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Xiang-Qian Xu

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Open access Aug 2026

Research on the Dynamic Stability and Applicability Boundaries of a Jet Pump-Based High Gas–Oil Ratio Multiphase Transportation System

High gas–oil ratio (GOR) well streams challenge the stable operation of oilfield gathering systems because positive-displacement multiphase pumps lose volumetric efficiency, amplify pressure pulsation, and suffer seal degradation as the inlet gas fraction rises. Targeting GOR = 100–300 Nm3/t (≈480–1450 scf/STB), this study proposes a jet pump-based oil–gas multiphase transportation system together with an evaluation framework that couples localized computational fluid dynamics (CFD) with a one-dimensional (1D) transient pipeline network model. The methodological novelty is a GOR-dependent source-term closure embedded in the 1D momentum equation: the pump pressure rise is evaluated at every time step as Δppumpt=kgGOR·ΠpGOR,pw·pw−ps from CFD-derived maps of entrainment ratio, pressure recovery, and high-gas correction, so that the jet pump enters the network simulation as a dynamic source rather than a steady boundary condition, a capability that neither pump-level transient CFD nor conventional 1D codes provide. Transient simulations under slug disturbances give three main results. (i) At GOR = 200 Nm3/t and constant working-fluid pressure, slug arrivals drive the outlet pressure transiently below the ±5% band (0.76–0.84 MPa), and it returns to the band of the 0.80 MPa set point within ≈150 s. (ii) As GOR increases from 100 to 300 Nm3/t, σppset rises from 0.031 to 0.089 and the peak-to-peak ratio from 0.18 to 0.50, with stability criterion C1 violated beyond ≈275 Nm3/t. (iii) Three applicability zones are delineated: preferred (100–200), controllable (200–260), and marginal (260–300 Nm3/t), where the marginal zone requires inlet peak-shaving, ≥30% working-fluid pressure margin, and feedforward–feedback control. Mesh independence (GCIfine=0.23–0.35%) and a CFD–1D transfer mismatch ≤3% support internal consistency; the delineated boundaries remain model predictions pending experimental and field validation.

Li-Hua Zhang, Mao Li, Siyu Jing et al. · 0 citations

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