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Record W4221097070 · doi:10.2118/209026-ms

Thru-Tubing Cleanouts and Acidization in Unconventional Wells

2022· article· en· W4221097070 on OpenAlexaff
J. T. Burke, Cayla Harrison, Francisco Gamarra, Matt Turner, Jim Ruby, Brandon Nono

Bibliographic record

VenueSPE/ICoTA Well Intervention Conference and Exhibition · 2022
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsConocoPhillips (Canada)
Fundersnot available
KeywordsCoiled tubingWorkoverCompletion (oil and gas wells)CasingPetroleum engineeringNozzleProduction (economics)EngineeringDrillingDirectional drillingMechanical engineering

Abstract

fetched live from OpenAlex

Abstract Over the last 12 years, technology in the drilling and completions space has reduced cycle time and dramatically lowered costs for operators. With the adoption of re-stimulations, additional production is being gained from existing wells at a cost that is less than the cost of drilling new wells. However, there has been limited development of low-cost intervention techniques to restore lost production or to extend the life of existing wells. To address this relatively untapped area of intervention, new tools and techniques are needed to revitalize older wells in unconventional reservoirs that are more cost effective than traditional intervention techniques. The economics of a workover are challenged by the uncertainties of successfully removing the existing production tubing and replacing it with a newly designed completion. In response a tool and cleanout technique has been developed that improves the ability of 1.25 in. coiled tubing to clean out the 5.5 in. casing through the 2.375 in. tubing string, thereby eliminating the need to pull and replace the upper completion. A recent application of this new technique in an unconventional well demonstrated that a modified jetting tool (Reverse Nozzle Bit Sub or RNBS), along with a regimented cleanout schedule, can clean out most of the lateral length and restore lost production at a greatly reduced time and cost compared to jointed pipe workovers. Additionally, using coiled tubing to spot acid along the length of the lateral in a uniform matter can remove scale buildup and clean up perforations for improved performance. This paper will review the design, testing and field application of the new tool and technique as well as show early results.

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: Empirical
Teacher disagreement score0.214
Threshold uncertainty score0.724

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)0.0010.000

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 head0.011
GPT teacher head0.206
Teacher spread0.195 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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