Basin-Scale Heterogeneity in CO2 Geological Storage: Mechanisms, Prediction, and Management
4 affiliations
- 1Daqing Oilfield Design Institute Co., Ltd , ,
- 2Chinese Academy of Sciences , , ,
- 3University of Chinese Academy of Sciences , ,
- 4College of Zijin Geology and Mining (Fuzhou University) , ,
Abstract
Large-scale CO2 geological storage is evolving from stand-alone sites toward million-tonne-scale, clustered, and basin-coordinated deployment, making basin-scale heterogeneity a key constraint on capacity utilization, sustained injection, and long-term storage security. However, existing studies have largely focused on individual reservoirs, capacity estimation, or localized risks, while a systematic review integrating tectono-sedimentary evolution, reservoir–caprock assemblages, fault-controlled hydrodynamics, and multisite interference remains lacking. Based on representative sedimentary basins and engineering projects, this study reviews multisource characterization, scale transformation, multiphysics coupling, probabilistic prediction, monitoring-informed updating, and coordinated management within a “geological foundation–storage performance–prediction and regulation” framework. The results indicate that reservoir–caprock discontinuities, fault connectivity, and pressure boundaries jointly control dynamic storage capacity, pressure footprints, plume migration, trapping efficiency, and leakage risk; although multilayer utilization can increase storage capacity, it may intensify pressure superposition and cross-formational flow. This study proposes development pathways centered on pressure-constrained capacity assessment, probabilistic prediction, full-life-cycle simulation, and basin digital twins, providing a basis for regional resource allocation, coordinated multiproject injection, and long-term risk management.
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BibTeX
@article{wang2026basinscale,
title = {{Basin-Scale Heterogeneity in CO2 Geological Storage: Mechanisms, Prediction, and Management}},
author = {Xueting Wang and Keyao Lin and Ning Wei and Bowen Chen and Wendong Wang and Tianyu Liu},
journal = {ACS Omega},
year = {2026},
month = nov,
doi = {10.1021/acsomega.6c09382},
url = {https://pubs.acs.org/acsodf/article/doi/10.1021/acsomega.6c09382/5464912/Basin-Scale-Heterogeneity-in-CO2-Geological},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - JOUR
TI - Basin-Scale Heterogeneity in CO2 Geological Storage: Mechanisms, Prediction, and Management
AU - Xueting Wang
AU - Keyao Lin
AU - Ning Wei
AU - Bowen Chen
AU - Wendong Wang
AU - Tianyu Liu
PY - 2026
DA - 2026/11/05
JO - ACS Omega
DO - 10.1021/acsomega.6c09382
UR - https://pubs.acs.org/acsodf/article/doi/10.1021/acsomega.6c09382/5464912/Basin-Scale-Heterogeneity-in-CO2-Geological
AB - Large-scale CO2 geological storage is evolving from stand-alone sites toward million-tonne-scale, clustered, and basin-coordinated deployment, making basin-scale heterogeneity a key constraint on capacity utilization, sustained injection, and long-term storage security. However, existing studies have largely focused on individual reservoirs, capacity estimation, or localized risks, while a systematic review integrating tectono-sedimentary evolution, reservoir–caprock assemblages, fault-controlled hydrodynamics, and multisite interference remains lacking. Based on representative sedimentary basins and engineering projects, this study reviews multisource characterization, scale transformation, multiphysics coupling, probabilistic prediction, monitoring-informed updating, and coordinated management within a “geological foundation–storage performance–prediction and regulation” framework. The results indicate that reservoir–caprock discontinuities, fault connectivity, and pressure boundaries jointly control dynamic storage capacity, pressure footprints, plume migration, trapping efficiency, and leakage risk; although multilayer utilization can increase storage capacity, it may intensify pressure superposition and cross-formational flow. This study proposes development pathways centered on pressure-constrained capacity assessment, probabilistic prediction, full-life-cycle simulation, and basin digital twins, providing a basis for regional resource allocation, coordinated multiproject injection, and long-term risk management.
SN - 2470-1343
ER -