MétaCan
Menu
Back to cohort
Record W4220721335 · doi:10.2118/208923-ms

Mitigating Surge and Swab by Changing Tripping from a Batch to a Continuous Process

2022· article· en· W4220721335 on OpenAlexaff
Rick Pilgrim, Stephen Butt

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsTrippingCasingProcess (computing)EngineeringUnderbalanced drillingDrill pipeDowntimeCrewDrillComputer scienceMechanical engineeringDrillingReliability engineeringDrilling fluidAeronautics

Abstract

fetched live from OpenAlex

ABSTRACT A significant portion of the time required to drill an oilwell is spent moving the drillpipe in or out of the wellbore, called "Tripping". The drill crew must trip pipe for numerous reasons. These include changing the bit as it wears out, inserting new casing strings, cleaning and treating the drillpipe and/or wellbore to allow more efficient drilling, and to run in various tools that perform specific jobs required at certain times in the oilwell construction plan. The traditional tripping process (TTP) inherently creates pressure transients developed from stopping and starting the vertical motion of the drillpipe during connections. These pressure transients called, "Swapping" and "Surging", contribute to borehole instability, restrict tripping speed, and increase non-productive time (NPT). This paper focuses on the benefits that can be gained from a bottom hole pressure (BHP) surge/swab perspective. Specifically, how these undesirable pressure transients can be dramatically reduced by modifying the TTP from a start/stop (batch) process to a continuous tripping process (CTP), where drillpipe tripping speed is kept constant throughout the entire tripping sequence and thereby significantly reducing the numerous starts and stops associated with traditional tripping. In this paper both the TTP and CTP systems were kinematically modeled using a custom simulator coded in C#. It is important to note that all the equipment used in the modified CTP exists and has only been reconfigured to facilitate a continuous process. This is inclusive of real-life limits for such items as derrick height, traveling block (TB) height as well as velocity, acceleration and inertia limits for TB, crown blocks, drawworks, their associated reeving configurations as well as racking system arms, grippers, and latches. The simulation results indicates that for a continuous tripping system we can achieve a ~73% slower average pipe speed that has an overall tripping speed approximately 4 times faster than traditional tripping. CTP decreased BHP deviation significantly. The continuous tripping process was awarded a patent by USTPO in 2016, US 9,441.247 B2.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.003
GPT teacher head0.174
Teacher spread0.171 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2022
Admission routes1
Has abstractyes

Explore more

Same topicDrilling and Well EngineeringFrench-language works237,207