Due to the effect of gravity differentiation in non-vertical wells and the asymmetry of the space around the well-bore, the fluid flow pattern in the well-born will change greatly. The water holdup reflects the distribution of water, which lays a foundation for understanding the proportion of oil and gas. Water holdup imaging can intuitively reflect the distribution of each phase and the overall water holdup. In this paper, with No. 10 industrial white oil and tap water as the working medium, the local water holdup value was measured in the oil-water two-phase by the Capacitance Array Tool, and then the response characteristics of the instrument were analyzed. MATLAB software is used to interpolate the local water holdup data of the array in the oil-water two-phase of the horizontal well. The interpolation algorithms used include: bilinear interpolation, cubic spline interpolation, simple inverse distance weighted interpolation and Gaussian radial basis function interpolation. The results show that the water holdup measured by the Capacitance Array Tool shows a good measurement effect at low and medium flow rates. Linear and Cubic Spline are selected in the case of low flow rate and low water cut in the oil-water two-phase flow with stratified flow pattern. Gaussian radial basis function is selected under the condition of low flow rate and high water cut. Gaussian radial basis function was selected under different water cut conditions of middle and high flow rate with dispersed flow pattern.

At the near-vertical position, the system error is a major factor lowering the attitude accuracy in the attitude determination system, and correction technology is often used to compensate all kinds of system errors. First, the absolute errors of the computed attitude angle including the measurement error and the correction error are analyzed, and the correction error caused by the correction matrix is emphatically derived and discussed. Then, a novel balance correction method with a nonunit correction matrix is proposed and verified theoretically. Finally, an inertial measurement unit (IMU) is tested for the near-vertical position and corrected with the conventional unit matrix and the proposed balance correction. The experimental results suggest that the balance correction under the near-vertical position can enhance the accuracies of the attitude angles over four times than those with the conventional correction.

In order to clarify the gas-water two-phase flow law in horizontal wells and study the gas-water two-phase flow characteristics in horizontal wells, firstly, the gas-water two-phase in a horizontal well is numerically simulated and analyzed, and the flow pattern distribution under different well inclination angles and different phase separation flow rates is obtained. Secondly, a series of production logging instruments including CAT instrument was used to conduct experimental research on gas-water two-phase flow under different flow conditions, and the measured values of each CAT probe were extracted to reflect the local holdup under different flow patterns. Finally, SSA-BP neural network algorithm is used to identify a gas-water two-phase flow pattern in a wellbore by using experimental parameters such as center holdup, well inclination angle, spinner revolution, and CAT probe measurements. The recognition accuracy of the neural network was improved from 83.75% to 91.66%, and the operation speed was accelerated. It provides a research idea to explore the flow characteristics of gas-water two-phase flow in horizontal wells.

Distributed temperature sensing (DTS) has been widely used in downhole dynamic monitoring. How to analyze its data and accurately interpret the flow profile using DTS data are still great challenges. Quantitative interpretation of downhole temperature measurements requires the development of an integrated flow and thermal model capable of handling multi-phase flow. The model must strike a balance between computational efficiency and achieving the highest possible accuracy. The finite difference method can solve the relevant problems well. The flow model and thermal model of reservoirs and wellbores are established. Combined with the single-phase flow theory, the coupling prediction model of wellbore and reservoir temperature is established through appropriate boundary and constraint conditions. The problem was solved iteratively using the finite difference method, and the coupled temperature prediction model’s reliability was confirmed through comparison with numerical simulation results. Based on the forward model, the sensitivity analysis of the influencing factors is carried out in this study which provides a theoretical basis for the inversion model. Taking the flow rate as the inversion parameter, the injection profile interpretation model based on DTS logging data is constructed. Four optimization methods are used in the inversion model which can balance the computational efficiency and model accuracy. The DTS data are preprocessed by the Kalman filter, and the inversion and interpretation evaluation of X injection well is carried out by the LSO-MCMC combined optimization algorithm. The results show that the method has high reliability in the interpretation accuracy of injection profile, and the inverted flow profile meets practical application requirements, confirming the method’s accuracy and effectiveness.