A pressure-monitoring method to warn CO2 leakage in geological storage sites

Park, Yong-Chan; Huh, Dae-Gee; Park, Chan Hee

doi:10.1007/s12665-012-1667-2

Cited by 21 publications

(9 citation statements)

References 19 publications

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“…Also, Nogues et al [12] developed an analytical solution to estimate the CO 2 and brine leakage from pressure variations observed at monitoring wells and investigated optimal location of the monitoring wells to improve leakage detection. Park et al [13] proposed a methodology to detect CO 2 leakage by measuring pressure changes at monitoring wells with a constrained distribution. Sun and Nicot [14] presented an inversion method based on a global optimization algorithm to identify CO 2 leakage through leaky wells from pressure anomalies observed in the layers overlying the injected aquifer.…”

Section: Introductionmentioning

confidence: 99%

Detection of potential leakage pathways from geological carbon storage by fluid pressure data assimilation

González‐Nicolás

Baù

Alzraiee

2015

Advances in Water Resources

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One of the main concerns of geological carbon storage (GCS) systems is the risk of leakage through "weak" permeable areas of the sealing formation or caprock. Since the fluid pressure pulse travels faster than the carbon dioxide (CO 2) plume across the storage reservoir, the fluid overpressure transmitted into overlying permeable formations through caprock discontinuities is potentially detectable sooner than actual CO 2 leakage occurs. In this work, an inverse modeling method based on fluid pressure measurements collected in strata above the target CO 2 storage formation is proposed, which aims at identifying the presence, the location, and the extent of possible leakage pathways through the caprock. We combine a three-dimensional subsurface multiphase flow model with ensemble-based data assimilation algorithms to recognize potential caprock discontinuities that could undermine the long-term

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Section: Introductionmentioning

confidence: 99%

Detection of potential leakage pathways from geological carbon storage by fluid pressure data assimilation

González‐Nicolás

Baù

Alzraiee

2015

Advances in Water Resources

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“…The rate of injection should be such that will not offset the stability of the system; however, the introduction of fluid will lead to an increase in the formation pressure, which without proper monitoring and control may result in mechanical failure of the material. As indicated in Bauer et al (2012) and Park et al (2012), tracking pressure development as the CO 2 is being injected and during post-mortem periods is essential in ensuring safety limits are not exceeded. An alternative measure of the evolution of fluid pressure can be achieved via changes in in-situ stress conditions.…”

Section: Introductionmentioning

confidence: 99%

Carbon dioxide injection and associated hydraulic fracturing of reservoir formations

Eshiet

Sheng

2013

Environ Earth Sci

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The storage potential of subsurface geological systems makes them viable candidates for long term disposal of significant quantities of CO 2 . The geo-mechanical responses of these systems as a result of injection processes as well as the protracted storage of CO 2 are aspects that require sufficient understanding. A hypothetical model has been developed that conceptualises a typical well-reservoir system comprising an injection well where the fluid (CO 2 ) is introduced and a production/abandoned well sited at a distant location. This was accomplished by adopting a numerical methodology (Discrete Element Method), specifically designed to investigate the geo-mechanical phenomena whereby the various processes are monitored at the inter-particle scale. Fracturing events were simulated. In addition, the influence of certain operating variables such as injection flow rate and fluid pressure was studied with particular interest in the nature of occurring fractures and trend of propagation, the pattern and magnitude of pressure build-up at the well vicinity, pressure distribution between well regions and pore velocity distribution between well regions.Modelling results generally show an initiation of fracturing caused by tensile failure of the rock material at the region of fluid injection; however, fracturing caused by shear failure becomes more dominant at the later stage of injection. Furthermore, isolated fracturing events were observed to occur at the production/abandoned wells that were not propagated from the injection point. This highlights the potential of CO 2 introduced through an injection well, which could be used to enhance oil/gas recovery at a distant production well. The rate and magnitude of fracture development is directly influenced by the fluid injection rate. Likewise, the magnitude of pressure build-up is greatly affected by the fluid injection rate and the distance from the point of injection.The DEM modelling technique illustrated provides an effective procedure that allows for more specific investigations of geo-mechanical mechanisms occurring at sub-surface systems. The application of this 2 Corresponding Author:Address: School of Civil Engineering, University of Leeds, UK e-mail: y.sheng@leeds.ac.uk 2 methodology to the injection and storage of CO 2 facilitates the understanding of the fracturing phenomenon as well as the various factors governing the process.

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“…The topic of CO 2 storage (CCS) has been recently discussed in the Thematic Issue ''The CLEAN project in the context of CO 2 storage and enhanced gas recovery'' (Kuehn et al 2012) where particularly studies from Germany, Korea, United States and Norway have been presented including benchmark and model comparison studies Kolditz et al 2012;Park et al 2012;Mukhopadhyay et al 2012;Mykkeltvedt and Nordbotten 2012). Beside of CCS Singh et al 2014;Tian et al 2014), the Special Issue ''Underground storage of CO 2 and energy'' in the framework of the third Sino-German conference in May 2013 focused on comparison of CCS with CCUS (Harrison and Falcone 2014), carbon geological utilization Ganzer et al 2014;Gou et al 2014;Pudlo et al 2015;Shen et al 2015), and energy storage (Bérest et al 2014;Zhang et al 2014).…”

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confidence: 99%