کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
242958 501913 2013 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Modelling and monitoring of geological carbon storage: A perspective on cross-validation
موضوعات مرتبط
مهندسی و علوم پایه مهندسی انرژی مهندسی انرژی و فناوری های برق
پیش نمایش صفحه اول مقاله
Modelling and monitoring of geological carbon storage: A perspective on cross-validation
چکیده انگلیسی

Effective monitoring and numerical simulations are essential to understanding the implications of long-term geological carbon storage; in particular, the predictions of CO2 plume flow under storage conditions, storage integrity of sites, and the design and operational aspects of the CO2 storage projects could be significantly supplemented. Site monitoring data can assure reliability and accuracy of the numerical simulation while numerical prediction results will provide more detailed information on the storage process. The cross-validation between numerical modelling results and monitoring data can play a major role in the development of carbon capture and storage technology. This paper briefly reviews the monitoring and modelling technologies associated with geological carbon storage. In addition, the spatial and temporal resolutions of the numerical simulations are highlighted, while estimations on the resolutions of some commonly used monitoring technologies are also presented. It is revealed that there are gaps in the correlations and cross-validation between the two technologies, where a possible option to reduce the gaps is to enforce more research efforts on multi-scale modelling and appropriate variable correlations.


► This paper reviews the monitoring and modelling technologies for geological carbon storage.
► The spatial and temporal resolutions of the numerical simulations are highlighted.
► Estimations on the resolutions of some commonly used monitoring technologies are also presented.
► There are gaps in the possible cross-validation between the two technologies.
► Multi-scale modelling and appropriate variable correlations may provide an option to reduce the gaps for cross-validation.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Applied Energy - Volume 112, December 2013, Pages 784–792
نویسندگان
, , ,