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Record W4401811720 · doi:10.2118/223093-pa

Investigating the Feasibility of EOR While Preloading Parent Wells to Mitigate Fracture Hits: An Experimental and Modeling Study

2024· article· en· W4401811720 on OpenAlexaff
Amin Alinejad, Hassan Dehghanpour

Bibliographic record

VenueSPE Journal · 2024
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPetroleum engineeringGeologyFracture (geology)Geotechnical engineering

Abstract

fetched live from OpenAlex

Summary During a fracturing operation in an infill (child) well, pressure and fluid communication between this well and a nearby parent well, known as fracture hits (FHs), can impair the production performance of both wells. A cost-effective strategy to mitigate the FH is to preload the parent well with water during the fracturing of the child well. It has been hypothesized that the production performance of the parent well can be enhanced by the preloading process if proper additives are used in the injected water. We develop a laboratory protocol to physically simulate primary production and surfactant preloading stages using Montney core and fluid samples under reservoir conditions. We investigate the role of wettability alteration, interfacial tension (IFT) reduction, and surfactant’s chemical stability on the performance of enhanced oil recovery (EOR) during the preloading process. An analytical model is developed to predict the volume of leaked-off surfactant and recovered oil using measured pressure-decline data from the preloading stage. This study only focuses on the interactions of preloading fluid with the parent well’s matrix and does not consider the child-parent well interference. Our results demonstrate that 31.8% of the oil is recovered during primary production from large inorganic pores under solution-gas drive mechanism. Under countercurrent imbibition, a nonionic surfactant leaks off into the smaller organic and inorganic pores and recovers an additional 11.8% oil from a depleted core during preloading. The analytical model estimates oil recovery factors close to the experimental data determined by material balance. Core visualizations demonstrate a population of small oil droplets on the rock surface under reservoir conditions. While IFT is reduced to nearly the same extent by either surfactant, only the wettability-altering surfactant yields incremental oil recovery. Zeta-potential measurements indicate that while neither surfactant alters the rock-water surface charge, the wettability alteration is achieved by modifying the oil-water surface charge even at concentrations above the critical micelle concentration (CMC). Based on the Derjaguin-Landau-Verwey-Overbeek (DLVO) theory, the repulsive electrostatic double-layer (EDL) forces are intensified with an increase in surfactant concentration, resulting in enhanced stability of the water film on the rock surface and increased hydrophilicity. Under elevated temperatures, we observe two phenomena, which can adversely affect the performance of a nonionic surfactant: (a) agglomeration of surfactant particles due to reduced solubility in water, reducing pore accessibility, and (b) chemical decomposition of the surfactant, affecting its ability for IFT reduction and wettability alteration.

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)0.001
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 score0.008
Threshold uncertainty score0.390

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.042
GPT teacher head0.309
Teacher spread0.267 · 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

Citations7
Published2024
Admission routes1
Has abstractyes

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