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.. --------------------------------- ..
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Schenkel and Morrison Casing Model
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==================================
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EM: Schenkel and Morrison Casing Model
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======================================
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we create and run a FDEM forward simulation to calculate the vertical
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ent inside a steel-cased. The model is based on the Schenkel and
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ison Casing Model, and the results are used in a 2016 SEG abstract by
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et al.
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Here we create and run a FDEM forward simulation to calculate the vertical
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current inside a steel-cased. The model is based on the Schenkel and
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Morrison Casing Model, and the results are used in a 2016 SEG abstract by
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Yang et al.
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henkel, C.J., and H.F. Morrison, 1990, Effects of well casing on potential field measurements using downhole current sources: Geophysical prospecting, 38, 663-686.
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- Schenkel, C.J., and H.F. Morrison, 1990, Effects of well casing on potential field measurements using downhole current sources: Geophysical prospecting, 38, 663-686.
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model consists of:
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r: Conductivity 1e-8 S/m, above z = 0
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ckground: conductivity 1e-2 S/m, below z = 0
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sing: conductivity 1e6 S/m
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- 300m long
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- radius of 0.1m
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- thickness of 6e-3m
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The model consists of:
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- Air: Conductivity 1e-8 S/m, above z = 0
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- Background: conductivity 1e-2 S/m, below z = 0
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- Casing: conductivity 1e6 S/m
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- 300m long
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- radius of 0.1m
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- thickness of 6e-3m
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de the casing, we take the same conductivity as the background.
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Inside the casing, we take the same conductivity as the background.
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re using an EM code to simulate DC, so we use frequency low enough
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the skin depth inside the casing is longer than the casing length (f
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-6 Hz). The plot produced is of the current inside the casing.
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We are using an EM code to simulate DC, so we use frequency low enough
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that the skin depth inside the casing is longer than the casing length (f
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= 1e-6 Hz). The plot produced is of the current inside the casing.
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e results are shown in the SEG abstract by Yang et al., 2016: 3D DC
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stivity modeling of steel casing for reservoir monitoring using
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valent resistor network. The solver used to produce these results and
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eve the CPU time of ~30s is Mumps, which was installed using pymatsolver_
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These results are shown in the SEG abstract by Yang et al., 2016: 3D DC
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resistivity modeling of steel casing for reservoir monitoring using
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equivalent resistor network. The solver used to produce these results and
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achieve the CPU time of ~30s is Mumps, which was installed using pymatsolver_
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pymatsolver: https://github.com/rowanc1/pymatsolver
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.. _pymatsolver: https://github.com/rowanc1/pymatsolver
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example is on figshare: https://dx.doi.org/10.6084/m9.figshare.3126961.v1
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This example is on figshare: https://dx.doi.org/10.6084/m9.figshare.3126961.v1
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ou would use this example for a code comparison, or build upon it, a
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tion would be much appreciated!
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If you would use this example for a code comparison, or build upon it, a
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citation would be much appreciated!
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