Comparative analysis and optimization of well control models for predicting annular surface pressure during well control operations in the Niger Delta

Abstract

This study develops and optimizes predictive models for annular surface pressure (ASP) during well control operations using detailed gas composition analysis and numerical modeling. Eight natural gas samples from the XYZ Field, Niger Delta, were analyzed by gas chromatography in accordance with GPA Standard 2286 (Standard Practice for Sampling and Analysis of Natural Gas by Gas Chromatography) to determine molecular compositions for accurate gas density and pressure gradient calculations. Well data and mud rheology based on the Herschel–Bulkley model were used to compute annular frictional pressure losses during influx circulation. Well control models for the Driller’s and Engineer’s Methods were formulated from pressure balance principles and optimized using a Multi-Objective Genetic Algorithm (MOGA). Optimization identified minimum wellbore pressures for kick volumes of 30–100 bbl and kick intensities of 0.5–1.5 psi/ft (equivalent to 9.6–28.8 ppg). Simulation results show that the Driller’s Method generated higher surface pressures (up to 838 psi) and greater standpipe fluctuations, whereas the Engineer’s Method maintained lower ASP (below 758 psi maximum allowable annular surface pressure (MAASP)) and shorter circulation times. A 100-bbl kick exceeded MAASP, indicating potential formation fracture. The Engineer’s Method therefore provides superior pressure control and operational stability. The optimized models enhance prediction of worst-case ASP, supporting safer, more efficient well control planning and casing design in the Niger Delta and similar high-pressure environments. Optimized models predict annular surface pressure during well control operations. Engineer’s Method maintains lower surface pressure and improved circulation stability. Findings enhance well control safety and casing design in high-pressure environments.