Core versus cuttings samples for geochemical and petrophysical analysis of unconventional reservoir rocks
Bibliographic record
Abstract
Core samples from petroleum wells are costly to obtain, hence drill cuttings are commonly used as an alternative source of rock measurements for reservoir, basin modelling, and sedimentology studies. However, serious issues such as contamination from drilling mud, geological representativeness, and physical alteration can cast uncertainty on the results of studies based on cuttings samples. This paper provides a unique comparative study of core and cuttings samples obtained from both vertical and horizontal sections of a petroleum well drilled in the Canadian Montney tight gas siltstone reservoir to investigate the suitability of cuttings for a wide range of geochemical and petrophysical analyses. The results show that, on average, the bulk quantity of kerogen or solid bitumen measured in cuttings is comparable to that of the core samples. However, total organic carbon (TOC) measurements are influenced by oil-based drilling mud (OBM) contamination. Solvent-cleaning of cuttings has been shown to effectively remove OBM contamination in light, medium, and heavy range hydrocarbons and to produce similar kerogen/solid bitumen measurements to that of core samples. Similarly, pyrolysis methods provide an alternative to the solvent-cleaning procedure for analysis of kerogen/solid bitumen in as-received cuttings. Microscopic study substantiates the presence of significant contamination by OBM and caved organic and inorganic matter in the cuttings, which potentially influence the bulk geochemistry of the samples. Furthermore, minerals in the cuttings display induced micro-fractures due to physical impacts of the drilling process. These drilling-induced micro-fractures affect petrophysical properties by artificially enhancing the measured porosity and permeability.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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".