Prediction of Formation Damage Caused by Suspend Solids from Injected Water and a Guideline for TSS Control
Notice bibliographique
Résumé
Abstract During waterflooding, suspend solids are usually contained in the injected water, which may gradually block pores and cause formation damage after flowing into a formation and being trapped there. Water treatment is usually conducted on the surface to reduce TSS (Total Suspended Solids) before being injected. However, to what extent the TSS should be controlled depends on specific water injection conditions and there are no methods in industry to quantitatively evaluate it. Meanwhile, the corrections between the injection parameters and the extent of formation damage are not clear. In this paper, a near-wellbore axisymmetric suspension flow and particle retention model is established based on the Langmuirian Pore Blocking mechanism. This model is solved numerically by Shampine's code developed in MATLAB using an explicit central finite deference method. Based on this model, pressure drop, damage factor, damage zone radius and damage time are defined and the methods to obtain them are described. With assumed injection parameters, the basic tendencies of particle retention as well as the influences of TSS, injection rate, initial filtration coefficient and maximum formation retention capacity are investigated. A general guideline is given in the end, suggesting the determination of three formation-related parameters and control of four operational parameters. A workflow for determining the TSS of injection water based on these models is also proposed. The modelling results using the assumed water injection parameters lead to deep understandings on the particle retention-caused formation damage. The concentration of retained particles is the highest near a wellbore and gradually declines to zero. Most of the particle retention occurs within five meters to the wellbore. The concentration of retained particles gradually increases with time, and the rate of increase is relatively high at the beginning of water injection but slows down with injection time. The damage zone radius increases continuously with the injection time, and it can reach 4.0-6.0m after 10 years of water injection. Most of the damage occurs in the first three years, which accounts for at least 60% of the 10 years’ cumulative damage. Higher TSS in injection water causes quicker and deeper damage to a formation. When TSS increases from 10mg/L to 100 mg/L, the damage zone radius with three years of water injection is doubled and the damage time is decreased by 30%. A higher injection rate will result in a larger damage zone radius. When the injection rate increases from 1.0bbl/(day·ft) to 6.0bbl/(day·ft), the damage zone radius is deepened by 30% after five years’ water injection and the damage time is shortened by 31.5%. The initial filtration coefficient has big influence on the damage zone radius. With 10 years of water injection, the damage zone radius is much higher for a bigger initial filtration coefficient. However, there is an optimal initial filtration coefficient to obtain the longest damage time. The maximum retention capacity has a significant impact on the damage zone radius. The smaller the maximum retention capacity, the larger the damage zone radius and the shorter the damage time. The novelty of this study is that an axisymmetric suspension flow model based on Langmuirian blocking is established and a method of quantitatively evaluating the particle retention-caused formation damage is obtained. Based on this method, the influences of TSS in injected water, rate of injection, initial filtration coefficient and maximum formation retention capacity on the damage zone radius and damage time are investigated. The proposed guideline and workflow for water injection parameter control can be a reference for designing of waterflooding scenarios in a matrix-type reservoir. The prediction results of the damage zone radius will also be a reference for acidizing job design.
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Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».