Methodology for Estimating Offshore CO 2 Storage Resource ... · is an attractive alternative to...
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Ф Effective Ф Total Phase II leverages NETL’s Offshore Risk Modeling Suite to characterize risk and uncertainty Quantify and communicate uncertainty to create better understanding of the importance of natural seeps and faults These tools are capable of measuring P-T adjustments required to assess risk O&G Infrastructure Geologic Features % Ф Effective % Ф Total Apply methods to remaining U.S. Gulf of Mexico Evaluate robustness of offshore efficiency factors in other U.S. waters A peer-reviewed publication on the methodology and the associated tool Build a user-friendly tool to implement logic scripts Release updated versions of tool via EDX Methodology for Esmang Offshore CO 2 Storage Resource Potenal in Saline Aquifers Lucy Romeo 1,2 , Kelly Rose 1 , Jennifer Bauer 1 , Burt Thomas 1,2 , Jenny DiGiulio 1,2 , Kate Jones 1,3 , Emily Cameron 1,2 , and Roy Miller 1,3 1 U.S. Department of Energy, National Energy Technology Laboratory, Albany OR; 2 AECOM, Albany OR; 3 ORISE, Albany, OR Research & Innovation Center Abstract: Important differences exist between onshore and offshore geological systems that affect the capacity, cost, and permanence of CO2 storage. In particular, offshore carbon storage is an attractive alternative to onshore storage where point sources of CO2 can be co-located with subsea storage reservoirs, thereby minimizing the risks of leakage to the public. Offshore systems are typically younger, unlithified, and have higher total porosity compared to onshore systems —all considerations that affect the performance of hypothetical offshore storage efforts. In general, offshore data is more scarce than onshore data due in part to the shorter history of offshore oil exploration and production. NETL has adapted the DOE storage resource calculation methodology to incorporate available offshore public and private geodata derived from oil and gas exploration in the US waters of the Gulf of Mexico. Here we present the spatially-driven methodology for estimating offshore storage resource potential including data sources and preliminary calculations for determining efficiency factors. Efficiency factors for the offshore include effective porosity, area, and height of the sand column of interest. This poster also summarizes Phase II of this project, which leverages tools and methods from NETL’s Offshore Risk Modeling suite to spatially assess potential risk factors including infrastructure, geologic, and environmental constraints. Data Acquisition Selected Well Logs with Saline Properties STA Domains with Log Points Selected Well Logs and Geologically-defined Domains Calculating Storage Efficiency Storage efficiency (E Saline ) is a function of the displacement efficiency components and the aquifer characteristics Defines available pore space Displacement parameters Science & Engineering To Power Our Future POC: Kelly Rose, [email protected] Acknowledgments: This technical effort was performed in support of the National Energy Technology Laboratory’s ongoing research under the RES contract DEFE0004000 and the Bureau of Safety and Environmental Enforcement (BSEE), U.S. Department of the Interior, Washington, D.C., under agreement E14PG00045. Disclaimer: This project was funded by the Department of Energy, National Energy Technology Laboratory, an agency of the United States Government, through a support contract with AECOM. Neither the United States Government nor any agency thereof, makes any warranty, expressed or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reject those of the United States Government or any agency thereof. Storage efficiency is used to calculate the total storage resource CO 2 (G CO2 ) Calculation disccused in Goodman et al. (2016) This method (Cameron et al. 2018) is built specifically for offshore environment, where density (ρ ) is derived as a function of subsea pressure and temperature at a given depth (see diagram to the right) E A : Ratio of net area to total area suitable for storage resource E H : Ratio of net thickness to total thickness of formations suitable for storage E Ф : Ratio of effective porosity to total porosity E V : Displacement factors E d : Microscopic displacement factors A T : Total area suitable for storage h T : Gross thickness of suitable formations Ф T : Total porosity ρ : Density of CO2 at P, T Faults Salts Leakage Pathways E h Height Efficiency Ratio of net to total vertical thickness of formation suitable for storage Height Net Height Total E A Area Efficiency Area (km2) minus potential leakage pathways Total area (km) Area Net Ratio of net to total area suitable for CO2 storage Area Total E V - Displacement factors E d - Microscopic displacement factor × × E Ф Porosity ( Ф ) Efficiency Ф Effective Ф Total Ratio of effective porosity to total porosity Log Top (ft) Log Bottom (ft) Sand 1 (ft) Sand 2 (ft) Height Total Height Net = ∑ Sand 1 + ... + Sand n Height (ft) of formation suitable for CO2 storage Total height (ft) Portion of the total void space available for storage Ratio of the entire pore space in a rock to its bulk volume Area Net Area Total × Phase II: Understanding Spatial Risk & Uncertainty E V & E d Displacement Parameters Well log data, spatial information, literature = E Saline ρ = G CO 2 P10, P50, and P90 values Logic-based Python scripts were created to estimate storage efficiency (E Saline ) and the potential amount of storable CO2 (G CO2 ) This logic implements Monte Carlo simulations and pseudo- random distribution sampling to known data This work compliments the CO2 Storage prospeCtive Resource Estimation Excel aNalysis (CO2-SCREEN) Tool (Sanguinito et al. 2017) Streamlining Methods with Logic-based Scripts References Cameron, E., Thomas, R., Bauer, J., DiGiulio, J., Disenhof, C., Galer, S., Jones, K., Mark-Moser, Miller, R., Romeo, L., Rose, K. Estimating Carbon Storage Resources in Offshore Geologic Environments; NETL-TRS-X-2018; NETL Technical Report Series; U.S. Department of Energy, National Energy Technology Laboratory: Albany, OR, 2018. Goodman, A., Sanguinito, S., & Levine, J. S. (2016). Prospective CO 2 saline resource estimation methodology: Refinement of existing US-DOE-NETL methods based on data availability. International Journal of Greenhouse Gas Control, 54, 242-249. Mark-Moser, M.; Miller, R.; Rose, K.; Bauer, J.; Disenhof, C. Detailed Analysis of Geospatial Trends of Hydrocarbon Accumulations, Offshore Gulf of Mexico; NETL-TRS-13-2018; NETL Technical Report Series; U.S. Department of Energy, National Energy Technology Laboratory: Albany, OR, 2018; p 108. DOI: 10.18141/1461471. Rose, K., 2016, Signatures in the Subsurface – Big & Small Data Approaches for the Spatio-Temporal Analysis of Geologic Properties & Uncertainty Reduction, 162 pgs, http://hdl.handle.net/1957/59459 Sanguinito, S.; Goodman, A. L.; Levine, J. S. NETL CO2 Storage prospeCtive Resource Estimation Excel aNalysis (CO2-SCREEN) User’s Manual; NETL-TRS-X-2017; NETL Technical Report Series; U.S. Department of Energy, National Energy Technology Laboratory: Pittsburgh, PA, 2017; p 32. E h E A E Ф E V E d × × × × A T A N Draft Outputs A T h T Φ T × × × × E Saline Draft Outputs G CO 2 Draft Outputs G CO 2 Key Takeaways Values Delivered Improved the accuracy of offshore saline resource estimations Offshore tailored efficiency terms from DOE carbon storage method Data-driven technical assessment of offshore storage resources through integration of NETL’s spatial, analytical tools Compliments CO2-SCREEN tool, data, models to improve existing stakholder access and utilization Next Steps Federal Waters Lorem ipsum E Saline = E A × E h × E Ф × E V × E d Calculating the Amount of Storable CO 2 G CO2 = A T × h T × Ф T × ρ × E Saline 0 100 miles TX LA MS AL FL Generate information on saline properties from well logs within a subset of STA domains to determine CO 2 storage efficiency and potential in saline reservoirs. NETL’s STA approach defines spatially-distinct geologic domains based on a regions lithologic, structural, and alteration histories (Mark-Moser et al. 2018; Rose 2016). Applied private and public geologic data to estimate storage efficiency and the storage resource available for CO 2 in the Gulf of Mexico Interpret well logs for storage resource parameters: sand thickness (reservoirs), shale thickness (seal), and sand porosity Selected well log distributions leveraging NETL’s Subsurface Trend Analysis (STA) (Mark-Moser et al. 2018) For each domain, selected at least 50 well logs, if available 400 location-based records throughout 18 of the STA-defined domains
Transcript of Methodology for Estimating Offshore CO 2 Storage Resource ... · is an attractive alternative to...
ФE�ectiveФTotal
Phase II leverages NETL’s O�shore Risk Modeling Suite to characterize risk and uncertainty
Quantify and communicate uncertainty to create better understanding of the importance of natural seeps and faults
These tools are capable of measuring P-T adjustments required to assess risk
O&G Infrastructure
Geologic Features
% ФE�ective
% ФTotal
Apply methods to remaining U.S. Gulf of Mexico Evaluate robustness of o�shore e�ciency factors in other U.S. waters A peer-reviewed publication on the methodology and the associated tool
Build a user-friendly tool to implement logic scripts
Release updated versions of tool via EDX
Methodology for Estimating Offshore CO2 StorageResource Potential in Saline AquifersLucy Romeo1,2, Kelly Rose1, Jennifer Bauer1, Burt Thomas1,2, Jenny DiGiulio1,2, Kate Jones1,3, Emily Cameron1,2, and Roy Miller1,31U.S. Department of Energy, National Energy Technology Laboratory, Albany OR; 2AECOM, Albany OR; 3ORISE, Albany, OR
Research &Innovation Center
Abstract: Important di�erences exist between onshore and o�shore geological systems that a�ect the capacity, cost, and permanence of CO2 storage. In particular, o�shore carbon storage is an attractive alternative to onshore storage where point sources of CO2 can be co-located with subsea storage reservoirs, thereby minimizing the risks of leakage to the public. O�shore systems are typically younger, unlithi�ed, and have higher total porosity compared to onshore systems —all considerations that a�ect the performance of hypothetical o�shore storage e�orts. In general, o�shore data is more scarce than onshore data due in part to the shorter history of o�shore oil exploration and production. NETL has adapted the DOE storage resource calculation methodology to incorporate available o�shore public and private geodata derived from oil and gas exploration in the US waters of the Gulf of Mexico. Here we present the spatially-driven methodology for estimating o�shore storage resource potential including data sources and preliminary calculations for determining e�ciency factors. E�ciency factors for the o�shore include e�ective porosity, area, and height of the sand column of interest. This poster also summarizes Phase II of this project, which leverages tools and methods from NETL’s O�shore Risk Modeling suite to spatially assess potential risk factors including infrastructure, geologic, and environmental constraints.
Data Acquisition
Selected Well Logswith Saline Properties
STA Domains with Log PointsSelected Well Logs and
Geologically-defined DomainsCalculating Storage E�ciency
Storage e�ciency (ESaline) is a function of the displacement e�ciency components and the aquifer characteristics De�nes available
pore spaceDisplacement
parameters
Science & Engineering To Power Our FuturePOC: Kelly Rose, [email protected]
Acknowledgments: This technical e�ort was performed in support of the National Energy Technology Laboratory’s ongoing research under the RES contract DEFE0004000 and the Bureau of Safety and Environmental Enforcement (BSEE), U.S. Department of the Interior, Washington, D.C., under agreement E14PG00045. Disclaimer: This project was funded by the Department of Energy, National Energy Technology Laboratory, an agency of the United States Government, through a support contract with AECOM. Neither the United States Government nor any agency thereof, makes any warranty, expressed or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any speci�c commercial product, process, or service by trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed herein do not necessarily state or reject those of the United States Government or any agency thereof.
Storage e�ciency is used to calculate the total storage resource CO2 (GCO2)
Calculation disccused in Goodman et al. (2016)
This method (Cameron et al. 2018) is built speci�cally for o�shore environment, where density (ρ) is derived as a function of subsea pressure and temperature at a given depth (see diagram to the right)
EA: Ratio of net area to total area suitable for storage resource
EH: Ratio of net thickness to total thickness of formations suitable for storage
EФ: Ratio of e�ective porosity to total porosity
EV: Displacement factors
Ed: Microscopic displacement factors
AT: Total area suitable for storage
hT: Gross thickness of suitable formations
ФT: Total porosity
ρ: Density of CO2 at P, T
FaultsSalts
Leakage Pathways
Eh HeightE�ciency
Ratio of net to total vertical thickness of
formation suitable for storage
HeightNet
HeightTotal
EA AreaE�ciency
Area (km2) minus potential leakage
pathways
Total area (km)
AreaNet
Ratio of net to total area suitable for CO2 storage
AreaTotal
EV - Displacement factors
Ed - Microscopic displacement factor× ×
EФ Porosity (Ф) E�ciency
ФE�ective
ФTotal
Ratio of e�ective porosity to total porosity
Log Top (ft)
Log Bottom (ft)
Sand1 (ft)
Sand2 (ft)Hei
ght To
tal
HeightNet = ∑ Sand1 + ... + Sandn
Height (ft) of formation suitable for CO2 storage
Total height(ft)
Portion of the total void space available for
storage
Ratio of the entire pore space in a rock to its bulk volume
AreaNet
AreaTotal
×
Phase II: Understanding Spatial Risk & Uncertainty
EV & Ed
DisplacementParameters
Well log data, spatial information, literature
=ESaline
ρ
=
GCO2 P10, P50, and P90 values
Logic-based Python scripts were created to estimate storage e�ciency (ESaline) and the potential amount of storable CO2 (GCO2)
This logic implements Monte Carlo simulations and pseudo- random distribution sampling to known data
This work compliments the CO2 Storage prospeCtive Resource Estimation Excel aNalysis (CO2-SCREEN) Tool (Sanguinito et al. 2017)
Streamlining Methods with Logic-based Scripts
References
Cameron, E., Thomas, R., Bauer, J., DiGiulio, J., Disenhof, C., Galer, S., Jones, K., Mark-Moser, Miller, R., Romeo, L., Rose, K. Estimating Carbon Storage Resources in O�shore Geologic Environments; NETL-TRS-X-2018; NETL Technical Report Series; U.S. Department of Energy, National Energy Technology Laboratory: Albany, OR, 2018.Goodman, A., Sanguinito, S., & Levine, J. S. (2016). Prospective CO 2 saline resource estimation methodology: Re�nement of existing US-DOE-NETL methods based on data availability. International Journal of Greenhouse Gas Control, 54, 242-249.Mark-Moser, M.; Miller, R.; Rose, K.; Bauer, J.; Disenhof, C. Detailed Analysis of Geospatial Trends of Hydrocarbon Accumulations, O�shore Gulf of Mexico; NETL-TRS-13-2018; NETL Technical Report Series; U.S. Department of Energy, National Energy Technology Laboratory: Albany, OR, 2018; p 108. DOI: 10.18141/1461471. Rose, K., 2016, Signatures in the Subsurface – Big & Small Data Approaches for the Spatio-Temporal Analysis of Geologic Properties & Uncertainty Reduction, 162 pgs, http://hdl.handle.net/1957/59459 Sanguinito, S.; Goodman, A. L.; Levine, J. S. NETL CO2 Storage prospeCtive Resource Estimation Excel aNalysis (CO2-SCREEN) User’s Manual; NETL-TRS-X-2017; NETL Technical Report Series; U.S. Department of Energy, National Energy Technology Laboratory: Pittsburgh, PA, 2017; p 32.
EhEA EФ EV Ed××××
AT
ANDraft O
utputs
AT hTΦT ××× ×
ESalineDraft O
utputs GCO2
Draft Outp
uts
GCO2
Key Takeaways
Values Delivered Improved the accuracy of o�shore saline resource estimations
O�shore tailored e�ciency terms from DOE carbon storage method
Data-driven technical assessment of o�shore storage resources through integration of NETL’s spatial, analytical tools
Compliments CO2-SCREEN tool, data, models to improve existing stakholder access and utilization
Next Steps
Federal Waters
Lorem ipsum
ESaline = EA × Eh × EФ × EV × Ed
Calculating the Amount of Storable CO2
GCO2 = AT × hT × ФT × ρ × ESaline
0 100 miles
TX
LA
MSAL
FL
Generate information on saline properties from well logs within a subset of STA domains to determine CO2 storage e�ciency and potential in saline reservoirs.
NETL’s STA approach de�nes spatially-distinct geologic domains based on a regions lithologic, structural, and alteration histories
(Mark-Moser et al. 2018; Rose 2016).
Applied private and public geologic data to estimate storage e�ciency and the storage resource available for CO2 in the Gulf of Mexico
Interpret well logs for storage resource parameters: sand thickness (reservoirs), shale thickness (seal), and sand porosity
Selected well log distributions leveraging NETL’s Subsurface Trend Analysis (STA) (Mark-Moser et al. 2018)
For each domain, selected at least 50 well logs, if available 400 location-based records throughout 18 of the STA-de�ned domains
