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Enregistrement W2471536349 · doi:10.2523/86685-ms

North Caspian Project - Challenges and Successes

2004· article· en· W2471536349 sur OpenAlexaboutno aff
Sarybekova Lyazzat

Notice bibliographique

RevueProceedings of SPE International Conference on Health, Safety, and Environment in Oil and Gas Exploration and Production · 2004
Typearticle
Langueen
DomaineEngineering
ThématiqueReservoir Engineering and Simulation Methods
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésCitationSustainabilityExhibitionBusinessComputer scienceLibrary scienceGeographyArchaeologyEcology

Résumé

récupéré en direct d'OpenAlex

North Caspian Project - Challenges and Successes Lyazzat Sarybekova Lyazzat Sarybekova Agip Kazakhstan Noth Caspian Operating Company, NV Search for other works by this author on: This Site Google Scholar Paper presented at the SPE International Conference on Health, Safety, and Environment in Oil and Gas Exploration and Production, Calgary, Alberta, Canada, March 2004. Paper Number: SPE-86685-MS https://doi.org/10.2118/86685-MS Published: March 29 2004 Connected Content Related to: North Caspian Project: Challenges and Successes Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Sarybekova, Lyazzat. "North Caspian Project - Challenges and Successes." Paper presented at the SPE International Conference on Health, Safety, and Environment in Oil and Gas Exploration and Production, Calgary, Alberta, Canada, March 2004. doi: https://doi.org/10.2118/86685-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search Dropdown Menu nav search search input Search input auto suggest search filter All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE International Conference and Exhibition on Health, Safety, Environment, and Sustainability Search Advanced Search AbstractOil & gas projects operating under extremely challenging circumstances or in the world's most sensitive environments are not a rarity. There are many examples where industry has successfully addressed such issues as unfavourable reservoir properties, lack of infrastructure, limited access, cold or hot climate, demanding regulatory requirements and unsympathetic public. Over the recent years industry aggressively developed and improved technologies and techniques that allow companies to significantly minimise the environmental impact of their operations and, thus, carry out projects in many areas with sensitive, vitally important or highly protected ecosystems. However, there are not many projects where most of the above mentioned challenges are present all at once.The development of Kashagan field in Kazakhstan sector of North Caspian Sea is one of the biggest and the most challenging development projects worldwide, uniqueness of which lies in the complexity and rarity of a blend of issues requiring consideration. It starts with the properties of the field such as geology, pressure, temperature, H2S content. Then there is a number of physical conditions within the area of operations such as shallow waters, sea level changes, extreme temperatures in winter and summer seasons, and ice. Shallow waters and wetlands of North Caspian support important number of bird and fish species, including rare and internationally protected, and Kazakhstan enforces high environmental standards to ensure adequate protection for the area.Agip Kazakhstan North Caspian Operating Company (Agip KCO), an Eni company operating on behalf of six international co-venturers, has the luxury and opportunity to draw on experience and resources that its founders acquired internationally. This paper describes some engineering solutions and operating methods as well as other protection measures employed by the Company to ensure maximum safety of its operations to the environment. Successes and lessons from this project may prove to be valuable throughout a wide sector of industry.IntroductionAgip KCO is an Eni Group company exploring and appraising several offshore oil and gas prospects and fields in the Kazakhstan sector of the North Caspian Sea, but the main focus of its present activities is the Kashagan oil field.Kashagan Field lies offshore approximately 75 km south of the Ural river delta in the water depth of about 4 meters.The field is enormous and covers an area of about 820 km2. Its estimated recoverable reserves are more than 7 billion barrels. Other features of the field include high pressure in reservoir (800 bar) and significant hydrogen sulphide levels (range 15–18%) in the reservoir fluids.The development of Kashagan will take place in multiple phases. The first phase, known as the Experimental Programme, will include construction of drilling islands, processing hub, an onshore processing facility and support utilities, pipelines for transporting oil and gas from the field to shore.Experimental Programme will be followed by the Full Field Development phase(s) which will require additional offshore facilities as well as the expansion of onshore facilities. Data gained from the first phase will be used to adjust the strategies and plans for the following phases. Keywords: society of petroleum engineers, lyazzat sarybekova, reservoir characterization, caspian, marine environment, knowledge management, upstream oil & gas, operation, agip kco, programme Subjects: Reservoir Characterization, Environment, Information Management and Systems, Seismic processing and interpretation, Knowledge management This content is only available via PDF. 2004. Society of Petroleum Engineers You can access this article if you purchase or spend a download.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Autre devis · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,959
Score d'incertitude au seuil0,455

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,067
Tête enseignante GPT0,288
Écart entre enseignants0,221 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeAutre devis
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2004
Routes d'admission1
Résumé présentoui

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Même revueProceedings of SPE International Conference on Health, Safety, and Environment in Oil and Gas Exploration and ProductionMême sujetReservoir Engineering and Simulation MethodsTravaux en français237 207