油田废水具有油类污染浓度高、水质成分复杂、水量波动大等特征，导致废水处理过程中存在稳定达标难、处理成本高、处理结果难预测等问题。为总结油田废水处理模型研究现状并展望未来研究方向，通过调研大量国内外文献，系统地综述了油田废水处理中重力式分离、气浮、过滤等常用工艺的机理模型和多因素调控的智能模型，尤其是计算流体力学(Computational Fluid Dynamics，CFD)、人工神经网络(Artificial Neural Network,ANN)等模拟技术的应用。在此基础上，针对油田废水处理过程中上下游相互制约的多工艺耦合问题，提出了多因素实时智慧调控、全流程系统优化等未来研究方向，为科研工作和技术应用提供参考。

 Oilfield wastewater is of high oil concentration, complex water quality, large water amount fluctuation and other typical properties. It often results in many problems such as the difficult to reach the treatment standard, high treatment cost and unpredictable performance of treatment. In order to summarize the research progress of oilfield wastewater treatment model and look forward to the future research direction, this study comprehensively reviewed a large number of domestic and foreign scientific literatures, covering the mechanism model of common processes such as gravity separation, flotation and filtration in oilfield wastewater treatment, and the intelligent feature model of multi factor regulation. Especially, this study detailed the application of computational fluid dynamics(CFD), artificial neural network(ANN) and other simulation technologies. On this basis, the future research directions such as multi factor realtime intelligent regulation and full process system optimization are proposed to solve the multi process coupling problem of mutual restriction between upstream and downstream in oilfield wastewater treatment process. It provides the reference for scientific research and technology application.