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Record W2064024308 · doi:10.2118/03-12-02

Numerical Evaluation of Geomechanical Parameters Affecting Productivity Index in Weak Rock Formations?Part 2: Field Application

2003· article· en· W2064024308 on OpenAlexafffund
Hans Vaziri, Y. Xiao

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2003
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of CanadaDalhousie University
KeywordsPermeability (electromagnetism)GeologyEffective stressGeotechnical engineeringPetroleum engineeringShearing (physics)Cohesion (chemistry)Stress fieldEngineering

Abstract

fetched live from OpenAlex

Abstract The numerical model proposed in Part 1 was first verified and then applied to a well-documented field case involving openhole cavity completion in a coalbed methane reservoir. Following calibration against the field observation, the numerical model was used to test the effect of strength, permeability, reservoir depth, and pressure gradient on cavitation and production. The sensitivity studies indicate that the potential for cavitation and production increases with reduction in strength properties, reduction in permeability, increase in depth, and increase in pressure gradient. Among them, the most influential parameter is the apparent cohesion. The smaller the cohesion, the larger the size of both cavitation and the adjoining plasticfailed zone. The latter is particularly important for boosting production because within the plastic zone, permeability increases due to shearing (dilation) and reduction in the mean effective stress. A corollary of the above is that in competent rocks, the response may be reversed since the creation of the cavity results in the development of a relatively tight plastic zone and a large zone outside the plastic zone within which permeability becomes depressed because of a net increase in the effective mean stress. In such formations, there would be a net reduction in permeability and hence productivity. Introduction In this study, we promote the benefits of maximizing sand production under controlled conditions. In many fields where the geological conditions (reservoir strength properties, stratigraphy, stress state) are favourable, creating massive sand production during the completion phase which can boost production by severalfold. In other fields where large amounts of sand production cannot be easily managed, mini sand bursts can be considered for removing the near wellbore plugging (skin damage); this typically improves productivity by about 30% and saves the cost of installing gravel packs and screens. While the benefits of sand production have been noted in a number of fields, such as the Gulf of Mexico and the North Sea(1, 6), the industry, in general, has been reluctant to consider it as routine operation for a number of reasons. For instance: insufficient data are available to make reliable predictions; the mechanisms are not well understood; concerns over the fact that sand production may result in total instability (ongoing sand production); traditional practices are hard to change; and, experience and field data gathered thus far are considered insufficient to demonstrate the significant cost effectiveness of sanding. The objective of the study presented here is to demonstrate the mode of sand production and its influence on the productivity index. In a companion paper, the theory used in the proposed numerical model is described. In this paper, the model is applied to a well-documented field case involving openhole cavity completion in a coalbed methane reservoir. The numerical findings are compared against the field data and the results and field implications are then discussed. As pointed out in the companion paper, however, the proposed numerical model cannot be applied to wormhole development in heavy oil sands where quite different sand production mechanisms are involved.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.987
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.225
Teacher spread0.216 · 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 designObservational
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

Citations3
Published2003
Admission routes2
Has abstractyes

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