Applications of petroleum geochemistry in reservoirs
Bibliographic record
Abstract
This thesis is structured in two main parts-theoretical and practical part. The theoretical part will be mainly focused on the detailed description of the application of geochemistry in oil production and exploration, through explaining the role of geochemistry in the hydrocarbon asset management, in identifying new exploration or missed pay zones, in delineating reservoir compartmentalization by explaining the fingerprinting approach in assessing the reservoir continuity, etc. Additionally, it will be presented how the geochemistry aids in maximizing the waterflood efficiency, as well as its importance in the prediction of the flow assurance problems. In this part, the application of the reservoir geochemistry will be also discussed together with the application of the geochemistry studies in the maturity assessment, oil-oil, oil-source rock correlation. Furthermore, related to the application of the light hydrocarbons, which is the main focus in the practical part, will be discussed the postgenerative alteration processes and its characterization through the application of the light hydrocarbons. In the practical part, a set of light hydrocarbon ratios will be applied on 146 sample set of oils from Western Canada. Using the compositional data of these oil samples, the compositional changes in the samples caused by the postgenerative processes will be detaily observed.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 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".