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蚁群算法是最近十余年刚刚兴起的一种高效的仿生优化算法,算法采用分布式并行计算和正反馈自我催化机制,具有易与和其他算法结合等特点.将其应用于断层追踪能够客观、全面的诠释断层的空间展布情况,有效的提高断层解释精度.以喇南中东一区萨二油层组为例,应用基于蚁群算法下断层追踪方法准确落实目的层段断层展布规律,能够很好地解决原认识在开发过程中所遇到的矛盾,对于深入油层开发、完善注采系统、挖潜剩余油具有一定的指导意义.
Ant colony optimization (ACO) is an efficient bionic optimization algorithm that has just emerged in the recent ten years. The algorithm adopts distributed parallel computation and positive feedback self-catalysis and has the characteristics of easy integration with other algorithms. It can be applied objectively, A comprehensive interpretation of the spatial distribution of the fault effectively improve the fault interpretation accuracy.According to the example of the SA2 reservoir in the southern region of southern Laonan, the fault tracking method based on the ant colony algorithm It is a good guide to resolve the contradictions encountered in the development of the original understanding, which will be of guiding significance for the further development of oil reservoirs, the improvement of the injection-production system and the tapping of remaining oil.