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Record W2014353981 · doi:10.2118/0407-0082-jpt

Overview: Heavy Oil (April 2007)

2007· article· en· W2014353981 on OpenAlexaboutno aff
Tony Kovscek

Bibliographic record

VenueJournal of Petroleum Technology · 2007
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsnot available
Fundersnot available
KeywordsOil reservesPetroleum engineeringSubmarine pipelineResource (disambiguation)PetroleumProcess (computing)Enhanced oil recoveryEnvironmental scienceChinaFossil fuelGeologyEngineeringWaste managementComputer scienceOceanographyGeographyPaleontology

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.862
Threshold uncertainty score0.526

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.277
Teacher spread0.263 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2007
Admission routes1
Has abstractyes

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