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Record W2013425440 · doi:10.2118/168982-ms

Immediate Gas Production from Shale Gas Wells: A Two-Phase Flowback Model

2014· article· en· W2013425440 on OpenAlexaff
O. A. Adefidipe, Hassan Dehghanpour, Claudio Virués

Bibliographic record

VenueSPE Unconventional Resources Conference · 2014
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsNexen (Canada)University of Alberta
Fundersnot available
KeywordsPetroleum engineeringShale gasTight gasOil shaleHydraulic fracturingFracture (geology)Natural gasGeologyPermeability (electromagnetism)CompressibilityReservoir simulationReservoir engineeringRelative permeabilityMechanicsGeotechnical engineeringChemistryPetroleumPorosityEngineeringWaste management

Abstract

fetched live from OpenAlex

Abstract Although existing models for analysing single-phase flowback water production at the onset of flowback in tight oil and gas reservoirs provide estimates of fracture volume, they are not applicable to shale gas reservoirs. This is because flowback data from shale gas wells do not show this single phase region. Instead, they show a surprising trend of immediate gas breakthrough. This paper attempts to (1) understand the fundamental reasons for this early gas breakthrough, (2) develop a representative mathematical model that describes this behaviour and (3) estimate the effective fracture volume and equivalent fracture half-length by history matching the early-time two-phase flowback data. From the diagnostic plots generated from of rate/pressure data of 8 multi-fractured horizontal wells completed in the Muskwa Formation, the gas-water ratio (GWR) plots indicate the presence of initial free gas in the complex fracture network. This conclusion is backed by the imbibition experiments conducted on shale samples collected from the same formation showing the presence of gas-saturated natural fractures. The linear diffusivity equation is solved for early-time two-phase gas/water flow in the hydraulic fractures. The primary drive mechanism at the onset of flowback is initial free gas expansion within the fracture network. Secondary drive mechanisms considered include fracture water expansion and fracture closure. The driving forces are modeled by an effective compressibility term analogous to the total compressibility in conventional multiphase flow formulations. Also, two-phase water/gas flow is handled by an explicitly determined relative permeability function of time. Eventually a new pseudo-time function is defined to account for the changes in gas properties and relative permeability with time. Rate normalized pseudo-pressure versus pseudo-time plots give a straight line when applied to field data, thus the solution can be used to characterize hydraulic fractures in a manner similar to conventional well testing methods.

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)0.001
metaresearch head score (Gemma)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.241
Teacher spread0.226 · 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

Citations54
Published2014
Admission routes1
Has abstractyes

Explore more

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