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Record W2911898253 · doi:10.2118/194322-ms

Dynamic Fracture Volume Estimation using Flowback Data Analysis and its Correlation to Completion-Design Parameters

2019· article· en· W2911898253 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSPE Hydraulic Fracturing Technology Conference and Exhibition · 2019
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsFracture (geology)Volume (thermodynamics)ChokePetroleum engineeringHydraulic fracturingCompletion (oil and gas wells)GeologyMaterials scienceMechanicsGeotechnical engineeringEngineering

Abstract

fetched live from OpenAlex

Abstract Hydraulic fracturing combined with horizontal drilling is the key to unlocking vast unconventional reservoirs. However, understanding the relationship between fracturing/completion-design parameters and the process efficiency remains challenging. The objectives of this paper are 1) to estimate initial fracture volume and its variations during the production by using flowback data and 2) to investigate the existence of correlations between completion-design parameters and induced fracture volume process optimization. We analyze flowback data and completion-design parameters of 16 shale-gas completed in the Eagle Ford Formation. First, we estimate ultimate water recovery and initial fracture volume by using harmonic-decline model, and fracture volume loss during flowback by using a new iterative approach that accounts for fracture-porosity changes with time. Then, we conduct a multivariate analysis to develop empirical correlations of completions-design parameters with initial fracture volume and fracture characteristic-closure rate (FCR). The results show that harmonic-decline model could be used to estimate initial fracture volume with an average absolute percentage error (AAPE) of 7%. The correlations developed between initial fracture volume and completion-design parameters show that the proppant concentration has the most significant effect on fracture volume, followed by gross perforated interval (GPI) and shut-in time, respectively. Total vertical depth (TVD) and fluid injection rate have insignificant effects. The results indicate that increasing choke size during early flowback leads to a relatively-sharp decrease in fracture volume, while changing choke size during late flowback has negligible effects. The proposed correlation between FCR and completion-design parameters demonstrates the significant effect of proppant concentration on fracture closure during flowback, while GPI and TVD have negligible effects.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.503
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.020
GPT teacher head0.247
Teacher spread0.228 · 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