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Review of the Development Status and Technology of Tight Oil: Advances and Outlook

2023· article· en· W4386736429 on OpenAlexaboutno aff
S. Liu

Bibliographic record

VenueEnergy & Fuels · 2023
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsnot available
Fundersnot available
KeywordsTight oilPetroleum engineeringTight gasOil shaleUnconventional oilShale oilGeologyFossil fuelDirectional drillingOil reservesChinaDrillingPetroleumEngineeringHydraulic fracturingGeographyPaleontologyWaste managementMechanical engineering

Abstract

fetched live from OpenAlex

Tight sandstone and shale oil reservoirs are one of the most promising and realistic important oil exploration fields in the 21st century. The research on the development technology of tight sandstone and shale oil reservoirs has important theoretical and practical significance for the exploration and development of tight sandstone and shale oil reservoirs in China. First, this article introduces the distribution of tight oil in the world and calculates the recoverable reserves of tight oil technology worldwide. The review also introduces the current status of tight oil exploration and development in major countries such as the United States, Canada, and China, including the distribution of tight oil resources, the main parameters of tight oil basins, and tight oil production. Second, it analyzes the current development status of tight oil in the United States, summarizes the four main factors that led to the success of tight oil exploration and development in the United States, and points out the impact of the successful development of tight oil in the United States on the global oil supply and demand relationship. Third, in the review of the main development technologies for tight oil, the current status, application, and progress of the main development technologies for tight oil are summarized and analyzed, including horizontal well drilling, fracturing and transformation technology, microscale seismic diagnosis, gas injection, and other technologies. Finally, the development examples of tight oil such as the Bakun shale in the United States are analyzed, and the application effects and experiences of horizontal well volume fracturing in regions such as the United States are summarized.

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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.878
Threshold uncertainty score0.149

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.008
GPT teacher head0.220
Teacher spread0.213 · 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 designOther design
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

Citations60
Published2023
Admission routes1
Has abstractyes

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