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Record W1979880440 · doi:10.2118/1012-0126-jpt

Improving Horizontal Completions in Heterogeneous Tight Shales

2012· article· en· W1979880440 on OpenAlex
Dennis Denney

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Petroleum Technology · 2012
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsOil shaleCompletion (oil and gas wells)Petroleum engineeringWellboreGeologyPermeability (electromagnetism)Tight oilHydraulic fracturingMining engineeringPaleontology

Abstract

fetched live from OpenAlex

This article, written by Senior Technology Editor Dennis Denney, contains highlights of paper SPE 146998, ’Improving Horizontal Completions in Heterogeneous Tight Shales,’ by Roberto Suarez-Rivera, SPE, Chaitanya Deenadayalu, Maxim Chertov, SPE, Ricardo Novalo Hartanto, SPE, and Patrick Gathogo, Schlumberger, and Rahul Kunjir, University of Utah, prepared for the 2011 Canadian Unconventional Resources Conference, Calgary, 15-17 November. The paper has not been peer reviewed. Production from nanodarcy-range-permeability shale formations requires extensive hydraulic fracturing, large volumes of water, and closely spaced wells. Comparing calculations of the possible fracture-surface area created during treatments to production results indicates that a large portion of that surface area is ineffective for production, resulting in ineffective use of resources. A fundamental understanding is required to improve the efficiency of horizontal completions in producing shales. The objective of this study was to improve completion design and horizontal-well-completion efficiency. Introduction When considering tight-shale-formation characterization and completion design, one should evaluate the formation characteristics conducive to economic production: reservoir quality (RQ), representing the multiple properties defining reservoir potential, and completion quality (CQ), representing the multiple properties defining the potential for creating and sustaining a large surface area in contact with the reservoir. RQ and CQ properties vary in the near-wellbore and far-wellbore regions. For CQ, the far-wellbore region represents the region of contact between the created fracture and the reservoir. Well production depends on this surface area being in contact with good RQ, and depends on conditions of containment, fracturability, rock/fluid interactions, and loss of surface area and fracture conductivity during production. The near-wellbore region represents the choking point between the created surface area and the wellbore. The goal is to maximize connectivity between the fracture system and the wellbore. This goal is attainable by minimizing near-fracture tortuosity, maximizing fracture width, reducing breakdown pressures, and limiting the risk of solids production. The result is a nonsubjective and consistent method that provides a means for understanding variability in fracture performance along wellbores (e.g., inferred from microseismic monitoring, trace analysis, and stage-by-stage flow measurements) and for selecting perforation stages on the basis of measured or log-inferred rock properties. The method also provides a means for monitoring consistency between the predicted values and measured 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.

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 score0.305
Threshold uncertainty score0.388

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.208
Teacher spread0.202 · 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