MétaCan
Menu
Back to cohort
Record W2303670994 · doi:10.2118/179088-ms

Optimizing Bridge Plug Milling Efficiency Utilizing Weight-On-Bit to Control Debris Size: A Comparative Study of the Debris Size vs Weight-On-Bit Utilizing Five Bladed Carbide Mill, Tri-Cone and PDC Bits

2016· article· en· W2303670994 on OpenAlexafffund
John Yeung, T.F. Fraser, Kevin Thiessen, Oleg Medvedev

Bibliographic record

VenueSPE/ICoTA Coiled Tubing and Well Intervention Conference and Exhibition · 2016
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsShell (Canada)
FundersShell Canada
KeywordsDrillingSpark plugPlug-inRate of penetrationBit (key)Computer scienceEngineeringMechanical engineeringOperating system

Abstract

fetched live from OpenAlex

Abstract Weight-on-bit can be challenging to calculate at surface as downhole motor performance is generally observed from differential pressure and rate of penetration (ROP). If an accurate weight-on-bit (WOB) is maintained, motor performance and ROP can be maximized while controlling debris size. This will increase the efficiency of the entire millout operation. The weight-on-bit can be monitored and manipulated live via new software (Yeung, J. et al. 2015). The objective of this research paper is to conduct a comparative study that analyzes the performance of the five bladed carbide mill, tri-cone and PDC bits in terms of debris size vs weight-on-bit. Two main criteria will be used for the analysis. Firstly, a test will be carried out in order to determine how the set down force affects the drilling tool in terms of generating smaller debris size. This knowledge intends to improve wellbore clean outs and reduce the number of wiper trips. Secondly, the test will analyze how set down force of the drilling tool affects the ROP on the bridge plug. One specific type of 4-1/2″ bridge plug with a combination of selected mills and bits will be studied in this paper to control the experiment. However, the overall milling parameters may vary greatly depending on the manufacturers, plug, mill, and bit types. A series of bridge plugs will be milled out in a controlled environment using the five bladed carbide mill and tri-cone and PDC bits. Each bridge plug will be milled out using a different weight-on-bit. After the bridge plug is milled out, all the plug debris is collected, and sorted based on a debris size distribution graph. The ROP will also be measured during the milling process to determine milling efficiency. In summary, this paper will compare the performance executed by the five bladed carbide mill, tri-cone, and PDC bits. This paper will identify the optimal weight-on-bit to achieve the desired quantitative debris size with these plugs. More studies need to be conducted for different plug types to see how weight-on-bit affects debris size.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.465
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
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 head0.021
GPT teacher head0.242
Teacher spread0.222 · 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 designBench or experimental
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

Citations2
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueSPE/ICoTA Coiled Tubing and Well Intervention Conference and ExhibitionSame topicDrilling and Well EngineeringFrench-language works237,207