水平气井井筒气液两相流型预测

Prediction of Gas-liquid Two-phase Flow Patterns in Horizontal Gas Wells

准确判断产水水平气井井筒流型是预测其井筒压降、合理制定排水采气方案的关键。水平井沿流向井斜角从90°到0连续变化,目前尚无描述水平井两相流动的统一流型图,只能分别采用描述水平管、倾斜管和垂直管的3个流型图来分段处理,各流型图实验条件差异大;且产水气井日产水量极小,气液比极高,易超出工程常用气液两相管流流型图的坐标值范围,导致其预测结果误差大。为此研制了水平段-倾斜段-垂直段的水平井空气-水两相流动模拟实验装置,考虑产水气井特高气液比的特点开展了7组管斜角641组水平井气水两相管流流型实验,归纳水平气井的5种流型及其典型特征。引用Duns&Ros定义的无因次气液速度准数,增加管斜角为X轴,绘制了描述水平气井气液两相管流的三维流型图,给出了BP神经网络模型预测水平气井井筒流型的方法。川西气田20口水平气井测压数据验证表明,该流型图预测正确率达90%。

An accurate estimation of the flow pattern of a horizontal gas well that produces water is the key to predicating the pressure drop of the wellbore and establishing a sensible water-drainage production plan. The angle of a horizontal well constantly varies from 90° to 0 according to the flow direction. A unified flow pattern map that describes the two-phase flow of horizontal wells has not yet been discovered. Therefore, three separate flow pattern maps are used to describe the horizontal, slanted, and vertical pipes individually. These maps are obtained under extremely different experimental conditions.In addition, the gas wells may produce extremely low water output. In such cases, the gas-liquid ratio may exceed the valid coordinate range of the commonly used gas-liquid two-phase flow pattern map leading to significant errors in the prediction results. Considering all these drawbacks, this study has developed an air-water two-phase flow simulation experimental device for horizontal, slanted, and vertical pipes. Provided the extremely high gas-liquid ratio of the gas well with water production,this study has conducted a gas-water two-phase flow pattern experiment using 7 slanted pipes and 641 horizontal pipes. It has summarized five flow patterns and the typical characteristics of horizontal gas wells. This work has used the dimensionless gas velocity number defined by Duns and Ros and the pipe inclination angle as the X-axis. A three-dimensional flow pattern map has been constructed to describe the gas-liquid two-phase pipe flow in the horizontal gas well. This study has also proposed a method to predict the flow pattern based on the back propagation neural network model. The pressure measurement results from 20 horizontal gas wells in the gas fields at Western Sichuan indicate that the flow map demonstrates an accuracy of 90%in prediction.