Integrated Risk Analysis for Scale Management in Deepwater Developments
Notice bibliographique
Résumé
Summary Owing to the increased cost of scale management in subsea developments, compared with platform or onshore fields, and because of the more-limited opportunities for interventions, it is becoming increasingly important to carry out a risk-analysis process for scale management as early as possible in the field-development plan. This process involves identifying the potential scale risks and analyzing and comparing the options available for managing those risks. This paper discusses how this risk-analysis process should be carried out, with a strong emphasis on the need to integrate all the available production-chemistry and reservoir-engineering data. To demonstrate this process, an example is used from a development complex that lies in water depths greater than 400 m (greater than 1,300 ft) offshore west Africa. The process involves the following steps: Analysis of available brine samples to identify maximum scaling potential. Laboratory testing of available scale inhibitors to identify chemistry best suited to this system. Study of analog fields to identify scaling risks in these fields, and how these risks have been managed, with implications for fields currently being studied. Modification of full-field reservoir-simulation model to predict seawater breakthrough and duration of seawater production to identify when and for how long the wells would require to be treated to control scale and how much inhibitor would be needed. This process involves using flow profiles derived from the reservoir-simulation model and applying them in a near-well squeeze simulator to predict treatment performance in terms of time taken for return concentrations to decrease to the minimum inhibitor concentration determined by laboratory studies. Well-by-well analysis of predicted seawater-production profiles and total-water production rates to identify the potential for correct placement of inhibitor by bullhead treatments in zones at risk of scale deposition. Modification of reservoir model to study the impact of in-situ scale deposition on brine chemistry at the production wells and the revision of requirements for inhibitor squeeze treatments. Economic analysis of options available for scale management comparing sulfate reduction to inhibitor squeezing on the basis of the treatment specifications identified above. The result of this process in the reservoirs in question, which have a moderate-to-severe scaling tendency, has been to demonstrate that inhibitor placement by bullheading would result in satisfactory placement for all wells. If the assumption is made that no scale deposition takes place in the reservoir, then sulfate reduction becomes a viable option, owing to the requirement of regular treatments and relatively high chemical concentrations. However, taking into account cation losses, owing to scale deposition deep within the reservoir, the requirements for chemical treatments reduce and squeezing becomes the preferred option. From the simulation models, differences between the reservoirs concerned, in terms of the contribution aquifer waters make to scale control, were identified with some wells at much higher risk than others owing to the volumes of potentially scaling brines that are expected to be produced. This paper clearly demonstrates that a cross-discipline approach using reservoir engineering, production chemistry, and completion engineering can lead to a more-complete assessment of the scale risk and the correct economic selection of the control program.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,006 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,004 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 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 ».