How to Avoid the Ditch When Trying to Find and Develop Oil and Gas Internationally
Notice bibliographique
Résumé
The Allure and the Unfamiliar Risks The allure for Canadian-based oil companies to expand their exploration and development activities into the international arena is easy to understand-the Western Canadian basin is a fiercely competitive environment, where the conventional oil and gas pools being discovered continue to get smaller. Other hydrocarbon regions of the world are typically much less explored, and offer the potential for new and larger conventional opportunities. One of the trade-offs in "going international," however, is that the management of some unfamiliar risks suddenly becomes key to project success. Important decisions can be made by default by the investor or manager when the risks are not adequately understood. It has been my observation that international ventures often fail for reasons that were not anticipated by the participants, but could have been. I interviewed some experts on this topic, and the most cited risks were in the category of cultural differences, and relations with the host government and/or national oil company (NOC). In the Canadian oil and gas industry, our success depends largely on how efficiently and effectively we can find, develop, and produce oil and gas. The quality of our relationship with government and regulatory bodies is a secondary focus in Canada, and we also largely take for granted the tremendous access to data that we have. Some Ideas as a Starting Point I have some references towards the end of the article for further reading, but here are some risks that are accentuated when working internationally, along with some mitigating advice. Risk Category A: Project Selection and Data PhaseAlthough you're doing a great job of managing the risks in the project you've got, you didn't pick the right project.Understand your company's niche (considering skills, knowledge, and financial strength), and find a project where that niche is applicable. Do your homework, get the data, and involve the right people in the evaluation. This is when you have the most leverage. In later stages of the project, your ability to make major changes decreases.You have only limited access to data when selecting the project, and get nasty subsequent surprises. Once you get full permission to access data, it still takes years for it to be in your hands, and you're still making decisions with partial data sets.Recognize that data will be much harder to come by than in Canada, allow enough time and resources to gather the necessary data, and build the necessary relationships with the data custodians.You get into a new area and don't know your way around, don't know the rules of the game, don't know the key players, and spend a lot of money learning things the hard way.Knowledge implies focus. If you're new to an area, either:partner with someone more experienced,get low cost entry and build slowly, orspend time and money to build knowledge (including hiring experienced personnel).There are multiple sources of data-use them all (competitors, government, service companies, legal and accounting firms, etc.). Do your homework.
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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 | 0,022 | 0,064 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,031 | 0,022 |
| Communication savante | 0,021 | 0,034 |
| Science ouverte | 0,004 | 0,014 |
| Intégrité de la recherche | 0,012 | 0,020 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,014 | 0,009 |
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 ».