Managing and Optimizing Massive and Interactive Geosciences Data to Improve Productivity for Better Decision Making
Authors: Al-Habib M. , Badar M. H. , Al-Ghamdi T. A. 
Published: February 2017

Abstract
Outputs from geological and geophysical applications are the major drivers for upstream prospect generation and field development. The current generation of applications can quickly produce a massive amount of intermediate data based on the iterative and interactive workflows. One major challenge for large organizations, with many disparate software systems and a large user base, is maintaining a clean and optimized data environment. Data management plays a key role in the delivery of accurate and efficient interpretation results to improve the decision making and exploration success. This case study shares the authors’ experience in leading corporate and project-based geoscience data management activities for several industry-leading applications.
The first activity was the data cleaning, standardization, and consolidation of over a 100 repositories of multiuser project-based application databases that had accumulated over 20 years. The objective for each step (data cleaning, standardization, and consolidation) was clearly defined and the processes have been implemented using best technologies. Automatic procedures have been implemented to optimize the master and interpretation data. In addition, this paper addresses the application of knowledge management methodologies, to transform existing geoscience interpretation workflows into a knowledge-based asset management system. We present the business drivers for each activity, challenges faced, and the approach adopted to resolve those challenges.
During the data management activity, many of the project databases need to remain active for ongoing well planning, monitoring, and geosteering, which make data management more challenging. New naming conventions were also established and enforced. These provided a larger than expected benefit to the users, in terms of data accuracy and availability. One sizeable operational database achieved around 55% clean up from projects’ archival and deletion. It it because projects are either not active anymore or merged with other projects. Geophysical interpretation has become an iterative, interactive, and resource intensive process. It generates massive amounts of maps and volume-based attribute data, resulting in significantly increased storage utilization and data complexity. The major challenges were to identify and extract the best available interpretation version, streamline the data flow, and leverage existing corporate knowledge. All challenges were tackled successfully, bringing a huge benefit to the organization. The creation of new processes, awareness, standards enforcement, and automation guided geoscientists toward the best data management practices. Benefits in reducing operational costs and improving productivity have been realized.
Innovative approaches utilized in our activities include knowledge management methodologies, automatic procedures implementation for data management and optimization. In addition, a continuous reporting mechanism was established to assure complete control and monitoring of data growth. This paper also provides a roadmap that can be applied to similar data management activities in the geoscience domain. Data management has been transformed into a continuous process, rather than a one-time task.