【作者】 蔡庆玲；

【导师】 史斌宁；

【作者基本信息】 合肥工业大学 ， 计算机应用技术， 2003， 硕士

【摘要】 石油在国民经济发展中的地位已毋庸赘述，但是我国石油的贮量形势令人堪忧。国内几个大型油田都不同程度地进入了衰竭期，很多油井因“出不敷入”已关闭，大量的低产油井也因功耗大、成本高而濒临“退休”。提高开采技术、降低采油成本，才能更大限度地挖掘已近贫乏的石油资源，这对我国目前尤显重要。 有杆抽油机是在我国采油工业中占主导地位的采油设备，针对有杆抽油机、以节能降耗为主要目标的采油控制技术研发得到国内外石化界高度重视。 空抽是导致有杆抽油机在贫油井使用时耗能大、效率低的症结所在，空抽不仅造成大量的无效电耗，而且加重设备损耗、引发断杆事故，对有杆抽油机实现智能化控制，从而实现自动识别空抽，自动检测故障，减少无功电能损耗、机械磨损、人工维护等，是本论文研究的主要目的。 由于地下产油量情况极其复杂，存在着非线性、不确定性、时变形和不完全性等因素，很难建立起一致的精确的数学模型，所以基于模型的传统控制方法很难达到理想的控制要求。本文提出了使用专家控制器技术，结合自学习能力，实现自动求取空抽点判据，自动计算出停机蓄油时间，有效地解决了节能、不减产、易操作等问题。更多还原

【Abstract】 There is no need to go into details how is the position of petroleum in the development of national economy. The reserves of petroleum in our country is not so rich and makes the peoples worried. Some oil field of large scale in our country are faced to be exhausted with different degrees and a lot of oil wells are closed for "income falling short of expenditures". Besides, a lot of oil well are faced to be "retailed" for too high energy consumption and too high cost of recovering. Improving the recovering technology and reducing the corresponding cost must be extremely significant for saving the old oil wells. It will be of great significance especially in our country.Up to now the oil pumps with sucker-rod are still the main facilities for oil recovering in our country. The oil experts in the world still pay their high attention to reducing the energy consumption for such oil pumps.Dry and empty pumping are the primary factors of energy wasting and low efficiency in the older oil wells. In addition, it makes the equipments quick wear and tea, leads breaks of sucker-rod etc. The major objective of this dissertation focuses on the development of control technology with artificial intelligence to realize automatic identification of dry and empty pumping, automatic inspecting of failures, reducing the energy consumption etc.Because of the complicated geological structure of oil fields, there are lots of problems on non-linear, non-definition, time varying and non-complete characteristics. Therefore it is difficult to establish an accurate mathematical model for controlling. This dissertation deals with an expert controller combined with self learning technology to realize automatic acquisition of dry and empty pumping criterions, automatic tracking of stopping time for maximal daily yields. The experiments in oil fields show that those results are effective for solving the problems of energy saving, daily yield and easy operating.更多还原