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On the issue of acid treatment of the well bottomhole

2025· article· W4416807954 on OpenAlexaboutno aff
Shahin Ziraddin Ismayilov, A.V. Sultanova

Bibliographic record

VenueBulletin of the Tomsk Polytechnic University Geo Assets Engineering · 2025
Typearticle
Language
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)SedimentationFiltration (mathematics)ProductivityWorkoverPoint (geometry)Mathematical modelProduction (economics)

Abstract

fetched live from OpenAlex

Relevance. The need to understand the features of reservoir and well interaction. To solve a number of scientific and engineering problems, it is currently necessary to stabilize the flow rate. World practice shows that many deposits in Siberia, Canada, Mexico, Venezuela are represented by heavy oils, which contain a significant amount of paraffins, resins and asphaltenes. When the temperature at the bottomhole decreases, the sedimentation of these components negatively affects the filtration and capacity properties. They are soluble in acid solutions, resulting in positive effect, which consists in increasing the efficiency of bottomhole zone treatment, as an aftermath of which the productivity of wells increases, which is an important task in the context of rising prices for hydrocarbons. Therefore, a more efficient use of the existing well stock, which, in comparison with drilling new wells, is the most rational from an economic point of view is realized. Aim. Theoretical substantiation using hydrodynamic modeling, which allows estimating the duration of acid treatment and efficiency in terms of increasing productivity. Mathematical calculation of the specified characteristics based on initial formation and well data. Using modern methods of perforation, acid treatment of the bottomhole zone, it is possible to stabilize or increase oil production by affecting the bottomhole of production wells. Methods. Mathematical modeling based on the course of underground hydromechanics and static methods. Results and conclusions. The conducted mathematical analysis allows determining the main parameters of the solution injected into the well. Based on the data of the calculation formulas it is possible to determine the time of injection to stabilize the parameters of the formation. The proposed work has a special practical value, since acid treatment increases productivity by 10–20%, which in these conditions even with a small well flow rate is significant. With the given parameters, production was 3.5 t/day, after the acid treatment, an increase in the filtration and capacity characteristics of the bottomhole zone by 17% is observed.

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 categoriesMeta-epidemiology (narrow)
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 score0.920
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.003
GPT teacher head0.172
Teacher spread0.169 · 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.

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

Citations0
Published2025
Admission routes1
Has abstractyes

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