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Record W2586346236 · doi:10.2118/185021-ms

Waterflooding a Multi-layered Tight Oil Reservoir Developed with Hydraulically Fractured Horizontal Wells

2017· article· en· W2586346236 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSPE Unconventional Resources Conference · 2017
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsRed River College
Fundersnot available
KeywordsPetroleum engineeringPetrophysicsTight oilGeologyOil shalePermeability (electromagnetism)Tight gasReservoir simulationReservoir engineeringOil in placePetroleum reservoirMaterial balanceGeotechnical engineeringHydraulic fracturingPetroleumPorosityEngineering

Abstract

fetched live from OpenAlex

Abstract A successful waterflood can be implemented in a multi-layered tight oil reservoir developed with horizontal multi-fractured wells. This paper forecasts the recovery factor that can be achieved in such a reservoir as well as discusses the challenges of analyzing and modelling tight oil reservoirs developed with multi-fractured horizontal wells. With some unconventional reservoirs that are hydraulically fractured, a phenomenon exists whereby material balance and simulation indicate pressure support from a water source that is not always obvious. This phenomenon is believed to be related to the multi-layered silts/shales in the reservoir and is not typically seen in simulation of conventional higher permeability reservoirs (Kair >10 mD). Although, the exact petrophysical nature of the silts/shale reservoir layers in this project are not well defined at this time, a successful production history match can be achived by incorporating their input into a simulation model.

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.

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 categoriesMeta-epidemiology (narrow)
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 score0.426
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.027
GPT teacher head0.246
Teacher spread0.219 · 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