Applied techniques for residual oil recovery from source rocks: A review of current challenges and possible developments
Bibliographic record
Abstract
Abstract Depleted fossil fuel resources have led to an investigation of other promising alternatives such as renewable and unconventional energy sources. Shale formations have limited permeability. Therefore, several extraction techniques have been applied to improve residual oil recovery and production. In this work, the techniques applied above ground to extract the organic fractions from oil/gas shale are discussed. Studies related to compositional fractionation, ultrasonic‐assisted, microwave‐assisted, supercritical fluids, and surface retorting techniques have been conducted systematically in approximately 150 scholarly articles over the past 10 years. The impacts of each technique as well as the drawbacks and challenges are highlighted in this paper. The fractionation techniques are sufficient in general; however, they are time consuming as they include several stages and use a considerable amount of solvents. Ultrasonic and microwave techniques are highly reliant on formation transparency linked to the organic fraction heterogeneous distribution. The surface retorting method, which is highly efficient with up to 90% recovery, for example, the Galoter and Paraho methods, is still dependent on shale particulate size, generates a massive amount of spent shale as waste, and is prominently emissive. Therefore, assessments that can be used to overcome existing drawbacks are considered. This can provide practical insight about these techniques to overcome limitations and concerns in terms of efficiency, cost, environmental issues, and reliability features. The work highlights the dominant extraction techniques for further development.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".