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Record W1987409394 · doi:10.2118/2007-038

Numerical Modelling of Borehole Ballooning/Breathing-Effect of Fracture Roughness

2007· article· en· W1987409394 on OpenAlexaff
M. Ozdemirtas, Tayfun Babadagli, Ergün Kuru

Bibliographic record

VenueCanadian International Petroleum Conference · 2007
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBallooningBoreholeSurface roughnessMechanicsSurface finishBreathingFracture (geology)GeologyEnvironmental scienceGeotechnical engineeringMaterials sciencePhysicsComposite materialMedicineNuclear physics

Abstract

fetched live from OpenAlex

Abstract Borehole ballooning or breathing is commonly observed during drilling through fractured zones. It refers to small, partial and continuous mud losses and significant rapid mud gains due to annular pressure fluctuations resulting from mud circulation and non-circulation. Better understanding of the factors controlling borehole ballooning and/or breathing is needed for correct interpretation of the symptoms observed while drilling and to avoid mixing this phenomenon with lost circulation and well kicks. This paper introduces a two dimensional transient model of borehole ballooning and/or breathing. The model considers the effects of Newtonian fluid rheology, and fracture roughness on the fracture volume change as a function of transient wellbore pressure fluctuations inherent in typical drilling operations. Different types of fracture surface roughness that are commonly observed in sedimentary rocks and the degree of roughness identified by a wide variety of fractal dimensions were considered. The model was solved numerically to investigate the effects of fractures' natural geologic properties (fracture roughness, fracture dimensions, fracture surface deformation law) on the fluid loss and gain rate between the borehole and the fractured formation. Analyses on the importance of fracture roughness and non-linear deformation approximations were provided and situations where the degree of roughness becomes critical were identified. Introduction Mud losses/mud gains have been a major problem in the drilling industry and the identification and treatment of this problem is still a crucial issue due to the high cost of the drilling operations. Several practical solutions have been recommended to avoid drilling fluid losses and gains. However, regardless of the type of treatment, significant rig time can be lost and these solutions can make the control of other drilling parameters required for a precise well design even more complicated. Borehole ballooning or breathing is a recognized combined mud loss and mud gain phenomenon referring to the small, partial and continuous mud losses and significant rapid mud gains due to annular pressure fluctuations resulting from mud circulation and non-circulation. If the bottomhole pressure or Equivalent Circulating Density (ECD) exceeds fracture initiation pressure during circulation, drilling mud starts to escape into the fractured formation and more mud is required to maintain the hydrostatic head. As soon as the dynamic wellbore conditions disappear and the ECD falls below the Fracture Initiation Pressure (FIP) during a pump-off period because of a connection or flow check operation, sizeable amount of mud is gained back into the wellbore. A large amount of mud gain from formation when pumps are turned off can be diagnosed as a well kick. This misjudgment and its likely treatments can lead to unnecessary costly well control procedures. Limited number of studies have been published about the mechanisms behind this phenomenon. According to Gill (1989), elastic deformation of the borehole wall due to the bottomhole pressure can explain this incident. Ram Babu (1998) proposed that expansion and contraction of the drilling fluid due to the temperature variations in the wellbore can be diagnosed as borehole ballooning.

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: none
Teacher disagreement score0.581
Threshold uncertainty score0.996

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 head0.010
GPT teacher head0.209
Teacher spread0.199 · 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

Citations19
Published2007
Admission routes1
Has abstractyes

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