Guo Haimin, Li Ao, Sun Yongtuo, Yu Liangliang, Peng Wenfeng, Ouyang Mingyu, Wang Dudu, Guo Yuqing
College of Geophysics and Petroleum Resources, Yangtze University, Wuhan 430100, China.
Key Laboratory of Exploration Technology for Oil and Gas Resources of Ministry of Education, Yangtze University, Wuhan 430100, China.
Sensors (Basel). 2025 Jul 23;25(15):4557. doi: 10.3390/s25154557.
Gas-water two-phase flow in horizontal and inclined wells is significantly influenced by gravitational forces and spatial asymmetry around the wellbore, resulting in complex and variable flow patterns. Accurate measurement of water holdup is essential for analyzing phase distribution and understanding multiphase flow behavior. Water holdup imaging provides a valuable means for visualizing the spatial distribution and proportion of gas and water phases within the wellbore. In this study, air and tap water were used to simulate downhole gas and formation water, respectively. An array capacitance arraay tool (CAT) was employed to measure water holdup under varying total flow rates and water cuts in a horizontal well experimental setup. A total of 228 datasets were collected, and the measurements were processed in MATLAB (2020 version) using three interpolation algorithms: simple linear interpolation, inverse distance interpolation, and Lagrangian nonlinear interpolation. Water holdup across the wellbore cross-section was also calculated using arithmetic averaging and integration methods. The results obtained from the three imaging algorithms were compared with these reference values to evaluate accuracy and visualize imaging performance. The CAT demonstrated reliable measurement capabilities under low- to medium-flow conditions, accurately capturing fluid distribution. For stratified flow regimes, the linear interpolation algorithm provided the clearest depiction of the gas-water interface. Under low- to medium-flow rates with high water content, both inverse distance and Lagrangian methods produced more refined images of phase distribution. In dispersed flow conditions, the Lagrangian nonlinear interpolation algorithm delivered the highest accuracy, effectively capturing subtle variations within the complex flow field.
水平井和斜井中的气水两相流受到重力和井筒周围空间不对称性的显著影响，导致流动模式复杂多变。准确测量持水率对于分析相分布和理解多相流行为至关重要。持水率成像为可视化井筒内气相和水相的空间分布及比例提供了一种有价值的手段。在本研究中，分别使用空气和自来水模拟井下气体和地层水。在水平井实验装置中，采用阵列电容阵列工具（CAT）在不同总流量和含水率条件下测量持水率。总共收集了228个数据集，并在MATLAB（2020版）中使用三种插值算法对测量数据进行处理：简单线性插值、反距离插值和拉格朗日非线性插值。还使用算术平均法和积分法计算井筒横截面的持水率。将三种成像算法得到的结果与这些参考值进行比较，以评估准确性并可视化成像性能。CAT在低至中等流量条件下显示出可靠的测量能力，能够准确捕捉流体分布。对于分层流态，线性插值算法对气水界面的描绘最为清晰。在低至中等流量且含水率较高的情况下，反距离插值法和拉格朗日插值法都能生成更精细的相分布图像。在分散流条件下，拉格朗日非线性插值算法的精度最高，能够有效捕捉复杂流场内的细微变化。
