Thermomagnetic Analyses of the Permeability Controlling Minerals in Red and White Sandstones in Deep Tight Gas Reservoirs: Implications for Downhole Measurements
Bibliographic record
Abstract
Abstract Our recent work on deep tight gas reservoirs containing red and white sandstones (Potter et al., 2009) has shown that the presence of small amounts of hematite in reservoir samples has 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, non-destructive magnetic measurements have previously been applied in clastic reservoir samples (Potter, 2005, 2007; Ivakhnenko, 2006; Ivakhnenko and Potter, 2006, 2008; Potter and Ivakhnenko 2007, 2008) and carbonate reservoir samples (AlGhamdi, 2006; Potter et al 2008). However, such laboratory based analyses are not representative of the downhole in-situ conditions, especially in deep gas reservoirs where temperature can reach quite high values. Typical tight gas reservoir depths can reach to about 4000m (Abu-Shanab et al 2005) and 6000m (Jianming et al 2008) and the equivalent temperatures would measure 131 °C and 192 °C respectively (Mayer-Gurr, 1976). This paper investigates the in-situ magnetic properties of permeability controlling reservoir minerals (hematite and illite in this case) via laboratory experiments to model downhole conditions. We perform magnetic hysteresis measurements at various temperatures in order to 1) quantify mineralogy and 2) to show changes in the magnetic behaviour of these minerals at in-situ downhole conditions. From these measurements, we are able to show whether the mineralogy and/or domain state of these permeability controlling minerals is likely to change with temperature in the deep gas reservoirs. This can have a major impact on permeability. We also show some results from another red and white tight gas reservoir where there is a strong correlation between core permeability and magnetic susceptibility data. In this particular reservoir, the presence of siderite in the white sections of the core greatly improves permeability. Once again for this reservoir, the permeability is low in red sections of the core due to the presence of hematite.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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 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".