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The E&P industry is rich in all types of data. Without proper database and analytics, companies are not able to retrieve and analyze the data they need in an efficient way. The result of the data management problems is that decisions are often made using incomplete or incorrect information. Even when the desired data is accessible, requirements for gathering and formatting it may limit the amount of analysis performed before a timely decision must be made. Strong data management is required to transform wells-related data into an integrated system of information. The key to successful data management is in the use of sophisticated platform-independent codes that doesn't need any special setup or systems which allows easy transfer of information and data over the internet. This paper describes the data management and accompanying analytics approach taken in support of operations in Egypt to provide a shared knowledge system. This innovative cloud application provides a common interface to multiple systems in the organization, allowing a richer and more complete source of data to be used for decision making. Moreover, it enables the integration of static data, such as well logs in a particular region, with a real-time system to facilitate integrative real-time analyses using artificial intelligence, cloud-hosted physics-based simulators, or both. To support deepwater needs such as those in Egypt, the system incorporates productivity optimization analysis, reservoir geomechanics (pore pressure prediction, log interpretation, reservoir collapse, fault activation, subsidence, compaction, etc.), and data mining of key development uncertainty and well performance drivers.
Mounir et al. (Tue,) studied this question.