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Record W2610888945 · doi:10.2118/157935-pa

Estimation of CHOPS Wormhole Coverage From Rate/Time Flow Behaviors

2017· article· en· W2610888945 on OpenAlexaff
Lei Xiao, Gang Zhao

Bibliographic record

VenueSPE Reservoir Evaluation & Engineering · 2017
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of ReginaHusky Energy (Canada)
FundersMassachusetts General Hospital
KeywordsWormholeDimensionless quantityMechanicsFlow (mathematics)Work (physics)Computer scienceGeologyEngineeringPhysicsClassical mechanicsMechanical engineering

Abstract

fetched live from OpenAlex

Summary In wormholed reservoirs with cold-heavy-oil-production-with-sand (CHOPS) wells, regions covered by wormhole networks are estimated by analyzing rate/time flow behaviors along with pressure and sand-production data. In this work, the concept of effective wormhole coverage is proposed as a proxy of the drainage region of CHOPS wells with complex wormhole networks. The wormhole intensity is defined as the total length of wormholes per unit effective wormhole coverage. A CHOPS flow model is developed by use of the boundary-element method (BEM) to account for various boundary conditions, wormhole morphologies, and effects of wormhole dynamic growth. Transient pressure and rate responses calculated by the model are validated by comparing with analytical solutions and numerical simulations. Modeling results show that the effective wormhole coverage and wormhole intensity within the region dominantly affect the characteristics of pressure and rate/time behaviors, regardless of the detailed wormhole morphologies. Accordingly, dimensionless pressure and rate type curves are developed to match flow behaviors, such as wormhole linear- and transitional-flow regimes to estimate effective wormhole coverage of CHOPS wells with available field data. This work extends the literature with fast type-curve matching of pressure and rate/time behaviors instead of generally practiced numerical-simulation routines. A field case with rate and sand-production data is successfully analyzed to show great potential of applying the proposed approach to characterize CHOPS wormholes.

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)0.001
metaresearch head score (Gemma)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.014
GPT teacher head0.266
Teacher spread0.251 · 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.

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

Citations10
Published2017
Admission routes1
Has abstractyes

Explore more

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