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Record W3081228570 · doi:10.2118/202485-pa

An Infill Well Fracturing Model and Its Microseismic Events Barrier Effect: A Case in Fuling Shale Gas Reservoir

2020· article· en· W3081228570 on OpenAlexaff
Haiyan Zhu, Xuanhe Tang, Yujia Song, Kuidong Li, Jialin Xiao, Maurice B. Dusseault, John McLennan

Bibliographic record

VenueSPE Journal · 2020
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsInfillGeomechanicsMicroseismGeologyFracture (geology)CaprockHydraulic fracturingTight gasOil shaleGeotechnical engineeringPetroleum engineeringSeismologyEngineeringStructural engineering

Abstract

fetched live from OpenAlex

Summary A microseismic (MS) events barrier (MSEB) phenomenon was detected during infill well fracturing of the Fuling shale gas reservoir. This phenomenon was evidenced by MS monitoring results, indicating that when the infill well hydraulic fracture (HF) propagated close to the parent well stimulated region, only a main straight fracture was propagating. Also, the number of seismic events diminished abruptly, suggesting some barrier or an attenuation process for the MS. To clarify the mechanisms involved in the MSEB effect, the infill well fracture propagation is investigated. An integrated workflow is proposed to analyze complex HF propagation of an infill well after the offset parent wells have experienced fracturing and production. The workflow integrates a geological model with natural fractures, a parent well fracturing geomechanical model, a coupled flow-geomechanics production model, and an infill well fracturing geomechanical model. First, a natural fracture network is embedded in the realistic geological model. Second, a geomechanical fracturing model is developed to simulate HF of parent wells. Third, a coupled flow-geomechanics model is used to analyze stress field evolution during parent well production. Fourth, complex HF propagation for the infill well is simulated. The case model is validated with parent well production data and infill well fracturing MS monitoring results. It can be concluded from the simulation results that (1) during parent well production, the pre-existing complex fracture network is a major contributor to pore-pressure decrease; (2) stress evolution is affected by the geomechanical heterogeneity; (3) near the parent well producing fractured region, the fracture complexity of the infill well stimulation decreases sharply and that matches well with the MS monitoring results; and (4) there are two primary mechanisms that are responsible for the MSEB phenomenon—natural fracture (NF) activation during parent well fracturing and stress evolution in parent well production. The Fuling shale gas reservoir infill well fracturing case study reveals the mechanism of the MSEB effect by demonstrating the impact of parent well production on infill well fracturing. To serve the fracture-hits evaluation and to maximize the stimulated reservoir volume (SRV), the MSEB effect should be taken into consideration in infill well fracturing design.

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 score0.003
Threshold uncertainty score0.854

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 integrity0.0000.001
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 head0.010
GPT teacher head0.236
Teacher spread0.226 · 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

Citations35
Published2020
Admission routes1
Has abstractyes

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