Time-lapse pressure tomography for characterizing CO2 plume evolution in a deep saline aquifer
Publisher DOI
Abstract
A time-lapse pressure tomography inversion approach is applied to characterize the CO2 plume development in a virtual deep saline aquifer. Deep CO2 injection leads to flow properties of the mixed-phase, which vary depending on the CO2 saturation. Analogous to the crossed ray paths of a seismic tomographic experiment, pressure tomography creates streamline patterns by injecting brine prior to CO2 injection or by injecting small amounts of CO2 into the two-phase (brine and CO2) system at different depths. In a first step, the introduced pressure responses at observation locations are utilized for a computationally rapid and efficient eikonal equation based inversion to reconstruct the heterogeneity of the subsurface with diffusivity (D) tomograms. Information about the plume shape can be derived by comparing D-tomograms of the aquifer at different times. In a second step, the aquifer is subdivided into two zones of constant values of hydraulic conductivity (K) and specific storage (Ss) through a clustering approach. For the CO2 plume, mixed-phase K and Ss values are estimated by minimizing the difference between calculated and “true” pressure responses using a single-phase flow simulator to reduce the computing complexity. Finally, the estimated flow property is converted to gas saturation by a single-phase proxy, which represents an integrated value of the plume. This novel approach is tested first with a doublet well configuration, and it reveals a great potential of pressure tomography based concepts for characterizing and monitoring deep aquifers, as well as the evolution of a CO2 plume. Still, field-testing will be required for better assessing the applicability of this approach.
Date Issued
2015
Publication Type
Article
Subject(s)
Language(s)
en
Author(s)
Hu, L. | |
Bayer, P. | |
Tatomir, A. | |
Sauter, M. | |
Brauchler, R. |
Additional Credits
Journal
Journal of Greenhouse Gas Control
Publisher
Elsevier
ISSN
1750-5836
Access(Rights)
restricted