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Characterization of the Madison Formation, SW Wyoming: First
steps in creating a model for carbon sequestration
Geoffrey Thyne, Mark Tomasso, David Budd, Sharon Bywater-Reyes and Brian Reyes
Why do we need to put it anywhere?Carbon (Dioxide) Emissions
• Current increase comes from burning Fossil Fuels
• Increase in atmosphere is “linked” to climate changes
• There will be a Tax on carbon emissions
Carbon Capture and SequestrationTechnology Options for Stabilization
The Stabilisation Wedge
Emission trajectory to achieve 500ppm
Emission trajectory BAU
1 GtC Slices of the Stabilisation Wedge
Where will we need to put it?
North American CO2
Sources
Why do we need a model?
• Carbon sequestration models will be required for screening, scoping and permitting of storage facilities.
• The model requires a geologic framework including stratigraphic, structural and petrophysical data.
• The primary source for this data are petroleum wellsin the study area.
• Information comes from public sources (WYOGCC, UGSS, WYGS, scientific literature.
Madison Formation Lithostratigraphy
• Platform carbonate
• Early dolomitization
• six 3rd order sequences
• Paleozoic section contains CO2, CH4, H2S and He
Study Area
• Moxa Arch mile long north-south trending anticline
• Late Cretaceous uplift to create structure
• Extensive trap for hydrocarbons (mostly gas) in Mesozoic and Cenozoic sections
• Paleozoic section contains CO2, CH4, H2S and He
• Zone of interest is Mississippian Madison Formation
Madison Formation Lithostratigraphy
• Literature Review
• Facies controlled petrophysics with dolomite having better reservoir quality
• Most good reservoir quality confined to lower two sequences
Core information
• Detailed descriptions of the four cores.
• Recognize several facies (karst breccia, micrite, wackestone, packstone, grainstone).
• Samples for thin sections, XRD, whole rock chemistry and stable isotopes.
• Correlate with petrophysical data.
Core information
• Primarily dolomitic rock.
• Thin limestone layers near top of sequences.
• Fractures in limestones and dolomite with multiple orientations.
• Karstic only at top of Madison.
Primary petrophysical information
• There are 95 wells that penetrate the Madison Formation in the study area
• Most have geophysical logs• Four wells have core• Ten wells have standard
petrophysical data, 1 foot intervals (porosity, Kx, Ky and Kz, oil and water saturation, density and mineralogy)
• Two wells have both petrophysical data and core
Facies dependent por-perm• Core-based data show:
– Facies control on porosity and permeability
Petrophysical data from core
Well information
• Core-based data show:
– Porosity with normal distribution skewed toward lower end
– Permeability with lognormal distribution
• This is the primary data to populate model grid
Petrophysical data from cores
Well information
• Core-based data show:
– Porosity – log Permeability relationship for samples with higher porosity
– Porosity-permeability relationship is very poor with wide range of permeability for lower porosity samples
• Core descriptions and thin sections show fracture-controlled permeability in lower porosity rocks
Potential bias in the petrophysical data
• Petrophysical data comes form core.
• Represents small portion of total formation.
• Limited sampling of facies.
• Ten wells have petrophysical data, but from only two locations.
• One location is in gas cap, one is not.
Dolomite petrophysics by location
CO2 versus no CO2
Average porosity = 1.5
Average porosity in gas cap = 12.6
Average porosity outside gas cap = 7.33
Calcite petrophysics by location
CO2 versus no CO2
Average porosity in gas cap = 2.3
Average porosity outside gas cap = 7.2
Potential bias in the petrophysical data
• Petrophysical data comes form core.
• Represents small portion of total formation.
• Limited sampling of facies.
• Ten wells have petrophysical data, but from only two locations.
• One location is in gas cap, one is not.
Well with core-based petrophysical data have limited sampling of facies
Note positionof cores with petrophysical data
Extending the data
• Extend petrophysical database (n = 2,671) by calculating log-based porosity for nine wells (n = 11,959).
• Use sonic logs to reconstruct bulk density where necessary (Gardner et al. 1974), and bulk density logs to calculate porosity (Schlumberger 1972).
• Calibrate relationship by comparing log-based and measured posoity
• Used calculated values every 0.5 feet to generate porosity for wells with logs.
Core based porosity
Petrophysical data core versus log
Petrophysical data log-based shows no location bias
Modified log-based petrophysical basis
• Good reservoir intervals are in third and fourth sequences.
• Still facies controlled.
• High porosity zones extend over 10’s miles.
• Trimodal porosity distribution?
• Three classes in formation.
• <4%, Mean = 2%, 45% of all porosity values.
• 4 – 12%, Mean = 7.5%, 16.5% of all porosity values.
• >12%, Mean = 14%, 37.7% of all porosity values.
Permeability Isotrophy
Use core based
samples with Kh
and Kv
N = 985
<4%, n = 470,
mean log Kh/Kv =
0.88
4 – 12%, n = 362
mean log Kh/Kv =
0.77
>12%, n = 153,
Mean log Kh/Kv =
0.52
Conclusions
• Core based petrophysical data is available to characterize the Madison in the study area.
• Core-based petrophysical data is somewhat biased by location of cores.
• Not representative of target entire formation.
• Can extend the data using geophysical logs.
• Extended data shows different stratigraphic distribution of reservoir quality than previous work in eastern Wyoming.
• Petrophysical properties in model will have to be modified.
Questions