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Record W2041479757 · doi:10.2118/05-06-03

Acid Fracturing Technique for Carbonate Reservoirs Using Nitric Acid Powder

2005· article· en· W2041479757 on OpenAlexafffund
X. Liu, Gang Zhao, Liqiang Zhao, P. Liu

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2005
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of Regina
FundersNatural Sciences and Engineering Research Council of CanadaPetroleum Technology Research Centre
KeywordsCarbonatePenetration (warfare)Nitric acidHydraulic fracturingPetroleum engineeringCarbonate rockFracture (geology)GeologyMaterials scienceGeotechnical engineeringEngineeringMetallurgy

Abstract

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Abstract The length of the etched fracture is rather limited utilizing traditional acid fracturing techniques, especially in a high-temperature carbonate reservoir. Although the propped fractures may have a deeper penetration, they have such drawbacks as low fracture conductivity, unintended proppant bridging, and subsequent proppant flow back. This paper presents the development of a new acid fracturing technique, Nitric Acid Powder (NAP) acid fracturing, to improve the acid penetration and fracture conductivity. The NAP acid fracturing technique has been applied in several oil fields in China. It has been shown that the NAP acid fracturing technique has the advantages of both hydraulic fracturing and acid fracturing, such as long effective penetration, high fracture conductivity, low cost, and easy field operation. We have developed a comprehensive mathematical model for the NAP acid fracturing technique to facilitate the optimization of the field treatment design. The model presented considers fracture growth, acid transport and reaction, leak-off, etched width of the fracture, and so on. The study has shown that the NAP acid fracturing technique could reach a very high stimulation ratio, even in a high-temperature carbonate reservoir. Therefore, it is an innovative and promising technique for well stimulation in carbonate reservoirs. Introduction Carbonate formations generally have a low permeability and can be highly fissured. Long fractures in acid fracturing treatments are essential to maximize production. Acid must react with the walls of the fracture to form a channel that remains open after the treatment. Flow channels can be formed as a result of an uneven reaction with the rock surface or preferential reaction with minerals heterogeneously distributed in the formation. If the formation temperature is very high, the reaction rate will be fast. If this occurs, the acid treatment will tend to remain in the near wellbore vicinity, resulting in short penetration. Acid fracturing techniques are the primary preference in carbonate formations. Operationally, acid fracturing is less complicated because no propping agents are used, which eliminates the risk of a screen-out and subsequent problems of proppant flowback and cleanout from the wellbore. Generally, acid-etched fractures have high conductivity, although they are quite limited in penetration, whereas the propped fractures have limited conductivity with deeper fracture penetration. The techniques to overcome the limitations of conductivity and penetration for the carbonate formation have been studied continuously to enhance the acid fracturing technology. Equilibrium acid fracturing was developed by Tinker(1) to maximize the contact time of acid with the fracture face to get a high fracture conductivity in cool dolomite formations, which react slowly with acid. Maximum acid contact time is essential to create highly conductive etched channels on the fracture faces. After the designed fracture length is created, the injection is continued at certain rates to maintain the equilibrium with the fluid leak-off rate from the created fracture faces. This technique was proven to be effective in stimulating the relatively cool dolomite. Closed acid fracturing techniques(2) were designed to obtain high conductivity, especially for the formations with extra high fracture close stress.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

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 communication0.0000.000
Open science0.0000.000
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 head0.009
GPT teacher head0.221
Teacher spread0.211 · 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 designBench or experimental
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
Published2005
Admission routes2
Has abstractyes

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