A Review on the Geologic Occurrence, Development and Associated Environmental Problems of Unconventional Hydrocarbon Energy Resources
Bibliographic record
Abstract
Unconventional hydrocarbon energy resources are non renewable energy resources whose major constituents are hydrogen and carbon. They have indistinct source rock- reservoir rocks-trap rocks characteristics/boundaries and unique exploitation technologies including mining and processing (surface and underground production using retorts for exploitation of oil shale and coking units for exploitation of bitumen; in-situ treatment and recovery (underground production using thermal treatment, chemical flooding and gas injection for exploitation of heavy oils in particular); and well production /underground production using vertical drilling, horizontal drilling and hydraulic fracturing. Only well production technology is applicable to conventional hydrocarbon energy resources, that is petroleum and natural gas exploitation. There are five classes of unconventional hydrocarbon energy resources including: coal bed methane (CBM), oil shale, shale gas/shale oil, heavy oil/bitumen, and natural gas hydrates. Worldwide, the recoverable methane from coal bed methane resources is about 2625 tcf. Similarly, the recoverable billions of barrels of oil from shale oil, heavy oil and bitumen, resources worldwide are 28626,443 and 651, respectively. Over 90% of these, that is, shale oil, heavy oil and bitumen are found in USA Venezuela and Canada respectively. The environmental problems associated with development of unconventional hydrocarbon energy resources include: surface/groundwater pollution; water depletion; air pollution and hazards of solid wastes from oil shale and bitumen mining/ processing. However, energy produced from unconventional hydrocarbon energy resources are similar to those produced from other (conventional) energy resources and can be equally used for various purposes including industrial, residential, transportation and commercial.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".