What question did this study set out to answer?

The aim is to estimate the flow rate of components in multiphase flow using neural network models.

February 28, 2026

Application of Neural Network Models for Estimating the Flow Rate of Components in a Multiphase Flow from a Well

Key Points

The aim is to estimate the flow rate of components in multiphase flow using neural network models.
Utilized various neural network models with different architectures.
Gathered data from multiphase flow meters using Venturi tubes and X-ray flow meters.
Focused on predicting the percentage of oil fractions in the flow.
Successfully demonstrated the ability of neural networks to predict flow rates.
Provided insights into the effectiveness of different model architectures.
Highlighted improvements in estimating multiphase flow compared to traditional methods.

Abstract

Due to high productivity and demand for products, oil industry holds a prominent place in contemporary industry. Increased attention is paid to the monitoring of its state and the production capacity of fields under operation. The exploration of new oil fields and the drilling of producing wells require high time and financial expenditures. To reduce them, some advanced technologies including different artificial intelligence methods are currently used, e.g., to estimate the percentage of fractions in the oil flow from a well. Some results of studying a number of models for predicting the flow rate of components in a multiphase flow from a well on the basis of neural networks of different architecture are presented. The study was carried out by using the readings from the sensors of multiphase flow meters based on a Venturi tube and an X-ray flow meter.

KI fragen

Bookmark