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Record W4221007823 · doi:10.3389/fenrg.2022.843518

Evaluation Model and Application of Shale Oil Production Efficiency Under Energy-Depleted Development Mode in Jimsar Sag

2022· article· en· W4221007823 on OpenAlexaff
Yang Gao, Dongming Zhi, Yingyan Li, Zhenxue Jiang, Yuan Deng, Jianhua Qin

Bibliographic record

VenueFrontiers in Energy Research · 2022
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsPetro-Canada
Fundersnot available
KeywordsOil shalePorosityPetroleum engineeringTight oilImbibitionShale oilShale oil extractionMaterials scienceEnvironmental scienceEffective porosityGeologyMineralogyComposite material

Abstract

fetched live from OpenAlex

In order to reveal the shale oil production mechanism and production efficiency under the energy-depleted development mode, experiments on expulsion oil based on imbibition and elastic energy release under high temperature and pressure were carried out, and nuclear magnetic resonance on-line monitoring was used to observe the production characteristics of shale oil. The experimental results show that the imbibition-expulsion oil mainly occurs in the small-size pore-throat system. Under the condition of high temperature and pressure, the oil-expulsion efficiency is generally less than 2% affected by pore pressure, which is significantly different from the conventional imbibition experiment results. Although elastic-energy expulsion oil occurs in different sizes of pore-throat systems, the oil-expulsion efficiency in large size pore-throat systems is more sensitive to temperature. Overall, the total elastic-energy oil-expulsion efficiency is significantly positively correlated with reservoir physical properties, production differential pressure and temperature, and negatively correlated with crude oil viscosity. Comprehensively considering various geological factors affecting oil-expulsion efficiency, the shale oil production efficiency evaluation model under the energy-depleted development mode is constructed, and the movable oil porosity of shale oil development section in the study area is evaluated. The results show that there is a good positive correlation between movable oil porosity and oil production intensity. The movable oil porosity of dry layer is generally lower than 0.5% and that of poor oil layer is between 0.5% and 1.5%. When the movable oil porosity is between 1.5 and 2.5%, it can be determined as the type II oil layer, and for more than 2.5%, it is the type I oil layer. The single-well evaluation results show that the shale oil “sweet spots” of the Lucaogou Formation in Jimsar Sag are mainly distributed in P 2 l 2 2−1 ∼ P 2 l 2 2−3 and P 2 l 1 2−1 ∼ P 2 l 1 2−3 , which is in good agreement with the current development status.

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)0.000
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.407
Threshold uncertainty score0.420

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.033
GPT teacher head0.293
Teacher spread0.259 · 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

Citations3
Published2022
Admission routes1
Has abstractyes

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