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Record W4200210580 · doi:10.2118/207415-ms

Efficient Drilling Technology of Horizontal Wells in the Duverney Block in Canada

2021· article· en· W4200210580 on OpenAlexaboutno aff
Haochen Han, Guobin Yang, Guobin Zhang, Jia Chen, Peter Chen, Fu Jin, Siqi Wang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsnot available
Fundersnot available
KeywordsDrillingPetroleum engineeringBoreholeMeasurement while drillingCasingBlock (permutation group theory)DrillDrilling fluidDirectional drillingEngineeringDrill pipeDrill bitCompletion (oil and gas wells)Mechanical engineeringGeotechnical engineering

Abstract

fetched live from OpenAlex

Abstract Recent years, both exploration and development have made considerable progress in the Duverney block shale gas in Canada. However, technical problems exposed in horizontal drilling engineering need to be optimized: 1) Loss is common in shallow formations; 2) High downhole friction torque, low ROP and drilling cuttings accumulation in long horizontal well section; 3) Borehole instability leads to hanger or packer failure; 4) Drill bits and PDM have short servicing life and low efficiency. Optimization comes from three aspects: (1) Based on previous drilling experience and latest formation condition and development requirement, we design a new well profile for the block taking into drilling safety and further development account;(2) Optimize strong inhibitive, easy-maintenance and high cutting-carrying capacity OBM to ensure the safety requirements in the ultra-long open hole section; (3) BHA and parameters optimization. Optimize drill bit with high-abrasiveness and axial efficiency according to logging data, drillability and UCS. Upgrade conventional PDM into high-performance PDM with even-wall thickness. By means of simulation and calculation, drilling parameters suitable for Duverney block has been optimized. Based on the optimization above, a stable and efficient well profile has been improved solving hanger failure on-site efficiently and complete with composite casing design (4-1/2 inch plus 5 inch) in reservoir section; a 90/10 oil-water ratio OBM has been optimized and applied onsite; Combined with high performance PDC bit and even-wall PDM as well as optimized drilling parameters, higher ROP and longer horizontal section have been achieved. The optimization has made successful field application results:(1) Completion depth has been deepened gradually, from 18,080 ft in 2013 to 23,208 ft at present, with an increase of 28.3%;(2) Horizontal section length has been increasing dramatically, from 6,190 ft in 2013 to 10,301 ft at present, with an increase of 66.4%;(3) The average drilling cycle has been shortened, from 51 days in 2013 to 26 days at present, with a decrease of 48.8%;(4) The average ROP has increased steadily, from 71.2ft/h in 2013 to 82.12ft/h at present, with an increase of 15.3%; (5) Drilling costs per meter have been significantly reduced, from 442.4 CAD/ft in 2013 to 228.3 CAD/ft at present. Combining the optimization and matching design above, it has effectively solved the difficulties of the Duverney block drilling engineering and achieved good field application effects: well depth and horizontal section length in the block have been deepened year by year, the drilling cycle and cost have been decreased year by year, as well as the economic effect has been significant. In all, the research achievements provide a practical and effective reference for horizontal wells in other region especially for the unconventional gas.

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)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.406
Threshold uncertainty score0.816

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.002
GPT teacher head0.146
Teacher spread0.144 · 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
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
Published2021
Admission routes1
Has abstractyes

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