovery rate of bitumen fluctuates and it is known that a portion of the bitumen can be lost to tails due to suboptimal conditions of the extraction process. We propose to conduct collaborative research with Syncrude Canada - the largest oil sands producer of the world - to gain a further scientific understanding of the recovery process by using image processing techniques and data analysis. This understanding will help to improve bitumen recovery rate, and result in benefits that are both economical - through increased production - and environmental - through reduced bitumen in tails.Specifically, we will develop image processing algorithms to study images of the moving suspended particles or droplets in ore slurry sampled by a novel sensor developed recently by Syncrude, called slurry image analyzer (SIA). These real-time algorithms will derive the characteristics of droplets of both bitumen and sand such as their size, direction and magnitude of motion, shape, and color. Since these characteristics directly translate into bitumen recovery rate, when they are examined under different extraction conditions that can be controlled, Syncrude can then attempt to construct a model that relates the conditions to the recovery rate. With the help of this model, Syncrude's SIA can be installed online to allow field engineers to monitor recovery rate, adjust operating conditions, and achieve optimal extraction performance.

在油砂开采中，富含沥青的开采矿石被压碎、筛选、与水混合，并在提取之前在管道中运输，以将沥青从沙子中分离出来。沥青的回收率波动，并且已知由于提取过程的次优条件，一部分沥青可能损失到尾料中。我们建议与世界上最大的油砂生产商Syncrude Canada进行合作研究，通过使用图像处理技术和数据分析来进一步科学地了解回收过程。这种理解将有助于提高沥青回收率，并通过增加产量带来经济效益，通过减少尾矿中的沥青带来环境效益。具体而言，我们将开发图像处理算法，以研究由Syncrude最近开发的称为浆料图像分析仪（SIA）的新型传感器采样的矿浆中移动悬浮颗粒或液滴的图像。这些实时算法将得出沥青和沙子的液滴的特征，例如它们的大小，运动方向和幅度，形状和颜色。由于这些特征直接转化为沥青回收率，当在可控制的不同提取条件下对其进行检查时，Syncrude可以尝试构建将条件与回收率相关联的模型。借助该模型，Syncrude的SIA可以在线安装，使现场工程师能够监控采收率，调整操作条件，并实现最佳提取性能。