Bibliographic record
Abstract
The quest to produce heavy oil (gravity less than 20°API) has gone global. In the past, papers describing heavy-oil recovery generally focused on resources in the Americas and some in China and Indonesia. In the papers evaluated for this issue's heavy-oil feature, the focus ranged from the North Sea to the Middle East to the Gulf of Mexico and places in between. In many cases, the resource does not resemble the conditions that are thought to be typical for heavy oil: viscous oil held in relatively permeable, shallow sands. The fields of interest nowadays have evolved to include fractured carbonates; offshore settings; and deeper, more geologically heterogeneous heavy-oil resources. Such new settings introduce new challenges, which include highly permeable pathways and limits on reservoir access, in addition to those of large oil-phase viscosity and low reservoir energy. Despite these apparent successes, it appears that heavy-oil-recovery techniques have bifurcated. On the one hand, thermal processes deliver significant recovery factors, but are capital-intensive and sometimes difficult to implement as well as optimize. On the other hand, some new developments appear to accept relatively low recovery factors and borderline economics. Given the heavy-oil volumes in place, the range of reservoir settings, and the challenges of effective extraction, it is time to renew our efforts in R&D. Production mechanisms of the heavy-oil solution-gas-drive process are not completely elucidated; performance cannot be simulated with conventional techniques; and, consequently, it is difficult to optimize primary recovery. Waterflooding of heavy oil is summarily dismissed because of adverse mobility ratios. In cold and/or offshore environments, waterflooding, and perhaps polymer-augmented waterflooding, may present the most attractive recovery option following primary recovery. Steam injection is relatively mature, but cost-effective mobility and profile control by use of aqueous-phase surfactants, gels, or advanced well completions remains an open question. In-situ combustion achieved by air injection is technically and economically feasible, especially for deeper, thinner, higher-pressured reservoirs. Combustion is difficult to describe and control. Nevertheless, it is attractive for in-situ upgrading and sulfur removal. In short, the heavy-oil resource is trillions of barrels, but the cumulative recovery totals to date are on the order of billions of barrels. Whether the potential and promise of heavy oil is realized depends on collective action of industry, academia, and governments to deliver recovery technologies appropriate for the wide range of reservoir and oil-phase conditions. Such technologies also need to be comparatively benign from an environmental aspect. Thus, the heavy-oil challenge remains significant. Heavy Oil additional reading available at the SPE eLibrary: www.spe.org SPE 102500 "Interpretation of Heat Distribution, Remaining-Oil Saturation, and Steamflood Potential of Block Wa38, Liaohe Field" by Y. Gao, RIPED, PetroChina Co. Ltd., et al. SPE 104046 "Thermal Simulation and Economic Evaluation of Heavy-Oil Projects" by E.R. Rangel-German, SPE, Natl. Autonomous U. of Mexico and Ministry of Energy, Mexico; et al. SPE 102876 "Making Sense of the Geomechanical Impact on the Heavy-Oil Extraction Process at Peace River Based on Quantitative Analysis and Modeling" by P.R. McGillivray, Shell Canada Ltd., et al. SPE 104405 "Efficient Technology Following Cyclic-Steam Stimulation for Thick, Massive Heavy-Oil Reservoirs" by S. Liu, RIPED, PetroChina Co. Ltd., et al.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.198 | 0.177 |
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".