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Record W1975892284 · doi:10.2118/152631-ms

Implications of Fracturing Pressure Data Recorded during a Horizontal Completion on Stage Spacing Design

2012· article· en· W1975892284 on OpenAlexaff
Nicolas Roussel, Ripudaman Manchanda, Mukul M. Sharma

Bibliographic record

VenueSPE Hydraulic Fracturing Technology Conference · 2012
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsConocoPhillips (Canada)
FundersUniversity of Texas at AustinU.S. Department of Energy
KeywordsHydraulic fracturingGeologyFracture (geology)Oil shaleTransverse planePerforationMicroseismStress (linguistics)Tight gasCompletion (oil and gas wells)Geotechnical engineeringShale gasPetroleum engineeringEngineeringSeismologyStructural engineering

Abstract

fetched live from OpenAlex

Abstract Horizontal completions have changed considerably in the last few years in an effort to substantially improve the drainage of shale gas reservoirs. The spacing of fracture stages and perforation clusters are among the most crucial completion decisions that impact well productivity and EUR. Yet, the decision regarding stage spacing is rarely guided by an engineering process, as it remains a challenge to tie production performance and completion design. In this paper, we offer some insight on the impact of fracture spacing on the propagation direction of multiple transverse fractures, and consequently the expected performance of the horizontal well. Stress-shadow effects, related to the mechanical interference induced by a proppant-filled fracture, can cause fractures initiated from a horizontal well to deviate toward or away from previous fractures. A three-dimensional geomechanical model of the combined stress interference from multiple transverse fractures has been applied to typical wells in three shale gas reservoirs: Bakken, Barnett and Eagle Ford. The existence of an optimum spacing is demonstrated, where fracture stages remain transverse even when subject to stress-shadow effects. Below the optimum spacing, induced fractures may intersect previous fractures, and re-stimulate previously fractured regions of the reservoir, while leaving undrained portions of the reservoir un-stimulated. Such behavior is highly dependent on the mechanical properties of the shale, in particular the Young’s modulus. Our modeling results suggest that the net fracturing pressure data measured in the field reflects the propagation direction of the fractures induced from the horizontal wellbore. A monotonic increase in net pressure, going from one stage to another, would indicate transverse fracture propagation during all stages. On the other hand, an up-and-down trend in the net pressure data is an indication that the mechanical stress interference is causing the later stage fractures to intersect fractures from previous stages. The net pressure data can, therefore, be used to investigate fracture-to-fracture interference and can be used to optimize the spacing of fracture stages in horizontal completions.

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)0.001
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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.043
GPT teacher head0.263
Teacher spread0.220 · 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

Citations55
Published2012
Admission routes1
Has abstractyes

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