Liu Qing, Chu Bo, Peng Jinye, Tang Sheng
School of Information and Technology, Northwest University, Xi'an 710127, China.
Sensors (Basel). 2019 Jul 5;19(13):2963. doi: 10.3390/s19132963.
In the process of oil exploitation, the water level of an oil well can be predicted and the position of reservoir can be estimated by measuring the water content of crude oil, with reference for the automatic production of high efficiency in the oil field. In this paper, a visual measuring method for water content of crude oil is proposed. The oil and water in crude oil samples were separated by centrifugation, distillation or electric dehydration, and a water-oil layered mixture was formed according to the unequal densities. Then the volume ratio of water and oil was analyzed by digital image processing, and the water content and oil content was able to be calculated. A new method for measuring water content of crude oil based on IGAVD (image grayscale accumulated value difference) is proposed, which overcomes the uncertainty caused by environmental illumination and improves the measurement accuracy. In order to verify the effectiveness of the algorithm, a miniaturization and low-cost system prototype was developed. The experimental results show that the average power consumption is about 165 mW and the measuring error is less than 1.0%. At the same time, the real-time and remote transmission about measurement results can be realized.
在石油开采过程中，通过测量原油含水量可预测油井水位并估算储层位置，为油田高效自动化生产提供参考。本文提出一种原油含水量视觉测量方法。通过离心、蒸馏或电脱水分离原油样品中的油和水，根据密度不同形成水油分层混合物。然后通过数字图像处理分析水和油的体积比，进而计算出含水量和含油量。提出一种基于图像灰度累积值差（IGAVD）的原油含水量测量新方法，克服了环境光照带来的不确定性，提高了测量精度。为验证算法有效性，开发了小型化、低成本的系统原型。实验结果表明，平均功耗约为165毫瓦，测量误差小于1.0%。同时，可实现测量结果的实时远程传输。
