A robust pressure drop prediction model in vertical multiphase flow: a machine learning approach.

ABSTRACT: Predicting pressure drop in multiphase flow is crucial for optimizing tubing size, wellhead pressure (WHP), completion design, cost management, and other production-phase objectives. While various correlations and models exist to calculate pressure drops, their accuracy diminishes significantly when applied to outlier datasets beyond their intended parameter ranges. Not only that, as reported by many studies, most of the empirical correlations and mechanistic models have an error, which is quite high and intolerable. This study introduces a novel Adaptive Neuro-Fuzzy Inference System (ANFIS) model for accurately predicting pressure drops in vertical wells carrying multiphase fluids. A comprehensive dataset of 335 experimental records was compiled from diverse sources to encompass a wide ra

SUBMITTER: Alakbari FS 

PROVIDER: S-EPMC12008291 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature