页岩气井柱塞工艺影响因素及制度优化方法

Plunger process in shale gas wells:Influential factors and optimization methods

为了维持气井长期稳产、支撑页岩气大规模上产,以目前长宁区块主要的排水采气工艺为研究对象,分析了主体工艺应用的影响因素,针对可控因素,基于智能管理平台对页岩气井生产数据实时监测和采集,提出了提升工艺实施效果的制度优化方法。研究结果表明:(1)页岩气开发后期需要采用排采工艺维持气井稳产,目前柱塞工艺在长宁区块已大规模推广应用200余口井;(2)对于柱塞气举制度优化,目前依然停留于根据现场生产情况调整柱塞工艺参数达到优化的目的;(3)结合柱塞运动模型,采用时间序列神经网络和多目标优化遗传算法,可建立页岩水平井柱塞气举制度优化方法。结论认为:(1)柱塞气举作为经济有效的稳产措施,是长宁区块主要的排采工艺之一;(2)目前的柱塞工艺制度优化方法多是试探的结果,优化不具有确定性,没有指导性的理论和预测结果,在工程上也无法用于快速的制度优化设计;(3)建立的制度优化新方法应用于现场21井次柱塞气举井,已对工作制度进行模拟和优化。结果表明目前采用的工作制度较为合理,与优化结果相近,由此可见该方法可有效指导柱塞工作制度的优化,可为大规模应用柱塞工艺及时调整工作制度,并为保障工艺效果提供技术支撑。

Some processes of drainage gas recovery adopted in Changning block were studied in an effort to sustain long-term stable production in shale gas wells and hold up scale shale-gas production.Their influential factors were identified.Then,with respect to controllable factors,one method to optimize process performance was proposed on the basis of an in-telligent management platform to complete real-time monitoring and acquisition of production data in shale gas wells.Re-sults show that(i)plunger gas-lift,as one process of drainage gas recovery,which is necessary to maintain the production at the late development stage,has been applied extensively in over 200 wells in Changning block;(ii)this plunger gas-lift system is mainly optimized by adjusting technical parameters depending upon production practice;and(iii)coupling the plunger movement model with the time-sequence neural network and multi-objective optimization genetic algorithm,the method to optimize this system can be developed for shale gas wells.It is concluded that,as an economic and effective sta-ble production technique,plunger gas-lift is one of popular drainage gas recovery processes used in Changning block;the existing way for optimizing the plunger gas-lift system is mostly in trial,which is not certain without any theoretical and predictable instruction,and it cannot realize rapid engineering design;and the newly proposed system has been applied to plunger gas-lift in 21 wells,for which the system has been simulated and optimized.Finally,it is derived that the current system is rational and may provide similar results to those optimized ones,proving that the proposed method can not only effectively guide system optimization but offer technical backup for guaranteeing the process with better performance.