Prediction of Nuclear Magnetic Resonance Surface Relaxivity for Shales
Jiuhui Cheng, Shuitao Zhang, Xiaolong Song · 2026
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Description
Jiuhui Cheng, Shuitao Zhang, and Xiaolong Song worked in 2026 on predicting a key magnetic resonance parameter for shale rock without direct calibration. Nuclear magnetic resonance readings reveal pore sizes in rock, but converting them needs surface relaxivity, a value tied to how pore walls affect the signal. Their study regressed that value from mineral and chemical measurements.
Mineralogy predicted the parameter with very small error, and chemical element data did almost as well. Iron and titanium stood out among the elements shaping the value. The magnetic character of the rock, captured well by its clay minerals and their magnesium, explained much of the link. Susceptibility, a measure of how strongly rock responds to a magnet, rose in step with surface relaxivity. The authors say such shortcuts can speed and simplify routine shale testing.
Catalog record
| CREATOR | Jiuhui Cheng, Shuitao Zhang, Xiaolong Song |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 19 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |