Management: Engineering Workflows Herald a New Era for Upstream Production
- Kemal Farid (Merrick Systems) | Jose A. Alvarez (Merrick Systems)
- Document ID
- Society of Petroleum Engineers
- Journal of Petroleum Technology
- Publication Date
- October 2006
- Document Type
- Journal Paper
- 36 - 37
- 2006. Copyright is retained by the author. This document is distributed by SPE with the permission of the author. Contact the author for permission to use material from this document.
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Over the last decade, a number of industries have improved their operations through workflow management—the management and improvement of data and activities through specific business, scientific, or engineering processes. Workflow management most commonly has been associated with business or back-office processes, where workflow-management systems have enabled improvements to productivity in tasks such as invoice processing, authority-for-expenditure management, and technical help-desk operations.
In recent years, several industries have begun focusing on scientific and engineering workflows that differ in many ways from business workflows. A new generation of software tools is emerging to manage engineering work-flows in the upstream production domain. These tools will enable many of the promises of the “digital oil field” and are part of the answer to industry challenges such as the “graying” of the workforce, the increasing complexity of assets, and the need to optimize production operations.
Types of Workflows
Business workflows are the most common type employed by companies. The management of business workflows dates back to the 1970s, when workflows were purely paper based. As workflow management evolved to modern information technology systems, many industries re-engineered their business processes for increased efficiencies and lowered transaction costs for optimal performance. Workflow-management software became commonly used to implement improved workflows and integrate business processes that spanned multiple workers and multiple information technology systems.
Scientific workflows gained wide acceptance in the field of bioinformatics in the early 2000s. Scientific and engineering workflows differ from business workflows. For example, where business workflows tend to deal with discrete transactions, engineering and scientific work-flows tend to deal with large data quantities, multiple data sources in multiple formats, and multiple interconnected tools. New software tools can be used to standardize engineering workflows by bringing together data from disparate systems and consolidating separate engineering capabilities within a single platform.
New workflows are needed for production operations. The aging of the oilfield workforce means experience will be lost when older workers retire, and new workers will need to accomplish the same work with less learned knowledge. The automation of engineering processes allows fewer workers to manage the same assets and allows knowledge to be transferred in the form of documented workflows. The increasing complexity of operations requires the management of larger data sets for ongoing operations, more precise decision making, and the opportunity for optimization through controls. New engineering workflows are needed to meet all these challenges, and they must be implemented predictably across multiple assets.
That will change engineering and operations in the upstream production arena. Engineering workflow systems can enable new capabilities for production surveillance through the use of automation and integration of modeling tools with multiple data sources, such as Merrick Systems’ workflows.
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