Volume flow rate calculation model of non-full pipe multiphase flow based on ultrasonic sensors

Abstract

In the oil and gas industries, it is crucial to employ appropriate drilling fluids in order to maintain equilibrium of formation pressure throughout the various stages of drilling operations. During the recycling process, the drilling fluid may precipitate gas and as a result exhibit non-full pipe flow upon return to the surface. Accurate measurement of the volume flow rate of the drilling fluid is imperative in obtaining valuable information from the bottom of the well. Commonly, on-site drilling operations use a multiphase target flowmeter in conjunction with an empirical model to rectify calculation results. However, the returned multiphase flow that is not fully in the pipe and its liquid component exhibits corrosive properties, making it a challenge for traditional invasive measurement methods to achieve adequate accuracy over an extended period. Therefore, the theoretical potential of utilizing non-contact ultrasonic sensors for measuring the multiphase volume flow rate of the non-full pipe flow is significant. In this research, an apparent flow velocity calculation model was established by integrating the ultrasonic Doppler shift model and pipeline fluid mechanics utilizing a four-channel ultrasonic array. Subsequently, the invariant scattering convolution—long short-term memory) network was trained on the data-fused ultrasonic signal to identify the liquid level. The velocity-area method was also employed to establish a new multiphase volume flow calculation model. To evaluate the validity of the proposed model, comparison experiments of liquid single-phase flow and liquid–solid two-phase flow were conducted. The experimental results show that, compared with the comparative flow measurement system, the accuracy of the ultrasonic flow measurement system is reduced by 0.965%, the nonlinear error by 2.293%, the average relative error by 2.570%, the standard deviation by 1.395, and the root mean square error by 14.394.