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Record W2047999725 · doi:10.2118/90579-pa

Optimization of Horizontal Well-Completion Design With Cased/Perforated or Slotted Liner Completions

2007· article· en· W2047999725 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSPE Production & Operations · 2007
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsConocoPhillips (Canada)
FundersConocoPhillips
KeywordsCompletion (oil and gas wells)BoreholePermeability (electromagnetism)WellborePetroleum engineeringAnisotropyTurbulenceFlow (mathematics)GeologyEngineeringGeotechnical engineeringMechanics

Abstract

fetched live from OpenAlex

Summary A well completion is a critical interface between the productive formation and the wellbore. An effective completion must maintain the mechanical integrity of the borehole without creating any significant restrictions on the flow capacity of the well. In this paper, a process is outlined to design optimal completions for horizontal wells by applying comprehensive skin-factor models that include damage and turbulence effects for all common types of completions. Slotted or perforated liner, cased, perforated, or gravel-pack completions have been used in horizontal wells for borehole stability and sand-control purposes. However, these completions may have lower productivity (as characterized by a positive skin) relative to an equivalent openhole completion, because the convergent flow to perforations or slots increases fluid velocity in the near-well vicinity. In addition, any reduced permeability zones (formation damage caused by drilling, completion, or other processes) magnify the convergent flow effects and therefore may result in substantially increased skin factors. Compound effects of formation damage around the well completion, a crushed zone because of perforating, plugging of slots, and turbulent flow, as well as interactions among these effects, are included in the model. This paper illustrates how to use skin factor models to screen the available completion types for cased/perforated and slotted liner completions. This screening approach considers reservoir permeability, permeability anisotropy, fluid properties, formation damage effects, and rock mechanical characteristics as the key parameters. The types of completion that yield the most productive well performance for this matrix of properties are presented. A more detailed completion design is then illustrated by showing how the skin-factor models were used to redesign the slot configuration of liner completions for viscous oil reservoirs on the North Slope of Alaska. Application of the slotted or perforated liner models to the readily available liners showed that the completion skin factor can vary by as much as 40%, depending on the detailed characteristics of the slots or perforations in the liner (slot or perforation size, density, and distribution). The example showed that optimizing the performance of the completion can increase well productivity at little or no cost and with no loss in liner mechanical strength.

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.

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: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.759
Threshold uncertainty score0.669

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.019
GPT teacher head0.236
Teacher spread0.217 · 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