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Record W2310115732 · doi:10.2118/178362-ms

Displacement Calculation of Dynamic Killing Drilling In Deepwater

2015· article· en· W2310115732 on OpenAlexaff
Weiyan Ren, Heng Fan, Shaogui Deng, Cong Cui, Peng Qi, X.. Liu, Xiangji Dou

Bibliographic record

VenueSPE Nigeria Annual International Conference and Exhibition · 2015
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsMemorial University of Newfoundland
FundersNational Natural Science Foundation of China
KeywordsDisplacement (psychology)Drilling fluidDrillingStability (learning theory)MechanicsControl theory (sociology)Flow (mathematics)DrillDrill pipeBoundary value problemAccelerationGeologyMathematicsComputer scienceEngineeringPhysicsMathematical analysisMechanical engineeringClassical mechanics

Abstract

fetched live from OpenAlex

Abstract The dynamic kill process is divided into two stages: “dynamic pressure stability” and “static pressure stability” stage in this paper. In dynamic pressure stability stage, sea water fluid was pumped into the well the initial killing fluid; Then in “static pressure stability” stage, pump into the weight liquid by quantified displacement based on “dynamic pressure stability” that can achieve complete killing effect, and control well kick effectively to drill efficiency. In this paper, the multiphase multicomponent staged pressure control equation is established by considering the effect of shallow flow gas influx, meanwhile, it adopts the auxiliary equations such as velocity equation, density equation, and Herschel-Bulkley fluid rheological equation with yield value. The dynamical drilling tools flow pressure loss method is considered to improve the calculation accuracy of displacement. This paper solves the equation by the finite difference iterative method which should get the solution conditions firstly, then the initial and weight displacement are got. This paper takes a deepwater well as an example by comparing and analyzing calculation results and the actual data which shows that it has a greater degree anastomosis with the actual construction site. The following conclusions are obtained: (1) Calculation accuracy is more precise and practical when using the Herschel-Bulkley rheological model and considering the dynamical drilling tools pressure loss calculation (2) The emphasis of finite difference iterative method are grid division and the boundary conditions determination. (3) The prevention of shallow geological disaster is more effective and the process is more delicate by dividing the progress into two stages. With oil and gas area trend diverting from land to sea, from the superficial to deep, the drilling and mining condition is becoming more and more complex. The method proposed in this paper can not only solve the complex well kick in deepwater which can't be solved before, but also the multicomponent multiphase equation established make the control of shallow flow gas more subtly, and the calculation equations of high accuracy displacement built by stages make the kill process more systemic.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.085
Threshold uncertainty score0.413

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 head0.016
GPT teacher head0.250
Teacher spread0.234 · 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

Citations4
Published2015
Admission routes1
Has abstractyes

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