PERMEABILITY PREDICTION USING NUCLEAR MAGNETIC RESONANCE
The accurate modelling of oil, gas, and water reservoirs depends fundamentally upon access to reliable rock permeabilities that cannot be obtained directly from downhole logs. Instead, a range of empirical models are employed and this paper will discuss several models derived from the Nuclear Mag...
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| Main Author: | |
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| Format: | Final Year Project |
| Language: | English |
| Published: |
UNIVERSITI TEKNOLOGI PETRONAS
2012
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| Online Access: | http://utpedia.utp.edu.my/3446/1/_Dissertation_report_benjamin.pdf http://utpedia.utp.edu.my/3446/ |
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| Summary: | The accurate modelling of oil, gas, and water reservoirs depends fundamentally upon
access to reliable rock permeabilities that cannot be obtained directly from downhole
logs. Instead, a range of empirical models are employed and this paper will discuss
several models derived from the Nuclear Magnetic Resonance data.
Nuclear Magnetic Resonance (NMR) measurements were initially made for high
magnetic fields, emphasizing time for protons to relax in the longitude manner, T1,
for pore-size evaluation. However, modern NMR logging tools use time for the
protons to relax transversely, T2, measurements to make it possible and feasible for
low field strengths and these measurements should be supported by core analysis.
This project will illustrate the differences in using the two different models which are
the COATES MODEL and MEAN TRANSVERSE RELAXATION TIME MODEL
(MEAN T2 MODEL, also known as, SDR model) to measure and predict the
permeability of samples. The result is then compared to see which permeability
prediction model is most accurate.
The permeability is shown to be closely related to porosity, pore size, pore fluid
properties and mineralogy. The NMR estimates permeability based on theoretical
models that show that permeability increases with both increase in porosity and pore
size. |
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