CO 2 Storage Capacity Evaluation in Deep Saline Aquifers for an Industrial Pilot Selection. Methodology and Results of the France Nord Project
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1 CO 2 Storage Capacity Evaluation in Deep Saline Aquifers for an Industrial Pilot Selection. Methodology and Results of the France Nord Project CLAR CO 2-14 Janvier 2015
2 France Nord Project > Joint Industry Project Funded by ADEME (French Environment and Energy Management Agency) 4 public research institutes 7 industrial partners > Main goals Feasibility of CCS in the Northern part of Paris Basin (France) This presentation is reviewing the main findings concerning the CO 2 storage evaluations. Qualify, on the basis of available data a site to store at least 200Mt of CO 2 in the deep saline aquifers of the Paris Basin.
3 Aquifer selection > In the Paris Basin Geographical extension and petrophysical properties for storing large volumes of CO 2 Deeper than 1000 meters Aquifer has to be undrinkable and unsuitable for agricultural use (salinity > 10 g/l) No conflict with other (potential) activity 3 stratigraphics targets : Buntsandstein sandstones Keuper fm. (Donnemarie, Chaunoy, Boissy) Dogger limestones (Bathonian + Callovian)
4 Regional modeling (basin scale) > Objectives : Select one or more sites with at least 200Mt CO 2 storage capacity. > 3 regional models Buntsandstein (BRGM) Keuper (IFP-EN) Dogger (BRGM) - with a common structural scheme, - from available data, - petrophysical filling at basin scale - definition of the boundary conditions of aquifers - selection of suitable injection sites During this phase of the project, 5 sites with a 200 Mt CO2 potential storage capacity were identified. 3 site were subject to a more detailed modeling (Storengy)
5 Buntsandstein Regional modeling > Static modeling model size : 200 km x 200 km 3 zones / 10 layers cells size : 2000 x 2000 m cells 4 properties : Porosity Permeability Temperature Salinity
6 Mt de CO2 Buntsandstein Regional modeling > Injection simulations 4 wells distance between wells : 30km 202 Mt injected in 50 years mainly in the upper zone (Grès à Voltzia) CO 2 injecte par Faciès GVZ CPCI GVG Années
7 Buntsandstein Regional modeling > Post injection - overpressure 15 years 30 years 150 years 300 years
8 Buntsandstein Regional modeling > Post injection - gas saturation 300 years 1500 years after 1500 years, lateral migration of CO2 : 65km in the freshwater area along Seycheprey fault.
9 Buntsandstein Site modeling > Optimisation of the gridding arround injection wells along the Secheprey fault > Review of the petrophysics permeability capillary pressure (Pc) > Optimisation of the wells location Storage potential reassessed to 133Mt Confirmation of CO 2 migration in the freshwater area
10 Buntsandstein Site modeling > Alternative case Injection west of the Marne fault Water injection east of the fault 23 wells (5 CO 2 injectors, 10 brine producers and 8 brine injectors) Storage potential : 87.5 Mt Necessity to produce brine to keep reasonnable pressure in the reservoir.
11 Keuper Regional modeling > Static modeling model size : 400km x 520 km 8 zones cells size : 4000 x 4000 m cells Rhétien marin Boissy sup. & Inf. Chalain Argiles inférieur intermédiaire Donnemarie s Chaunoy Buntsandstein
12 Keuper Regional modeling > Static modeling 3 properties : Porosity Permeability Effective thickness Chaunoy Chaunoy Chaunoy
13 Keuper Regional modeling > Injection simulations 2 area of interest : Keuper Nord Keuper Sud Keuper Nord : 6 wells necessary to inject 200 Mt of CO 2 in 50 years. Keuper Sud: SW of the area, 1 well can be sufficient to inject 200 Mt of CO 2 in 50 years.
14 Keuper Regional modeling > Post injection, Example of Keuper Sud with 4 wells 1050 years overpressure
15 Keuper Regional modeling > Post injection, Example of Keuper Sud with 4 wells 50 years gas saturation 1050 years
16 Keuper Sud Site modeling > Refinement of the model 3,98 Boissy sup. Vertical layering from 8 to 28 layers, 2,07 New constraints on the structural scheme, Petrophysical analysis 38,76 from cores, logs and production test. Modèle IFP Modèle IFP STORENGY STORENGY Hu moyen Hu moyen Unités v #1 Layering Unités proposé v #1 Layering proposé modèle local Hu moyen modèle local 0 Rhétien marin 0 argiles Rhétien supérieurs marin argiles argiles supérieurs supérieurs (couverture) argiles supérieurs (couvertu 0 Boissy sup / Chalain Sup Chalain Boissy Supérieur sup / Chalain (Argiles Sup et chenaux Chalain mal Supérieur connectés) (Argiles et 0,34 chenaux m 3,98 Boissy sup. Boissy Inf / Chalain Moy Chalain Boissy Moyen Inf / Chalain sup (Argiles Moy et chenaux Chalain Moyen mal connectés) sup (Argiles et 2,69 chenaux Boissy inf. Boissy inf. 2,07 Chalain Moyen inf (Argiles ) Chalain Moyen inf 0(Argile Chalain Inf Chalain Chalain Inférieur Inf (Argiles et chenaux Chalain mal Inférieur connectés) (Argiles et chenaux 2,74 m 0 Chalain inf. 0 Chalain Chalain Couv. inf. Chalain Couv. Chalain Couv. Chalain Couv. 0 Dolomie Dolomie Dolomie (réservoir) Dolomie (réservoir) 4,82 Couverture CCS ou absence couverture Couverture CCS ou absence 0 cou Chaunoy Marnes IS Chailly Chaunoy chaunoy Marnes Sup IS Chailly chaunoy Chailly chaunoy Sup Sup (réservoir) Chailly chaunoy Sup 4,28 (réserv Couverture CCM Couverture CCM Couverture CCM Couverture 0CCM 38,76 Chailly chaunoy Moy. Chailly Chailly chaunoy chaunoy Moy. moyen sup (réservoir) Chailly chaunoy moyen 3,02 sup (rés CCMCI CCM inf CCMCI 0 CCM inf 2,2 Couverture CCI Couverture CCI Couverture CCI Couverture 0CCI Chailly chaunoy Inf. Chailly chaunoy Chailly chaunoy Inf. inf. (réservoir) Chailly chaunoy inf. 0,27 (réserv Arg. Interm. Sup. Arg. Interm. Sup. Arg. Interm. Sup. Arg. Interm. 0Sup. Argiles et Grès Argiles AI R1 et Grès AI R1 AI R1 (argiles et grés) intermédiaires intermédiaires AI R1 (argiles 3,06 et grés) 2,68 2,68 AI R2 AI R2 AI R2 (argiles et grés) AI R2 (argiles 2,44 et grés) Arg. Interm. Inf Arg. Interm. Inf Arg. Interm. Inf Arg. Interm. 0Inf Reduction of the net thickness estimation for all layers 40,44 (~2.5 factor) 40,44 0,29 Donnemarie Sommital Donnemarie Donnemarie Sommital Sommital (reservoir) Donnemarie Sommital 7,5 (reser Donnemarie Couv. Donnemarie Sup. Couv. Sup. Couv. Sup. Couv. Sup. 0 Donnemarie Sup. Donnemarie Donnemarie Sup. Sup. (réservoir) Donnemarie Sup. 0,62 (réservo Couv. Moy. Couv. Moy. Couv. Moy. Couv. Moy. 0 Donnemarie Moy. Donnemarie Donnemarie Moy. Moy. (réservoir) Donnemarie Moy. 4,08 (réservo Couv. Inf. Couv. Inf. Couv. Inf. Couv. Inf. 0 Donnemarie Inf. Donnemarie Donnemarie Inf. Inf. (reservoir) Donnemarie Inf. 4,71 (reservo Couv. Couv. Couv. Couv. 0 Buntsandstein (réservoir) Buntsandstein (réservoir Bunt 0,29 Bunt Bunt 7,12 Socle Socle
17 Keuper Sud Site modeling > Injection simulation with the new petrophysical models 1 model with K/Phi laws computed by layers but no facies modeling Storage potential : 140 Mt with 15 wells 1 model with facies integration. K/Phi relationships computed for each facies in each layer. Storage potential : 54 Mt with 15 wells chalain Chailly- Chaunoy Grès Intermédiaires Donnemarie
18 Keuper Nord Site modeling > Refinement of the model Net thickness revisited No advanced geological studies > Injection simulations Storage potential : 40 Mt with 20 wells
19 Dogger Regional modeling > Static modeling model size : 500km x 700 km 7 zones cells size : 5000 x 5000 m cells facies modeling
20 Dogger Regional modeling > 3 K-Phi relationship were investigated > Due to a complex diagenesis history of the Dogger limestones, dual porosity / permeability system occurs (presence of pathways of very high permeability) > As there is no predictive localization of these drains, we are not able to control the evolution of the CO 2 plume and its migration. > Moreover, there is a risk that injection of 200 Mt of CO 2 in the Dogger would impact the geothermal activity. Because of these uncertainties on the Dogger geological properties and the possibility of an interaction with geothermal energy development within this level, this stratigraphic target was discarded.
21 Storage capacity identified Site Potential of injection # of wells Comments Keuper Nord 40 Mt 20 wells Keuper Sud 140 Mt 15 wells Keuper Sud 54 Mt 15 wells Without facies modeling (optimistic case) With facies modeling (pessimistic case) Injection east of the Faille de la Marne. Buntsandstein 157 Mt 21 wells Buntsandstein 87 Mt 23 wells Risk of CO 2 migration towards the drinkable part of the aquifer was considered as too important. Injection west of the Faille de la Marne Aquifer properties significantly degraded compared to the previous case All these result are largely under the objectives of the France Nord project > 21
22 Comparison with previous estimations JOULE II (1996) Projets GESTCO (2003) et EU GEOCAPACITY (2009) France Nord ( ) Traps Traps Total Conservative Flow models Dogger 189 Mt (E=0.18%) 9 Mt (E=0.01%) 4320 Mt (E=6%) 1440 Mt (E=2%) Potential Conflict with geothermal resources Keuper 529 Mt (E=0.18%) 130 Mt (E=0.18%) 4331 Mt (E=6%) 72 Mt (E=0.1%) Mt Buntsandstein Conflict with fresh water 529 Mt (E=0.18%) Mt (E=6%) 5880 Mt (E=2%) ~ 90 Mt Other fm. 91 Mt Mt 530 Mt - TOTAL 809 Mt 668 Mt Mt 7922 Mt Mt > 22
23 Conclusions > The assessment phase of the project has shown that it was not possible to identify a single site to store 200 Mt CO 2. The best identified site is the Keuper Sud site. Its storage capacity ranges between 54 and 140 Mt, with the necessity to drill about 15 injection wells over a large area (about 3000 km 2 ). > The constraint of the acceptable overpressure is the main obstacle to a massive injection of CO 2 in saline aquifers. > Do not take into account this phenomenon leads to an overestimation of storage capacity as shown in comparison with previous capacity estimates. > 23
24 Thank you for your attention Acknowledgements This work has been done within the France Nord project funded by ADEME (French Environment and Energy Management Agency) and industrial partners. The authors also thank all the technical contributors that have enabled to perform this work, namely: T. Fargetton, D. Dequidt, K. Djaouti, F. Delsante, P. Egermann and R. Nabil from Storengy; J.-P. Gely, and R. de Lannoy from GDF SUEZ; S. Gabalda, C. Kervevan C. Chiaberge and M. Gastine from BRGM; J.C. Lecomte, P. Houel, J.M. Daniel, A. Fornel and F. Roggero from IFPEN; D. Pourtoy, L. de Marliave and G. Moutet from Total. The full version of the article is available online at:
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