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Record W4401812942 · doi:10.2118/218032-pa

Understanding the Dynamics of Matrix-Fracture Interaction: The First Step Toward Modeling Chemical EOR and Selecting Suitable Fracturing Fluid in Unconventional Oil/Gas Recovery

2024· article· en· W4401812942 on OpenAlexaff
Lixing Lin, Tayfun Babadagli, Huazhou Li

Bibliographic record

VenueSPE Journal · 2024
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPetroleum engineeringEnhanced oil recoveryHydraulic fracturingUnconventional oilFracturing fluidFracture (geology)Tight gasMatrix (chemical analysis)Reservoir simulationGeologyFossil fuelChemistryGeotechnical engineeringEngineeringWaste managementChromatography

Abstract

fetched live from OpenAlex

Summary The effects of chemical additives on mitigating water blocking and improving oil recovery were experimentally examined for gas-water and oil-water systems in spontaneous imbibition cells. In these attempts, two factors are critically important: (1) understanding the physics of the interaction, whether it is co- or countercurrent, and (2) characteristics of the chemical additives to suitably orient the interaction for specific purposes (accelerate/decelerate matrix-fracture interactions). Co- and countercurrent imbibition experiments were conducted on sandstone rock samples using various oil samples (viscosities between 1.37 cp and 54.61 cp) as well as gas (air). The selected new-generation chemical additives included deep eutectic solvents, cationic/anionic/nonionic surfactants, and inorganic and organic alkalis. We observed that the functionality of the chemicals varied depending on the fluid type, interaction type (co- or countercurrent), and application purposes. For instance, chemicals such as the cationic surfactant cetyltrimethylammonium bromide (CTAB) significantly reduced water invasion into the gas-saturated sandstone cores during fracturing, while chemicals such as the nonionic surfactant Tween® 80 provided considerable oil recovery improvement in the oil-saturated sandstone cores. The surface tension and wettability of the rock surface are crucial factors in determining the suitability of chemicals for mitigating water blockage. In terms of oil recovery, certain chemical additives, such as O342 and Tween 80, may result in a lower recovery rate in the early stage because of their strong ability in interfacial tension (IFT) reduction but could lead to a higher ultimate recovery factor by altering the wettability. Additionally, the introduction of chemicals resulted in notable spontaneous emulsification, especially in countercurrent imbibition, thereby enhancing oil recovery. The spontaneous emulsification and its stability are influenced by factors such as oil drop size, boundary condition, interaction type, IFT, wettability, as well as rock surface charges. The results have implications for understanding the physics and dynamics of matrix-fracture interactions in co- and countercurrent conditions. In addition, they serve as the first step toward selecting appropriate chemical additives in hydraulic fracturing fluid design and enhancing oil recovery in unconventional reservoirs.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

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 communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.024
GPT teacher head0.258
Teacher spread0.234 · 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 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

Citations6
Published2024
Admission routes1
Has abstractyes

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