Utilizing CO2-Resistant Self-Healing Cement System for Gas Wells: A Case History from East Malaysia
Notice bibliographique
Résumé
Abstract Three offshore development gas wells were drilled in East Malaysia. The reservoir zones were identified to potentially contain high levels of carbon dioxide (CO2), as well as given the potential to be utilize as CCS wells. CO2 is corrosive and may cause degradation of the cement sheath, compromising well integrity. This paper presents the decision process for selecting a suitable cement system, as well as the execution, evaluation, and improvement results applied to the three wells. The operator was committed to ensuring safer operations over the lifespan of the well by maintaining long-term well integrity. Degradation of conventional Portland cement due to the corrosive effects of CO2 can result in compromised cement sheaths, leading to reduced gas production rates and serious environmental hazards. Implementing the appropriate technology requires well-structured planning. To achieve consistent blending of the innovative self-healing CO2-resistant cement, a series of quality control procedures were established, supported by thorough laboratory testing and comprehensive management of the blend lifecycle. Due to its superior mechanical properties and self-healing capabilities, the operator opted to use a novel self-healing CO2-resistant (SHCR) cement system for the gas field development. Blend homogeneity was maintained throughout the transfer process from the bulk plant to the sea vessel and then to the offshore rig, with minimal changes in specific gravity and blend composition between samples from the bulk plant and those collected at the rig. Several key logistical challenges were addressed to ensure successful delivery, including the complexities of offshore operations, job frequency, and handling requirements, as well as the setting of custom equipment specific to this rig. These challenges were effectively managed through quality control and improvement processes developed during the campaign. This paper shares lessons learned from the execution and evaluation methods deployed. Ultimately, cementing operations were successfully completed without incidents using conventional equipment. Moderate to good cement bonding was achieved across the target zones, enabling the rig to proceed with perforation, well testing, and production operations. Because of its superior mechanical properties and self-repair capabilities when exposed to CO2-containing fluids, this innovative system is highly effective in maintaining zonal isolation and ensuring long-term well integrity. Additionally, this technology is applicable in any field globally where CO2 regulation is enforced and safety risks exist for the operators or the public. It also enables operators to adopt proven processes for successful operations, leveraging insights gained from meticulous planning, implementation, and lessons learned.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».