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Flow rate and holdup are two essential parameters to describe oil-water two-phase flow. The distribution of oil-water two-phase flow in the pipeline is very uneven, and there is a significant slippage between the phases. This makes it difficult to measure these two flow parameters. In this paper, a new measurement method of flow rate and holdup based on phase state regulation is proposed. The oil-water two-phase flow is adjusted to oil or water single-phase flow according to the time sequence by the phase state regulation, and the oil-water phase interface is measured with a conductance sensor. A wavelet transform based phase inflection point detection model is proposed to detect the oil-water phase change point. The experimental results show that the maximum measurement error of the flow rate of water is 3.73%, the maximum measurement error of the flow rate of oil is 3.68%, and the flow rate measurement repeatability is 0.0002. The accuracy of the measurement holdup is better than 3.23%, and the repeatability of the measurement holdup is 0.0003. The prototype designed based on this method has two advantages. One is that it is small in size, the other is that it does not depend on the accuracy of the sensor. Therefore, it can be widely used in oilfield ground measurement. [ABSTRACT FROM AUTHOR]

As oil exploitation enters its middle and late stages, formation pressure drops, and crude oil degases. In production profile logging, the presence of the gas phase will affect the initial oil–water two-phase flowmeter's flow measurement results. In order to eliminate gas-phase interference and reduce measurement costs, we designed a downhole gas–liquid separator (DGLS) suitable for low flow, high water holdup, and high gas holdup. We based it on the phase isolation method. Using a combination of numerical simulation and fluid dynamic measurement experiments, we studied DGLS separation efficiency separately in the two cases of gas–water two-phase flow and oil–gas–water three-phase flow. Comparative analysis of the numerical simulation calculation and dynamic test results showed that: the VOF model constructed based on k − ε the equation is nearly identical to the dynamic test, and can be used to analyze DGLS separation efficiency; the numerical simulation results of the gas–water two-phase flow show that when the total flow rate is below 20 m3/d, the separation efficiency surpasses 90%. The oil–gas–water three-phase's numerical simulation results show that the oil phase influences separation efficiency. When the total flow rate is 20 m3/d–50 m3/d and gas holdup is low, the DGLS's separation efficiency can exceed 90%. Our experimental study on fluid dynamics measurement shows that the DGLS's applicable range is when the gas mass is 0 m3/d~15 m3/d, and the water holdup range is 50%~100%. The research presented in this article can provide a theoretical basis for the development and design of DGLSs. [ABSTRACT FROM AUTHOR]

In oilfield development, vertical longitudinal multipole conductance sensors (VLMCS) have been widely used to measure the water holdup in the oil-water two-phase flow. When water is a continuous phase and oil is a discrete phase, the oil phase distribution has a great influence on the VLMCS output. In this paper, a 3D theoretical model of the VLMCS is established, and the output response characteristics are studied, considering an oil bubble behavior in the 3D model. The task is performed by establishing a spherical coordinate system and a cylindrical coordinate system with varying mesh sizes and axial and radial positions. At the same time, finite element analysis is used to study the VLMCS output response characteristics of multiple oil bubbles. The results reveal the effect of oil bubble size and position on the VLMCS output response characteristics, which is of great significance for the measurement of the oil-water two-phase flow parameters and optimization of the VLMCS design. The established model provides a theoretical basis for the engineering applications of the VLMCS. [ABSTRACT FROM AUTHOR]

Velocity is an important parameter for fluid flow characteristics in profile logging. Particle tracking velocimetry (PTV) technology is often used to study the flow characteristics of oil wells with low flow velocity and high water cut, and the key to PTV technology is particle matching. The existing particle matching algorithms of PTV technology do not meet the matching demands of oil drops in the oil phase velocity measurement of oil-water two-phase flow with low velocity and high water cut. To raise the particle matching precision, we improved the particle matching algorithm from the oriented FAST and the rotated BRIEF (ORB) feature description and the random sample consensus (RANSAC) algorithm. The simulation and experiment were carried out. Simulation results show that the improved algorithm not only increases the number of matching points but also reduces the computation. The experiment shows that the improved algorithm in this paper not only reduces the computation of the feature description process, reaching half of the computation amount of the original algorithm, but also increases the number of matching results, thus improving the measurement accuracy of oil phase velocity. Compared with the SIFT algorithm and the ORB algorithm, the improved algorithm has the largest number of matching point pairs. And the variation coefficient of this algorithm is 0.039, which indicates that the algorithm is stable. The mean error of oil phase velocity measurement of the improved algorithm is 1.20 %, and the maximum error is 6.16 %, which is much lower than the maximum error of PTV, which is 25.89 %. The improved algorithm overcomes the high computation cost of the SIFT algorithm and achieves the precision of the SIFT algorithm. Therefore, this study contributes to the improvement of the measurement accuracy of oil phase velocity and provides reliable production logging data for oilfield. [ABSTRACT FROM AUTHOR]

The development of Daqing Oilfield in China has entered the middle and late stages of high water cut. At this time, oil-water two-phase flow is ubiquitous, and its flow rate is very difficult to measure accurately. Addressing this issue, the measurement model and simulation model of electromagnetic flow transducer (EFT) with saddle excitation structure is designed in this paper. Then the distribution characteristics of magnetic flux density of different excitation structures are analyzed by finite element simulation. Furthermore, the prediction model between the parameters of different excitation structures and the performance evaluation indexes is established based on RBF neural network. Through normalization and weight assignment on the output of neural network model, the structure optimization factor is constructed. Then the optimum solution of this factor is gotten, and the optimum parameters of EFT's excitation structure are obtained. In addition, an EFT with the optimum structure is developed and tested in Daqing oilfield, and the experiment results show that the EFT has high precision, especially in the high viscosity wells. [ABSTRACT FROM AUTHOR]

Flow velocity field measurement is important for analyzing flow characteristics of oil–water two-phase immiscible flow in vertical well. Digital particle image velocimetry (DPIV) is an effective velocity field measurement method that has overcome single point measurement limitation of traditional instruments. However, multiphase flow velocity fields generated by DPIV are often accompanied by local false vectors caused by image mismatching, which leads to measurement results with low accuracy. In this paper, the reasons for oil–water two-phase immiscible flow image mismatching in inner diameter 125 mm vertical pipe is identified by studying the DPIV calculation process. This is mainly caused by image noise and poor window following performance that results from poor deformation performance of the interrogation window. To improve deformation performance of the interrogation window, and thus improve the accuracy of the algorithm, iterative closest point (ICP) and moving least squares (MLS) are introduced into the window deformation iterative multigrid algorithm in DPIV postprocessing algorithm. The simulation showed that the improved DPIV algorithm had good matching performance, and thus the false vector was reduced. The experimental results showed that, in light of the present investigation, on average, the improved DPIV algorithm is found to yield an accuracy improvement of ~6%; the measurement uncertainty and reproducibility of the improved DPIV algorithm were 0.149 × 10−3 m/s and 1.98%, respectively. [ABSTRACT FROM AUTHOR]

In the process of production logging interpretation, a water cut is one of the key factors to obtain the oil phase content in the oil well. In order to measure the water cut of the horizontal oil–water two-phase flow with low yield, the response characteristics of the combined capacitance sensor (CCS) are investigated under different flow patterns. Firstly, the measuring principles of coaxial, cylindrical, and CCS are introduced in detail. Then, according to the different flow pattern conditions of the horizontal oil–water two-phase flow, the response characteristics of the CCS are simulated and analyzed using the finite element method. Additionally, compared with the other two sensors, the advantages of the CCS are verified. Finally, the temperature and pressure calibration experiments are carried out on the CCS. The horizontal oil–water two-phase flow patterns in a low yield liquid level are divided in detail with a high-speed camera. Dynamic experiments are carried out in a horizontal pipe with an inner diameter of 125 mm on the horizontal oil–water two-phase flow experimental equipment. The simulation and experimental results show that the CCS has good response characteristics under different working conditions. [ABSTRACT FROM AUTHOR]

A new type of conductance sensor has been studied to simultaneously measure both flow rate and water cut of oil-water two-phase fluid in production wells. The water cut is obtained by the ratio of the conductivity of the oil-water mixture fluid to that of the water, and the flow rate is obtained by cross-correlation flow rate measurement, which can determine the transit time of the flowing noise signals of fluid passing through the upstream and downstream sensors in the conductance sensor. In this article, the structure of the conductance sensor and the principles of measurement of flow rate and water cut are introduced. The results of the dynamic experiment in a multiphase flow loop and the in situ application of the technology are introduced herein. [ABSTRACT FROM AUTHOR]

Velocity and flow field are both parameters to measure flow characteristics, which can help determine the logging location and response time of logging instruments. Particle image velocimetry (PIV) is an intuitive velocity measurement method. However, due to the limitations of image acquisition equipment and the flow pipe environment, the velocity of a horizontal small-diameter pipe with high water cut and low flow velocity based on PIV has measurement errors in excess of 20%. To solve this problem, this paper expands one-dimensional displacement sub-pixel fitting to two dimensions and improves the PIV algorithm by Kriging interpolation. The improved algorithm is used to correct the blank and error vectors. The simulation shows that the number of blank and error vectors is reduced, and the flow field curves are smooth and closer to the actual flow field. The experiment shows that the improved algorithm has a maximum measurement error of 5.9%, which is much lower than that of PIV, and that it also has high stability and a repeatability of 3.14%. The improved algorithm can compensate for the local missing flow field and reduce the requirements related to the measurement equipment and environment. The findings of this study can be helpful for the interpretation of well logging data and the design of well logging instruments. [ABSTRACT FROM AUTHOR]