Magnetic Core Analysis for Improved Interpretation of Geothermal Prospects
Bibliographic record
Abstract
Locating intervals where there may be radiogenic heat sources is critically important for potential geothermal prospects. This paper details use of core magnetic techniques on rock powder samples from northern Alberta to accurately determine: (i) the depth to the Precambrian crystalline basement rocks (where most of the radiogenic heat sources are expected to reside) below the Phanerozoic sedimentary cover rocks, and characterize variations in the different lithologies, (ii) the contents and domain states of certain minerals, and (iii) the temperature dependence of magnetic properties, which can potentially be used for mineral quantification from laboratory or potential borehole magnetic measurements. The results demonstrated that rapid core magnetic susceptibility measurements correlated with borehole gamma ray results, and could arguably identify certain lithologies (such as the granitic basement samples) better than the gamma ray. Whilst small rock powder samples were only available to us in this study, the same types of magnetic measurements can be made (using different sensors in some cases) on whole core, slabbed core, core plugs, drill cuttings or rock chips. The core measurements strongly suggest the potential usefulness of a high resolution borehole magnetic susceptibility tool for the above purposes. Interestingly, the magnetic susceptibility and gamma ray results with depth indicated that the Precambrian basement rocks were more complicated than initially expected, and exhibited a large range of values.Rapid, low field magnetic susceptibility measurements using a small portable sensor were first acquired, and subsequently validated independently via magnetic hysteresis measurements using a larger, sensitive and expensive variable field translation balance (VFTB). The results demonstrated that the portable, relatively cheap sensor is potentially suitable for basic, rapid measurements. However, the VFTB had several advantages. Firstly, it enabled magnetic hysteresis and susceptibility measurements to be acquired over a range of low to high applied fields. The high field signal enables estimates of the type and contents of the diamagnetic and paramagnetic minerals to be determined. Secondly, the low field signal due to the ferrimagnetic mineral components can be extracted from the high field signal. This gives useful information on the domain state of the ferrimagnetic (generally iron oxide) carriers. Interestingly, we observed a progressive change with increasing depth from multidomain (MD) or pseudo single domain (PSD, which are essentially small MD) to stable single domain (SSD) to superparamagnetic (SP) ferrimagnetic grains. This effectively represents a change from larger to smaller ferrimagnetic grain sizes with depth, and could be a potential tool for distinguishing lithologies in future similar studies. Thirdly, the temperature dependence of the hysteresis curves and magnetic susceptibility could be measured. This information can be used to improve predictions of the contents of the diamagnetic, paramagnetic and ferrimagnetic minerals from laboratory measurements, or from in-situ borehole magnetic susceptibility data (since temperature varies with depth in a borehole).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".