Potential application of functional micro-nano structures in petroleum

This paper takes micro-nano motors and metamaterials as examples to introduce the basic concept and development of functional micro nano structures, and analyzes the application potential of the micro-nano structure design and manufacturing technology in the petroleum industry. The functional micro-nano structure is the structure and device with special functions prepared to achieve a specific goal. New functional micro-nano structures are classified into mobile type(e.g. micro-nano motors) and fixed type(e.g. metamaterials), and 3 D printing technology is a developed method of manufacturing. Combining the demand for exploration and development in oil and gas fields and the research status of intelligent micro-nano structures, we believe that there are 3 potential application directions:(1) The intelligent micro-nano structures represented by metamaterials and smart coatings can be applied to the oil recovery engineering technology and equipment to improve the stability and reliability of petroleum equipment.(2) The smart micro-nano robots represented by micro-motors and smart microspheres can be applied to the development of new materials for enhanced oil recovery, effectively improving the development efficiency of heavy oil, shale oil and other resources.(3) The intelligent structure manufacturing technology represented by 3 D printing technology can be applied to the field of microfluidics in reservoir fluids to guide the selection of mine flooding agents and improve the efficiency of mining.

基于机器学习的电喷印精度预测方法研究

目的节省电流体喷射打印精度预测的时间和解决电流体工艺参数的选择问题,达到提高电流体打印的质量和效率的目的。方法为了对电流体喷射打印精度进行预测,提出有限元模型与机器学习相结合的方法。基于线性回归、支持向量回归和神经网络等机器学习算法建立4种参数与射流直径的关系模型。结果算法结果表明:支持向量回归和神经网络预测模型的决定系数R2能达到0.9以上,表示模型可信度高;支持向量回归和神经网络预测模型指标都比线性回归预测模型的小。结论机器学习算法可对电喷印打印精度进行有效预测,预测效率提高了十几倍,节省了精度预测的时间。