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Record W2792018636 · doi:10.2118/189805-ms

Dual-Permeability Matrix–Fracture Corefloods for Studying Gas Flooding in Tight Oil Reservoirs

2018· article· en· W2792018636 on OpenAlexaff
Peng Luo, Kelvin D. Knorr, Sheng Li, Petro Nakutnyy

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of CalgarySaskatchewan Research Council (Canada)
Fundersnot available
KeywordsPermeability (electromagnetism)Tight gasPetroleum engineeringTight oilGeologyWater floodingPorosityPorous mediumOil in placeRelative permeabilityOil fieldMatrix (chemical analysis)Enhanced oil recoveryGeotechnical engineeringMaterials scienceChemistryComposite materialPetroleumHydraulic fracturing

Abstract

fetched live from OpenAlex

Abstract Laboratory evaluation of tight oil production processes requires a unique coreflood apparatus that portrays both the tight rock matrix and fractures—a dual-permeability system. However, with some tight formations such as the Bakken having no available outcrop, full-sized actual cores are very difficult and sometimes impossible to obtain. In this study, a large-volume coreflood apparatus was developed to incorporate the detailed physics of ultra-tight, dual-porosity, dual-permeability flow in porous media. Also, large synthetic cores were made to represent the permeability, porosity, and mineralogy of actual tight reservoir rocks. To generate the desired dual-permeability system, fractures are simulated by creating sand-filled branched pathways in the large synthetic core. During a coreflood test, fluids are injected through the peripheral high-permeability belt into the tight matrix and recovered through the central fracture. This simulates the flow of matrix to fracture, or vice versa, seen in an ultra-tight reservoir. As well, either continuous gas/water injection or cyclic gas injection modes can be tested with the model. Two large-volume dual-permeability corefloods were conducted to study the effectiveness of immiscible field-produced gas flooding using recombined reservoir oil and synthetic tight cores. The corefloods simulated a practical field production sequence that included primary recovery (pressure depletion), injection of field-produced gas, pressurizing and soaking with this gas, and pressure depletion. The higher-recovery run produced 28.3% original oil in place (OOIP) including primary and tertiary (enhanced) processes. The dual-permeability corefloods demonstrated more representative performance of actual field operations than do traditional one-dimensional corefloods. The new matrix–fracture coreflood system better reflects the extreme permeability contrast between matrix and fractures that characterizes tight oil reservoirs. Therefore, history matching of its results using a numerical simulator is expected to provide much better representation in scaling up and predicting realistic field operations.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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 head0.018
GPT teacher head0.274
Teacher spread0.256 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2018
Admission routes1
Has abstractyes

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