Tenth Annual Conference on Carbon Capture & Sequestration

Transcription

1 Tenth Annual Conference on Carbon Capture & Sequestration Decision Making Tools / Criteria A New Carbon Capture and Storage Initiative in Saudi Arabia: Development of an Innovative GIS-based System for Managing Source-Sink Matching Scenarios Pierre Le Thiez, Yann Le Gallo (Geogreen), Murad Barghouty, Saud Al-Fattah (KAPSARC), Damien Rambourg, Alexandre Brugeron (BRGM), Hervé Quinquis (IFPEN) Acknowledgements: KFUPM, and Saudi Aramco s Cartography May 2-5, 2011 David L. Lawrence Convention Center Pittsburgh, Pennsylvania

2 KAPSARC at a glance The King Abdullah Petroleum Studies and Research Center (KAPSARC) was established in 2008, as a future-oriented research and policy center committed to energy and environmental research and analysis: CCS project launched in 2010: Framework for Carbon Capture and Sequestration (CCS) Program in the Kingdom of Saudi Arabia in collaboration with Geogreen, IFP Energies nouvelles, BRGM, King Fahd University of Petroleum and Minerals (KFUPM), and Saudi Aramco with the aim to: Establish a comprehensive understanding of the current state of the art in carbon capture and storage from the perspectives of technology, policy, implementation models and applications. Develop a framework for implementing an effective CCS program in Saudi Arabia. Develop a Geographical Information System (GIS) based tool for Source-sink matching in the Kingdom

3 Presentation outline GIS Tools objectives Workflow, concepts and implementation CO 2 storage capacity calculation Automatic routing of pipelines for source-sink matching Conclusions

4 Purpose of the GIS tool Build a GIS-based tool to run source-sink matching scenarios in the Kingdom of Saudi Arabia: Map all data related to geology and potential constraints: CO 2 sources by categories and size of emissions in Saudi Arabia Geological formations and flow units with a 3D organization based on the Kingdom stratigraphic chart Constraints to take into account for potential storage site selection: urbanized areas, protected zones, water supply wells, natural seismicity, zones reserved for hydrocarbon exploration and production Define and draw potential storage reservoir(s) Calculate theoretical storage capacity for selected reservoir(s) use of CSLF formulas Calculate optimum pipeline transport routes between selected sources and defined storage site(s) through an optimization scheme taking into account

5 Overall workflow 3D processing and visualization of all geological information and constraints Selecting the potential CO 2 storage site(s) and automatic capacity calculation Generation of 2D cost function for automatic drawing of optimized pipeline routing between selected CO 2 sources and potential CO 2 storage(s)

6 Conceptualization of the GIS LITHO UNITS : The smaller horizon of the litho-stratigraphic succession, at different hierarchies: formations, members, beds. For the internal purpose of the GIS, unconformity surfaces (e.g. horizons without thickness) are considered LITHO UNITS as well FLOW UNITS : A single or comprehensive hydraulic system composed of one or several LITHO UNITS having similar hydrogeological properties. Potential reservoir composed of one or several geological formations Caprock Litho unit 1 Flow unit Litho unit 2 Litho unit 3

7 From stratigraphic chart to definition of units

8 Conceptual sketch cross section Geological formation No reservoir Reservoir No reservoir Outcrop Well field Surface HC field Tight 1000 m Shallow Supercritical CO 2 Fresh Deep Saline Saline HC Shale

9 Conceptual sketch top view Geological formation No reservoir Well field Reservoir No reservoir Shallow 1000 m Outcrop Tight Fresh Supercritical CO 2 HC HC field Shale Potential CO 2 storage Saline

10 Example of mapping various constraints Surface constraints Zones likely to be excluded from potential storage zones KAPSARC

11 Natural Seismicity example KAPSARC

12 Example of potential CO 2 storage reservoir Extension of the selected formation Potential target for CO 2 geologic storage KAPSARC

13 CO 2 sources Industrial CO 2 sources in KSA (power, desalination, refineries, cement, chemicals, gas plants) Potentially addressable with CCS (From IEAG-GHG and Carbon Monitoring for Action databases) KAPSARC

14 Potential CO 2 storage delineation Drawing of 2 potential locations for CO 2 storage in a flow unit KAPSARC

15 Calculation of aquifer storage capacity (CSLF) M CO2 = A x h x Φ x ρ CO2 x E M CO2 = Mass of CO 2 A = aquifer area, or area of maximum extent of the CO 2 plume ( Storage A: 6750 km 2 ) h = net aquifer thickness ( 99 m) Φ = average porosity ( 0.3) ρ CO2 = average CO 2 density evaluated at pressure and temperature that represents storage conditions, ρ CO2 = f(p, T) ( 210 bar, 85 C, 584 kg/m 3 ) E = storage efficiency, defined as the fraction of the total pore volume most likely accessible to CO 2, E= f(depth, Lithology) ( 0.019, from IEA-GHG/EERC study in 2009) Theoretical capacity for storage A 2.2 Gt CO 2

16 Decision Support System Based on two successive tools: Grid Computation, which aims at calculating a cost grid (optimum function) from a set of relevant constraints, chosen by user. Path Computation which identifies the more favorable paths to match CO 2 sources and potential sinks by minimizing the total constraints cost. The constraints which can be taken into account for the calculation of the cost grid can belong to any of the following types: Morphological, as ground surface slope, Transport infrastructures such as roads, railways or existing pipelines, Urbanized areas, Environmental and natural protected zones

17 How to compute the Cost grid (1) Four categories of constraints: Combinatorial constraints are expressed by the user through relative weights, which are normalized by the system in percentage. In the same cell, their weights are added, as shown in the following figure. They will increase the relative cost to pass through the areas on which they exist Example: Protected zones Contextual constraints correspond to constraints that will increase or decrease the resulting cost of the combination of combinatorial constraints Example: use of an existing pipeline routing Typological constraints are the ones that will prevail over all the previous ones (combinatorial and contextual). Two types of typological constraints exist: Barriers, where cost is maximum (100%) By-passes, where cost is minimun (0%) Exclusion constraints are constraints that prevail over all the previous constraints (combinatorial contextual and typological). They correspond to areas on which no path is possible

18 How to compute the Cost grid (2) Example of Contextual constraints Expressed by the user through percentage In each cell, apply a percentage to combinatorial constraints Increase or Decrease resulting cost of combinatorial constraints Values normalized between [ ]

19 Example of pipeline routes automatic calculation KAPSARC

20 Conclusions An innovative GIS-based tool has been developed for the purpose of source-sink matching in the Kingdom Saudi Arabia Process and mapping of geological formations and flow units in 3 dimensions Mapping of all constraints (zones reserved for oil & gas exploration and production, water wells, protected zones, urbanized areas, natural seismicity) Delineation of potential CO 2 storage reservoirs with automatic calculation of theoretical capacity (DOE/CSLF) Automatic routing of pipelines between CO 2 emitters and potential storage locations through an optimization procedure