--> Abstract: Integration of Well Data Management Processes in a Diverse Data Environment, by Al Kok and David Li; #90105 (2010)

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AAPG GEO 2010 Middle East
Geoscience Conference & Exhibition
Innovative Geoscience Solutions – Meeting Hydrocarbon Demand in Changing Times
March 7-10, 2010 – Manama, Bahrain

Integration of Well Data Management Processes in a Diverse Data Environment

Al Kok1; David Li1

(1) Exploration Technical Services Department, Saudi Aramco, Dhahran, Saudi Arabia.

Data management is becoming increasingly critical as E&P companies are expanding their capabilities to keep pace with world energy demands. As data management becomes more critical, it is also becoming more difficult to manage and disseminate the significant increase in volumes and complexity of the E&P data. In addition, in a large company like Saudi Aramco, managing data in a diverse data environment with multiple data producers presents significant challenges related to data standards, completeness, quality and timeliness. These data integrity and availability issues can quite often undermine the confidence in the data and data management effort.

The integration of well data management processes is essential for ensuring data completeness, quality and timeliness in a diverse data environment. It is also essential for ensuring accurate data can be delivered to geoscientists in a timely manner. Included in the presentation is the methodology for the integration of well data management processes and standardization at Saudi Aramco for enhancing the quality, completeness and timeliness of geological and drilling engineering data in the corporate repositories.

The integration methodology to be presented begins with the understanding of the root causes of the problems related to data quality, completeness and timeliness of geological and drilling engineering data. The effective collaboration necessary between the stakeholders is essential. The integration process is achieved through establishing data standards, a thorough understanding of the data flow, the roles and responsibilities of the stakeholders, the data management requirements for data quality, completeness and timeliness as well as the technology required. All these will be presented along with the successes achieved through automation, productivity gains and benefits.