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Record W2028726697 · doi:10.2118/68835-ms

Enhanced Production in Horizontal Wells by the Cavity Failure Well Completion

2001· article· en· W2028726697 on OpenAlexaffabout
Yarlong Wang, B. Tremblay

Bibliographic record

VenueSPE Western Regional Meeting · 2001
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsPetro Geotech (Canada)
Fundersnot available
KeywordsPetroleum engineeringCompletion (oil and gas wells)GeomechanicsOil wellOil productionPermeability (electromagnetism)GeologyOil fieldPorosityEnvironmental scienceGeotechnical engineering

Abstract

fetched live from OpenAlex

Abstract High viscosity and weak cementation existing in heavy oil reservoirs present great challenge to us in rich heavy oil reservoirs in Northwestern Canada for production and well completion. On one hand, we attempt to increase the exposure of the reservoir to the well so that we can maximize the production potential. On the other, we must select an adequate strategy for well completion in order to maintain the integrity of the well during production. A well completion strategy by cavity-failure mechanism has been used for coalbed methane and heavy oil production during SAGD. The success of their previous operations leads us to investigate the feasibility of such a well completion strategy in both cold production and other enhanced production process in poorly consolidated heavy oil reservoirs. A coupled reservoir-geomechanics model is developed. A black-oil model is fully coupled to a Mohr-Coulomb type elastoplastic geomechanics model. An open hole condition with slotted liner is simulated. The wellbore pressure is rapidly reduced to create a massive dilation zone near the well so that the intact porosity can be mobilized. Consequently, an enhanced zone near the slotted liner with a higher permeability can be generated, leading to negative skin factor during the production. The field conditions reported in Cold Lake are used to evaluate our study and simulations.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.765
Threshold uncertainty score0.499

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 studies0.0000.000
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 head0.010
GPT teacher head0.217
Teacher spread0.207 · 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.

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

Citations5
Published2001
Admission routes2
Has abstractyes

Explore more

Same venueSPE Western Regional MeetingSame topicHydraulic Fracturing and Reservoir AnalysisFrench-language works237,207