Open Access

ARTICLE

A Coupled Model for Multi-Component Gas Wellbore Thermo-Pressure Behavior

Xiang Li^1,2, Jie Zhang^1,2,*, Yuxin Cheng^1,2, Jiaohao Xie^1,2, Zhaoqi Xiong^1,2

1 State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University, Chengdu, China
2 Petroleum Engineering School, Southwest Petroleum University, Chengdu, China

* Corresponding Author: Jie Zhang. Email:

(This article belongs to the Special Issue: Theoretical Foundations and Applications of Multiphase Flow in Pipeline Engineering)

Fluid Dynamics & Materials Processing 2026, 22(5), 9 https://doi.org/10.32604/fdmp.2026.079253

Received 18 January 2026; Accepted 28 April 2026; Issue published 27 May 2026

Abstract

Current prediction methods for wellbore temperature and pressure in gas storage injection–production wells are commonly based on the simplifying assumption of pure methane, thereby neglecting the multi-component nature of real natural gas and limiting predictive accuracy. To overcome this shortcoming, this study develops a comprehensive model for the coupled temperature and pressure fields in wellbores transporting multi-component natural gas mixtures. The proposed framework explicitly accounts for compositional effects by integrating key thermophysical properties, including density, viscosity, compressibility factor, and Joule–Thomson coefficient, into the governing flow equations, thereby enhancing the fidelity of the ensuing injection and production process simulations. The resulting system of equations is solved numerically using a fourth-order Runge–Kutta scheme. Validation against field data from the Xiangguosi Gas Storage facility demonstrates strong agreement, with prediction errors for both temperature and pressure remaining within 3%. Furthermore, sensitivity analyses are presented for representative field conditions, thereby elucidating the roles of principal controlling factors in shaping the wellbore thermo-pressure behavior, and offering valuable theoretical and practical insights for operational optimization and safety management.

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Keywords

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