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Record W2571347807 · doi:10.2118/184865-ms

Analyzing ISIP Stage-by-Stage Escalation to Determine Fracture Height and Horizontal-Stress Anisotropy

2017· article· en· W2571347807 on OpenAlexaff
Nicolas Roussel

Bibliographic record

VenueSPE Hydraulic Fracturing Technology Conference and Exhibition · 2017
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsConocoPhillips (Canada)
FundersConocoPhillips
KeywordsMicroseismHydraulic fracturingAnisotropyFracture (geology)GeologyStage (stratigraphy)TiltmeterPerforationStress (linguistics)Stress fieldGeotechnical engineeringMechanicsStructural engineeringEngineeringSeismologyMechanical engineeringPhysics

Abstract

fetched live from OpenAlex

Abstract ISIP Analysis is a novel analytical method that calculates the hydraulic height of induced fractures and the in-situ horizontal stress anisotropy from the evolution of instantaneous shut-in pressures during a multi-stage horizontal completion. The fracture height calculated will be smaller than what is measured through microseismic measurement, but larger than the propped and effective fracture height. Because every frac stage contributes to increase minimum horizontal stress and reduce the formation's horizontal stress anisotropy, ISIP Analysis may be a useful tool to guide the spacing design of perforation clusters. Increased characterization of hydraulic fracture dimensions from ISIP Analysis also makes it a useful addition to any workflow looking to optimize well spacing and stacking in unconventional plays. Multiple formulations of the stress escalation equation were derived, as well as type-curves that relate hydraulic-fracture height to the parameters of the equation. ISIP Analysis consists in finding the unique combination of parameters of the stress escalation equation that best matches field ISIP data. Application of ISIP Analysis is illustrated in the paper using field data taken from wells in various shale formations across North America. It addresses key uncertainties in the design of unconventional field development and is being proposed as an inexpensive alternative to other stress/fracture diagnostic techniques. In addition, the method has been successfully used to design the number of perforation clusters and their spacing to reach a desired magnitude of stress interference during horizontal-well stimulation. While other techniques such as microseismic monitoring, tracers, downhole tiltmeters, pressure gauges, may be utilized to characterize fracture dimensions, the main advantage of ISIP Analysis is the ability to be applied to a vast majority of wells, without additional hardware, operational delay, or any modification to the well or completion design. As a result of its simplicity, ISIP Analysis takes a trained completion engineer only a few minutes to complete.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.234
Teacher spread0.223 · 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 designObservational
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

Citations33
Published2017
Admission routes1
Has abstractyes

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