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A Rapid Analytical Method for Predicting Injection Rates in Heterogeneous Reservoirs

A Rapid Analytical Method for Predicting Injection Rates in Heterogeneous Reservoirs

This is a Preprint and has not been peer reviewed. This is version 1 of this Preprint.

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Authors

Arman Darvish-Sarvestani, Philip Craig Smalley, Lidia Lonergan, Ana Widyanita, Nur Myra Rahayu Razali, Yong Wen Pin, Ann Muggeridge

Abstract

Maximum injection rate is a key criterion when screening subsurface hydrocarbon reservoirs or aquifers for possible EOR schemes or storage of hydrocarbon gas, hydrogen or carbon dioxide. It has to be high enough to achieve desired rates without risking the formation fracturing. Screening requires evaluation of thousands or millions of potential injection sites to identify those with favourable characteristics that merit further, more detailed study. This study presents a computationally efficient and geologically informed workflow to rapidly estimate gas injection rates in regional-scale 3D models, combining radial-based permeability upscaling with a transient compressible gas flow model that captures spatial variability in reservoir and fluid properties. The methodology requires an estimate of the distribution of petrophysical properties, pressure and temperature and applies a block-by-block rate calculation scheme, supported by a pre-processing step for pressure-dependent fluid properties (density, compressibility and viscosity). The approach is validated against numerical simulation for the case of geological storage of CO2 in a saline aquifer and then demonstrated on a real-world regional model covering ~1,200 km2. Average and maximum errors were 27% and 71% for random heterogeneous cases, and 13% and 30% for field-scale predictions, respectively, demonstrating strong agreement with numerical simulations given the scale and complexity of the models. The full regional model was processed in under five minutes using parallel computing. The key innovation lies in the permeability averaging scheme, which effectively captures near-wellbore heterogeneity for accurate rate prediction without requiring numerical simulation.

DOI

https://doi.org/10.31223/X50R00

Subjects

Engineering

Keywords

CO2 storage, CCS, screening, Injection rate, Permeability upscaling, heterogeneity, Large-scale reservoir modelling

Dates

Published: 2025-12-17 00:44

Last Updated: 2025-12-17 21:42

License

CC-BY Attribution-NonCommercial 4.0 International