The U-tube sampling methodology and real-time analysis of geofluids
Bibliographic record
Abstract
The U-tube geochemical sampling methodology, an extension of the porous cup technique proposed by Wood [1973], provides minimally contaminated aliquots of multiphase fluids from deep reservoirs and allows for accurate determination of dissolved gas composition.The initial deployment of the U-tube during the Frio Brine Pilot CO 2 storage experiment, Liberty County, Texas, obtained representative samples of brine and supercritical CO 2 from a depth of 1.5 km.A quadrupole mass spectrometer provided real-time analysis of dissolved gas composition.Since the initial demonstration, the U-tube has been deployed for (1) sampling of fluids down gradient of the proposed Yucca Mountain High-Level Waste Repository, Armagosa Valley, Nevada (2) acquiring fluid samples beneath permafrost in Nunuvut Territory, Canada, and (3) at a CO 2 storage demonstration project within a depleted gas reservoir, Otway Basin, Victoria, Australia.The addition of in-line high-pressure pH and EC sensors allows for continuous monitoring of fluid during sample collection.Difficulties have arisen during U-tube sampling, such as blockage of sample lines from naturally occurring waxes or from freezing conditions; however, workarounds such as solvent flushing or heating have been used to address these problems.The U-tube methodology has proven to be robust, and with careful consideration of the constraints and limitations, can provide high quality geochemical samples.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".