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Whenever a company is involved in divesting or acquiring oil and gas assets, whether they are exploration ventures, appraisal opportunities or field developments, it is almost certain that a data room will be involved. Setting up a data room requires as much forethought and planning as
attending one. If the attention to detail is lacking, from either the seller or the buyer, then the data room will not achieve its objective and the potential deal may not only be delayed, it may not occur at all.
This course aims to provide E&P professionals and stakeholders in oil and gas investment sector with an understanding of how to get the most out of data rooms in order to put a reasonable evaluation in front of the decision makers in the shortest timeframe possible. Learning objectives are at knowledge and application levels and participants will take away workflows to streamline their data room processes, to ensure essential data are gathered, and to quickly evaluate opportunities while avoiding some of the pitfalls that exist in all assessments of oil and gas opportunities.
• Organizational Decision Processes.
• Overview of the data rooms: a means of providing and acquiring data.
• Data rooms and why they are important.
• Physical data rooms vs. virtual data rooms - access, timing and cost issues.
• Data room framework, from the perspective of the seller and the buyer.
• Data room management – getting the appropriate data for a competent evaluation including
development of data check lists.
• Selecting the data room team.
• What each member of the team should do before, during and after the data room.
• Asset targeting.
• Initial screening techniques.
• Data analysis considerations – prioritizing data, ensuring data validity and comparison to analogues.
• General data room content and structure tips.
• Key project related valuation areas.
• The need for uncertainty and how to recognize and avoid bias.
• Rapid asset evaluation - how to make short cuts while avoiding pitfalls.
• Calculating better estimates of hydrocarbon-in-place.
• Recovery factors.
• Creating production profiles.
• Well requirements for different scenarios.
• Petroleum agreements.
• Time Value of Money.
• Economic Indicators.
• Risk Analysis.
• Project enhancement, vulnerability and risk.
• Project Evaluation.
Scientist and engineers who deal with big data and data room management
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