Thermomagnetic Analyses of the Permeability-Controlling Minerals in Red and White Sandstones in Deep Tight Gas Reservoirs: Implications for Downhole Measurements
Bibliographic record
Abstract
Summary Our recent work on deep tight gas reservoirs containing red and white sandstones (Potter et al. 2009) has suggested that the presence of small amounts of hematite in reservoir samples can have a dramatic effect on permeability. Such conclusions were made using laboratory-based low- and high-field magnetic-susceptibility measurements on reservoir-rock samples and by comparing these measurements with the permeability data. These rapid, nondestructive magnetic measurements have been applied previously in clastic reservoir samples (Potter 2007; (Ivakhnenko 2006; Ivakhnenko and Potter 2008; Potter and Ivakhnenko 2008) and carbonate reservoir samples (Al-Ghamdi 2006; Potter et al. 2011). However, such laboratory-based analyses are not representative of the downhole in-situ conditions, especially in deep gas reservoirs where the temperature can reach quite high values. Typical tight-gas-reservoir depths can reach approximately 4000 m (Abu-Shanab et al. 2005) and 6000 m (Tang et al. 2008), and the equivalent temperatures would measure 131 and 192°C, respectively, if one assumes the normal geothermal gradient (Mayer-Gurr 1976). This paper investigates the in-situ magnetic properties of deep tight gas reservoir samples (containing permeability-controlling reservoir minerals hematite and illite) by means of laboratory experiments to model downhole temperature conditions. We perform magnetic hysteresis measurements at various temperatures in order to identify and quantify mineralogy and model changes in the magnetic behavior of these minerals at in-situ downhole conditions. From these measurements, we are able to show whether the mineralogy or domain state of the permeability-controlling minerals is likely to change with temperature in deep gas reservoirs. These changes can potentially have a major effect on permeability. We also demonstrate that there are strong correlations between core-permeability and magnetic-susceptibility data in these tight-gas-reservoir samples. The permeability is low in red sections of the core wherever there is hematite.
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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 | 0.002 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".