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Record W1988522730 · doi:10.2118/163957-ms

Practical Directional Drilling Techniques and MWD Technology in Bakken and Upper Three Forks Formation in Williston Basin North Dakota to Improve Efficiency of Drilling and Well Productivity

2013· article· en· W1988522730 on OpenAlexaboutno aff
Guangzhi Han, Wilfredo Davila, Eric C. Magnuson, Azar Azizov

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsnot available
FundersBaker Hughes
KeywordsDrillingDirectional drillingPetroleum engineeringGeologyDevonianPetroleumStructural basinHydraulic fracturingNatural gasCompletion (oil and gas wells)Well drillingOil fieldMining engineeringPaleontologyEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

Abstract The Upper Devonian-Lower Mississippian Bakken petroleum system, including the Bakken, Lower Lodgepole, and Upper Three Forks formations, is a widespread unit within the central and deeper portions of the Williston Basin in Montana, North Dakota, and the Canadian provinces of Saskatchewan and Manitoba. The USGS estimated that the U.S. portion of the Bakken Formation contains between 3 and 4.3 billion barrels of undiscovered, recoverable oil, 1.85 Tcf of associated/dissolved natural gas and 148 million barrels of natural gas liquid; the Upper Three Forks Formation is estimated to contain 20 billion barrels of oil, with approximately 2 billion barrels of recoverable oil. There are extensive horizontal drilling and multi-stage hydraulic fracturing activities targeting these two formations. Those horizontal wells typically have 10,000 ft lateral sections in pay zones and multi-stage hydraulic fracturing with 24 to 36 stages. The extensive well paths bring numerous challenges, including precisely landing the curve, enhancing drilling rig operating conditions to obtain measuring while drilling (MWD) system optimal performance, and avoiding drilling into undesirable formations. Overlooking some or all of these conditions could lead to unnecessary high dogleg severity (DLS), poor rate of penetration (ROP), unnecessary trips and sidetracks to name a few. All these conditions could ultimately add additional time and cost to the drilling and completion program of the well and in the worst-case lower future production rates to the operator. Several practical field techniques and technology applications are presented as solutions to help optimize ROP, reduce non-productive rig time and chances of sidetracks. Several field examples were analyzed. The techniques gained are valuable for developing optimal drilling practice procedures, and improving drilling operations and future well production.

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: Methods · Consensus signal: none
Teacher disagreement score0.365
Threshold uncertainty score0.726

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 studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.005
GPT teacher head0.218
Teacher spread0.212 · 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
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

Citations6
Published2013
Admission routes1
Has abstractyes

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