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Record W3047189331

Influence of formation anisotropy and axial compliances on drilling performance

2019· dissertation· en· W3047189331 on OpenAlexfundno aff
Abdelsalam Abugharara

Bibliographic record

VenueMemorial University Research Repository (Memorial University) · 2019
Typedissertation
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsnot available
FundersMemorial University of NewfoundlandSuncor Energy IncorporatedCanadian Bureau for International Education
KeywordsDirectional drillingDrillingPetroleum engineeringOil shaleGeologyMeasurement while drillingAnisotropyRate of penetrationGeotechnical engineeringMechanical engineeringEngineering
DOInot available

Abstract

fetched live from OpenAlex

Drilling provides the path to reach and exploit underground oil and gas reserves. Drilling oil and gas wells can be vertical, inclined, or horizontal. However, as non-vertical drilling has become dominant, success in increasing oil and gas production has been led by horizontal drilling. Trajectories of horizontal wells have three main curvature segments: vertical, inclined (diagonal or oblique), and horizontal, where the properties of the encountered formation during drilling may vary with inclination. Rocks, classified as anisotropic (i.e. shale), whose properties are directional dependent or classified as isotropic (i.e. fine-grained and sandstone), whose properties are not directional dependent, have high influence on drilling performance, especially in nonvertical drilling. The significant shift towards horizontal drilling has increased the interest in laboratory studies and research on directional drilling, particularly in shale, to evaluate the influence of anisotropy orientation on drilling performance (i.e. ROP), and therefore, choose optimal trajectory, enhance performance, and reduce costs. This dissertation focuses on: (i) developing an experimental procedure for classifying rock anisotropy through oriented physical, mechanical, and drilling measurements, (ii) evaluating the influence of shale (as VTI rocks) anisotropy orientation on drilling parameters, and (iii) investigating the enhancement of the drilling rate of penetration (ROP) by implementing the novel drilling technique of passive Vibration Assisted Rotary Drilling (pVARD). First, a laboratory baseline procedure was developed for a rock anisotropy characterization involving oriented physical, mechanical, and drilling tests on rock like materials (RLM). This research objective was to develop the procedure on synthetic rocks (RLM) as well as natural rocks, including shale, granite, and sandstone. Second, detailed oriented physical, mechanical, and drilling measurements were taken for the determined isotropic and non-isotropic rocks in stage I, then aimed to interlink all results of all measurements, through which isotropic rock classifications can be enriched, and confirmed. Third, compliant (i.e. pVARD) versus non-compliant (without pVARD) drilling was performed in various rocks for the purpose of evaluating the influence of axial oscillations on drilling performance. Also, the parameters behind enhancing ROP with compliant versus non-compliant were investigated in this research. Last, a relationship between oriented strength and oriented drilling parameters for isotropic and anisotropic rocks was developed. This research aims to establish relationships between strength variation, drilling performance, and the main drilling parameters that influence ROP in different rock types for the purpose of rock isotropy / anisotropy evaluation.

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)0.002
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0010.000

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 head0.016
GPT teacher head0.224
Teacher spread0.208 · 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
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

Citations0
Published2019
Admission routes1
Has abstractyes

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