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Record W2058292580 · doi:10.2118/2008-017

Estimation of Suspended Particle Retention Rate and Permeability Damage in Sandstone from Back Analysis of Laboratory Injection Tests

2008· article· en· W2058292580 on OpenAlexaff
Z. Li, R.C.K. Wong

Bibliographic record

VenueCanadian International Petroleum Conference · 2008
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPermeability (electromagnetism)CitationComputer scienceChemistryLibrary science

Abstract

fetched live from OpenAlex

Abstract This paper investigates the suspended particle retention rate and permeability damage in porous sandstone during produced water injection process. The data used in this study was obtained from one-dimensional constant rate injection tests in which both the effluent concentration and the pressure drop were recorded. The particle retention process was modeled as a filtration process using finite difference method. The intrinsic filtration and permeability reduction functions were determined by matching the overall measured effluent concentration and pressure drop data. Least square method was used as an optimization technique in the back analysis. Introduction Produced water re-injection process is considered as the most suitable and economical method to dispose the produced waste water with minimum environment impact. However, the loss of permeability and injectivity due to the particle retention within the formation around the injection wells is a common problem in this process. Mettananda (2005) conducted 1-D injection tests with particle suspensions to study the particle retention and permeability reduction in sandstone specimens. In this paper, systematic methodologies are developed to analyze the results measured from these injection tests to determine the filtration and permeability reduction functions. Particle suspension Injection experiments (Mettananda 2005) Materials and fluids used The sandstone specimens used in the study were recovered at depths of about 1750–1774 m from Camaal-30 Well of the Qishn formation, Masila block, Yemen. Specimens of 3.8 cm in diameter and 6.3 cm in length were trimmed from drilled cores. Fig. 1 shows a typical thin section of Qishn sandstone specimen. Results from mercury intrusion porosimetry tests show that the porosity values lie in a range of 0.17-0.23, and the median pore throat sizes are within 10–33 µm. Fig. 2 shows a typical pore throat size distribution of Qishn sandstone specimen. Formation water present in oilfields is usually brine. Results of the chemical analysis of Qishn sandstone formation water showed that the main cations present are Na+ and Ca2+ while the main anions are Cl−, SO42-and HCO3-. Based on the milliequivalents, the equivalent NaCl concentration was estimated to be 2646 mg/l. To be on the conservative side, 5 g/l NaCl brine was used in the flow experiments. Silica fume was selected to be the type of particle used in the experiments. Silica fume is a commercially available admixture used in concrete material. It does not flocculate in NaCl solution and has a wide size range of 0.4 µm to 60 µm. Based on the pore throat size distribution of the core specimens (median pore throat sizes are 10–33 µm), the injected particles should have a size range between approximately 0.6 µm to 8 µm. Sedimentation method was used to achieve a good separation. Test setup In this study, a flexible wall permeameter (ASTM D 5084- 03) was used in the 1-D injection tests. In this method, the same confining pressure is applied to the specimen, both in radial and axial directions. A schematic of the permeameter used is shown in Fig. 3.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.014
GPT teacher head0.225
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 designObservational
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
Published2008
Admission routes1
Has abstractyes

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