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Record W2483902342 · doi:10.2118/00-10-05

Application of Multiphase Flow Methods to Horizontal Underbalanced Drilling

2000· article· en· W2483902342 on OpenAlexaboutno aff
S. Smith, G.A. Gregory, N Munro, Muhammad Muqeem

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2000
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsnot available
Fundersnot available
KeywordsUnderbalanced drillingPetroleum engineeringDrillingDrilling fluidDirectional drillingMultiphase flowLost circulationCoiled tubingTrippingCompletion (oil and gas wells)Well drillingGeologyEngineeringMechanical engineeringMechanics

Abstract

fetched live from OpenAlex

Abstract Multiphase flow can be present in all aspects of underbalanced drilling. This paper outlines the ways in which multiphase flow pressure loss calculations can be used by drilling engineers in the design and optimization of underbalanced drilling operations. Then, detailed field measurements for several horizontal wells drilled underbalanced with coiled tubing are used to evaluate the application of existing pressure loss calculation methods to this unique application. Introduction Underbalanced drilling (UBD) is rapidly gaining popularity in the oil and gas industry. The Alberta Energy and Utilities Board ID94–3(1) defines underbalanced drilling as follows: "When the hydrostatic head of a drilling fluid is intentionally designed to be lower than the pressure of the formation being drilled, the operation will be considered underbalanced drilling. The hydrostatic head of the drilling fluid may be naturally less than the formation pressure or it can be induced. The induced state may be created by adding natural gas, nitrogen, or air to the liquid phase of the drilling fluid. Whether induced or natural, this may result in an influx of formation fluid which must be circulated from the well and controlled at surface." Benefits of Underbalanced Drilling Maintaining the pressure in the wellbore below the reservoir pressure allows reservoir fluids to enter the wellbore while UBD operations proceed, thus preventing flow of drilling fluids (and associated solids) into the formation, thereby minimizing or even eliminating formation damage. This is of particular importance in the drilling of horizontal wells as the formation is exposed to the drilling fluids for an extended period of time. Although formation damage reduction is the most widely recognized benefit of underbalanced drilling, several additional benefits are outlined below: Increased Penetration Rates Underbalanced drilling can achieve higher rates of penetration due to reduced "chip holdown" and decreased hydrostatic pressure at the bit face. Reduction in "chip holdown" refers to easier removal of drilled solids from the vicinity of the drill bit due to the flow of drilling and reservoir fluids, thus allowing the bit to drill into fresh rock continuously. The decreased hydrostatic pressure at the bit face reduces stress in the rock being drilled, allowing it to fail more easily. The experience of drilling engineers(2) familiar with UBD is that the rate of penetration can be increased by between three and ten times that of conventional drilling. Minimal Lost Circulation Underbalanced drilling gives better control in situations where fractured, low pressure, or high permeability formations may lead to the loss of drilling fluids and the associated problems that can cause. Evaluation While Drilling Data acquired in real time during underbalanced drilling operations allow for both the short term on site optimization of the UBD operation, and the longer term assessment of the well's potential. On site, the data acquired can be used to optimize drilling parameters such as the well's horizontal length, vertical depth, and orientation. Other data that can be obtained, useful both on site and long term, include fluid properties, productivity, and geological interpretations of the formation.

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.004
GPT teacher head0.224
Teacher spread0.220 · 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 designBench or experimental
Domainnot available
GenreMethods

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

Citations17
Published2000
Admission routes1
Has abstractyes

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