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Record W2260968572 · doi:10.2118/175919-ms

Laboratory Investigation of Shale Permeability

2015· article· en· W2260968572 on OpenAlexafffund
Al Moghadam, Rick Chalaturnyk

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsUniversity of Alberta
FundersCMG Reservoir Simulation Foundation
KeywordsPermeability (electromagnetism)Oil shalePore water pressureGeologyGeotechnical engineeringChemistry

Abstract

fetched live from OpenAlex

Abstract Matrix permeability of shales is an elusive but important parameter in characterizing shale gas reservoirs. Permeability is typically measured using steady-state flow tests or the more timely transient methods such as pulse-decay. Due to the low permeability nature of shale rocks, slip flow regime is observed to be dominant in pore scale. As a result, permeability changes with pore pressure. Traditionally, permeability is measured at various mean pore pressures and the data is used to extract the Klinkenberg or absolute permeability. However, it has been shown recently that Klinkenberg permeability significantly overestimates the absolute (liquid) permeability of shale rocks. Additionally, several studies have shown different methods of permeability measurement can lead to significantly different results at similar pressures. In this work, steady-state laboratory gas flow experiments have been conducted on four shale samples using methane and nitrogen as flowing fluid. At each stage, mean pressure and mean effective stress is held constant and permeability is measured at various gas flow rates. Mean pressure is then raised and the tests are repeated at the next stage. The tests are designed to study the influence of mean pressure as well as flow rate on gas permeability. Subsequently, the samples are sheared in a triaxial cell and similar permeability tests are repeated to compare the permeability behavior before and after shearing. Finally, the samples are saturated with water to measure water permeability in order to analyze the gas permeability observations using theory. The results indicate strong rate sensitivity in shale permeability measurements. Measured shale permeability is observed to rise as flow rate increases and reaches a constant value at higher rates. Permeability of sheared samples shows a similar trend although with higher permeability values. This phenomenon casts a shadow of doubt around the common non-steady-state permeability measurement methods and has never been discussed previously with respect to shale gas reservoirs. The basic definition of gas permeability needs to be revisited in order to set up new standards (concerning testing pressure, rate, and stress state) in order to obtain meaningful and comparable permeability measurements.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

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)0.0010.000

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 head0.025
GPT teacher head0.223
Teacher spread0.198 · 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 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

Citations23
Published2015
Admission routes2
Has abstractyes

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