基于井间动态连通性模型的注采参数优化方法

水驱油田开发过程中,由于储层非均质性以及注采参数与井网不匹配,造成优势通道发育,注入水低效无效循环严重.为了对注采井间各方向优势通道进行定量描述,基于物质平衡理论与叠加原理,在考虑井底流压变化的基础上,建立了油藏井间动态连通性反演模型——阻容模型,并运用人工蜂群算法进行求解,通过模型求解得到了不同注采井间的连通系数,经验证该系数合理表征了油藏井间动态连通程度.针对优势通道发育造成注水井在各注采方向上水驱不均衡、剩余油饱和度分布差异较大的问题,基于最优化理论,以当前各生产井含水率条件下生产井总产油量最大为目标函数,结合油水井动态生产数据,建立一种基于井间动态连通性模型的注采参数优化方法,并利用优化算法对该模型进行求解.实例应用表明:利用本文方法优化注采参数后,含水率得到明显控制,注入水驱替效率明显提高,并且本文方法仅需要油水井的动态生产资料,简单实用,对矿场具有较高的应用价值.

Optimization of Injection and Production Parameters Based on Dynamic Well Connectivity Model

During the development of waterflooding oilfield, due to the reservoir heterogeneity and mismatch of injection and production parameters with the well pattern, the thief zone is developed and the ineffective circulation of injected water is serious. In order to quantitatively describe the degree of connectivity between injection wells and production wells, based on the material balance theory and superposition principle, considering the variation of bottomhole flow pressure, dynamic well connectivity model is established. And the artificial bee colony algorithm is used to solve the problem. The connectivity coefficients between different injection and production wells are obtained by solving the model. It is verified that the coefficient can reasonably characterize the dynamic connectivity between injection and production wells. In view of the problem of uneven waterflooding in water injection wells and residual oil saturation distribution in the thief zone due, based on the optimization theory, with the current production well moisture content, by using the dynamic production data of oil and water wells, an optimization method of injection and production parameters based on dynamic well connectivity model was established, which is functioned with the maximum value of oil production in the oilfield, and the optimization algorithm was used to solve the model. The application of the method shows that by using this method, the water cut is obviously controlled and the displacement efficiency of waterflooding is obviously improved. The method only needs dynamic production data of oil and water wells, which is simple and practical and could be easily used in many oilfields.