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Record W2033359647 · doi:10.2118/137779-pa

Evaluation of Recovery Technologies for the Grosmont Carbonate Reservoirs

2010· article· en· W2033359647 on OpenAlexfundaboutno aff
Qi Jiang, Jian-Yang Yuan, Jen Russel-Houston, Bruce Thornton, A. D. Squires

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2010
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsnot available
FundersUniversity of Calgary
KeywordsSteam-assisted gravity drainageCarbonateOil sandsPetroleum engineeringSteam injectionGeologyOil fieldEnhanced oil recoveryOverburdenPetroleum reservoirAsphaltMining engineeringChemistryArchaeology

Abstract

fetched live from OpenAlex

Summary The Upper Devonian Grosmont formation is a bitumen-saturated, carbonate unit located in Northern Alberta. It is considered to be among the world?s next largest unconventional oil resource plays. Since early 2006, there has been an increased interest in Grosmont resources exhibited by a range of companies, including super-majors. Several in-situ pilot tests were conducted in the central portion of this area in the 1970s and 1980s, using steam and in-situ combustion processes. Similar to field tests in the McMurray formation oil sands before invention of the Steam-Assisted Gravity Drainage (SAGD) process, none of the early recovery technologies tested proved to be economic. Because the "gravity" drainage process has proved successful in commercial development of the McMurray formation oil sands since the mid- to late-1990s, the recovery potential for the Grosmont formation should be re-evaluated, based on improved recovery techniques. Results from cyclic steam stimulation (CSS) field tests are compared and analyzed to understand the similarity and fundamental differences in reservoir properties between the McMurray formation oil sands and the Grosmont formation carbonate rocks. A preliminary interpretation is provided for laboratory test results for solvent processes applied to Grosmont carbonate cores. The scaling considerations from the laboratory results to field expectations are discussed. The paper also provides a direction for future studies and optimization opportunities for reservoir recovery leading to the commercial development of Grosmont carbonate reservoirs.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.662
Threshold uncertainty score0.876

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.013
GPT teacher head0.239
Teacher spread0.226 · 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 designBench or experimental
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

Citations36
Published2010
Admission routes2
Has abstractyes

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