A Single-Shot Method for Capillary Pressure Curve Measurement Using Centrifuge and Quantitative Magnetic Resonance Imaging
Bibliographic record
Abstract
Abstract The centrifuge method for capillary pressure curve measurement involves increasing the centrifuge speed in steps and measuring the liquid expelled from a short core plug, at equilibrium, for each step. However, the traditional methods for deducing approximate solutions for the capillary pressure curve are based on the assumption that the capillary pressure is zero at the outflow end of the core. In addition, the traditional centrifuge methods for capillary pressure measurement are time consuming. A full capillary pressure curve requires approximately 10 different rotational speeds. We have observed for most sedimentary rocks that the experimental magnetic resonance free induction decay is single exponential and the effective transverse relaxation time (T2*) is largely insensitive to fluid saturation. These features ensure that Centric Scan SPRITE (single-point ramped imaging with T1 enhancement) is a quantitative magnetic resonance imaging (MRI) method, since its local image intensity is directly proportional to the local fluid content. We propose a single-shot method to measure the capillary pressure curve of a long rock core using a single-speed centrifuge experiment and one-dimensional Centric Scan SPRITE MRI to determine the fluid saturation distribution, S(r), along the length of the core. A full capillary pressure curve can be directly determined by the relation of S(r) and the capillary pressure distribution, Pc(r), along the length of the core. The single-shot method, employing a desktop centrifuge and a desktop permanent magnet based one-dimensional MRI instrument, has been applied to measure the primary drainage, imbibition, and secondary drainage capillary pressure curves for reservoir rocks. The proposed method for determining the capillary pressure curve is rapid, cheap, and precise. The capillary pressure curve can be obtained straightforwardly with about 40 data points. The duration of the experiment is approximately 10 times less than the traditional method. Since only a single moderate rotational speed is employed, the outflow boundary condition can be maintained, and the effect of gravity can be neglected. In addition, the long rock cores employed for the single-shot method result in a relatively small radial effect.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".