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Record W2736751931 · doi:10.2118/0718-0062-jpt

Technology Focus: New-Frontier Reservoirs I (July 2018)

2018· article· en· W2736751931 on OpenAlexaboutno aff
Simon Chipperfield

Bibliographic record

VenueJournal of Petroleum Technology · 2018
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsDrillPetroleum engineeringCoringReservoir engineeringGeologyHydraulic fracturingGeomechanicsDrillingMining engineeringEngineeringPetroleumGeotechnical engineeringMechanical engineeringPaleontology

Abstract

fetched live from OpenAlex

Technology Focus Recently, a lot of discussion has revolved around the benefits of multilaterals in unconventional reservoirs. But is this truly the next breakthrough for the industry, or is it all hype? No doubt enormous need exists for a technology such as this to improve reservoir recovery and reduce well cost. The current modus operandi in many plays is to drill horizontal hydraulically fractured wells. The results, however, continue to show that these well types are not effective at draining the reservoir. This is a result of complex hydraulic-fracture geometries with very short propped heights and lengths. Fracture complexity is a natural phenomenon now proved by coring and is likely caused by reservoir stratigraphy and geomechanics. Completion engineers typically counteract this, to some degree, by pumping more fracture treatments in the horizontals. This ineffective drainage points to the benefits of greater reservoir contact with a multilateral. As well as improved drainage, multilateral technology also can reduce well cost by avoiding the necessity to drill top hole for the second (or third) lateral and requiring only one completion and one set of surface equipment. Multilateral technology has been around for many years; however, what has changed in recent times is the reliability of these systems, with more than 98% reliability quoted in a recent publication. Hydraulically fracturing the laterals is now possible as well. Companies such as Occidental, BP, and ConocoPhillips are evaluating the potential of this technology in onshore unconventional plays. In fact, in the fourth quarter of 2017, Occidental successfully performed its first pilot. Enormous need for this technology exists, and time will tell whether it is the next major step in subsurface technology to improve the unit cost of production. Recommended additional reading at OnePetro: www.onepetro.org. SPE 188231 Modeling Early-Time Rate Decline in Unconventional Reservoirs Using Machine Learning Techniques by Aditya Vyas, Texas A&M University, et al. SPE 186107 Optimization of Spacing and Penetration Ratio for Infinite-Conductivity Fractures in Unconventional Reservoirs: A Section-Based Approach by S. Liu, Texas A&M University, et al. SPE 186092 Rate Dependence of Bilinear Flow in Unconventional Gas Reservoirs by M.S. Kanfar, University of Calgary, et al.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.319
Threshold uncertainty score0.902

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.006
GPT teacher head0.216
Teacher spread0.210 · 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 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
Published2018
Admission routes1
Has abstractyes

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