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Record W2911879762 · doi:10.2118/191376-pa

Wormhole Formation During Acidizing of Calcite-Cemented Fractures in Gas-Bearing Shales

2019· article· en· W2911879762 on OpenAlexaff
Piotr Szymczak, Kamil Kwiatkowski, Marek Jarosiński, Tomasz Kwiatkowski, Florian Osselin

Bibliographic record

VenueSPE Journal · 2019
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of Calgary
FundersPanstwowy Instytut Geologiczny-Panstwowy Instytut Badawczy
KeywordsCalciteOil shaleCarbonateGeologyWormholePermeability (electromagnetism)Merge (version control)Fracture (geology)Petroleum engineeringMineralogyGeotechnical engineeringMaterials scienceChemistry

Abstract

fetched live from OpenAlex

Summary A relatively large number of calcite-cemented fractures are present in gas-bearing shale formations. During hydraulic fracturing, some of these fractures will be reactivated and may become important flow paths in the resulting stimulated fracture network. On the other hand, the presence of carbonate lamina on fracture surfaces will have a hindering effect on the transport of shale gas from the matrix toward the wellbore. We investigate numerically the effect of low-pH reactive fluids on such fractures, and show that dissolution of the cement proceeds in a highly nonuniform manner. The morphology of the emerging flow paths (“wormholes”) strongly depends on the thickness of the calcite layer. For thick carbonate layers, a hierarchical, fractal pattern appears, with highly branched wormhole-like channels competing for an available flow. For thin layers, the pattern is much more diffuse, with less-pronounced wormholes that merge easily with each other. Finally, for intermediate thicknesses, we observe a strong attraction between shorter and longer wormholes, which leads to the formation of islands of carbonate lamina surrounded by the dissolved regions. We argue that the wormhole-formation processes are not only important for the increase of shale-gas recovery, but also can be used for retaining the fracture permeability, even in the absence of proppant.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.513
Threshold uncertainty score0.383

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 integrity0.0000.000
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 head0.006
GPT teacher head0.222
Teacher spread0.217 · 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

Citations9
Published2019
Admission routes1
Has abstractyes

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