Estimation and uncertainty analysis of the CO2 storage volume in the sleipner field via 4D reversible-jump markov-chain Monte Carlo SCIE SCOPUS

Cited 6 time in WEB OF SCIENCE Cited 5 time in Scopus
Title
Estimation and uncertainty analysis of the CO2 storage volume in the sleipner field via 4D reversible-jump markov-chain Monte Carlo
Author(s)
Cho, Yongchae; Jun, Hyunggu
Alternative Author(s)
전형구
Publication Year
2021-05
Abstract
Many scientists have developed technology to store CO2 in the subsurface and to monitor the storage conditions to comply with the requirements for zero detectable leakage and greenhouse gas control. The goal of this research is to propose a novel workflow to estimate the stored CO2 volume and to quantify the uncertainty of the injected volume. We implemented geophysical stochastic inversion using the time-lapse 3D seismic volumes as inputs, which provides an indirect estimation of the velocity changes and the migration path of the injected gas content. When performing the inversion, we employed the reversible-jump approach and used the Sleipner time-lapse 3D seismic volumes to demonstrate the proposed workflow. The inversion result was validated via forward modeling and pseudo well log interpretation. We then built a structural geology model and populated porosity logs by performing 500 realizations for volumetric analysis. In a comparison of the measured volume of the injected gas via volumetric analysis results, the predicted subsurface CO2 volume linearly increases in the same phase with the injection rate, and the volume estimation error is less than 17%.
ISSN
0920-4105
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/41317
DOI
10.1016/j.petrol.2020.108333
Bibliographic Citation
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING, v.200, 2021
Publisher
ELSEVIER
Keywords
Carbon capture and sequestration; Time-lapse monitoring; Markov-chain Monte Carlo; Uncertainty analysis; Volume estimation
Type
Article
Language
English
Document Type
Article
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