The Digital Oil Field (DOF) has been exhaustively discussed for production enhancement and optimization, but there has been little focus on its use in other areas. This paper describes an integrated approach by multiple business units on how data management and visualization is been applied to enhance decision making, improve cost control, and increase asset integrity in Murphy’s onshore and offshore developments. Data visualization and the automation of data reporting play an important role in achieving the goal of reducing OPEX and optimizing field operation activities. As more data becomes available, a tool for maximizing the benefits of how data is presented and used in day-to-day decision making is required. This begins with reducing man-hours associated with data acquisition, report-generation, analytical tool development and key performance indicator (KPI) tracking. A data management and visualization tool is currently in-use to enhance offshore operations in chemical management, cost-tracking, and production forecasting, as well as unconventional onshore operations for asset integrity monitoring systems. Since implementation, the program minimizes duplicate work by field personnel, as well as ensures they are engaged and involved in OPEX reduction and increasing field uptime. Effective visualization of data streamlines decision-making on chemical performance, cost-benefit analysis, and effective treatment. It also maximizes the amount of data available for use and interpretation. In remote areas onshore field data is entered via mobile devices, providing a fast, simple, and effective tool for managing onshore maintenance campaigns, pigging programs, cathodic protection, & vessel inspections. New workflows provide real-time data and metrics to help make on the fly ‘fit-for-purpose’ decisions. Utilization of apps and dashboards has drastically changed the performance of the asset integrity & maintenance programs and significantly reduced OPEX across onshore and offshore assets, and improves reliability across pipeline and gathering systems by identifying high-risk areas and reducing system upsets. This shift has moved focus from effective data collection to using the existing data in an efficient and cost-effective way in helping the operations engineering team and field operations in data analysis, KPI-tracking and achieving production and OPEX targets. It also provides indication of existing data gaps and identifies where more data collection would add value to business decisions.
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