Search citation statements
Paper Sections
Citation Types
Year Published
Publication Types
Relationship
Authors
Journals
In model based oil field operations, engineers rely on simulations (and hence simulation models) to make important operational decisions on a daily basis. Three problems that are commonly encountered in such operations are: on-demand access to information, integrated view of information, and knowledge management. The first two problems of on-demand access and information integration arise because a number of different kinds of simulation models are created and used. Since these models are created by different processes and people, the same information could be represented differently across models. A unified view of the models and their simulations is desirable for decision making, and thus the necessity for information integration. Knowledge management refers to a systematic way to capture the rationale (knowledge) behind the various analyses performed by an engineer and decisions taken based on the analyses. It is critical to capture this knowledge for auditing, archiving, and training purposes. In this paper, we propose the application of semantic web technologies to address these problems. The key elements of the semantic web approach are the ontologies or the information schemas that model various elements from the domain, and a knowledge base (KB) which is a central repository of the instance information in the system. We present a modular approach for organizing the ontologies and outline the process that was followed to define the ontologies. We also describe the workflow that was used to populate the KB and briefly discuss some of our prototype applications that address the problems mentioned above. Based on our experience, semantic web technologies appear to be a highly promising approach to deal with these information management issues in the oilfield domain, although performance and tool support remain the key areas of concern at this stage.
In model based oil field operations, engineers rely on simulations (and hence simulation models) to make important operational decisions on a daily basis. Three problems that are commonly encountered in such operations are: on-demand access to information, integrated view of information, and knowledge management. The first two problems of on-demand access and information integration arise because a number of different kinds of simulation models are created and used. Since these models are created by different processes and people, the same information could be represented differently across models. A unified view of the models and their simulations is desirable for decision making, and thus the necessity for information integration. Knowledge management refers to a systematic way to capture the rationale (knowledge) behind the various analyses performed by an engineer and decisions taken based on the analyses. It is critical to capture this knowledge for auditing, archiving, and training purposes. In this paper, we propose the application of semantic web technologies to address these problems. The key elements of the semantic web approach are the ontologies or the information schemas that model various elements from the domain, and a knowledge base (KB) which is a central repository of the instance information in the system. We present a modular approach for organizing the ontologies and outline the process that was followed to define the ontologies. We also describe the workflow that was used to populate the KB and briefly discuss some of our prototype applications that address the problems mentioned above. Based on our experience, semantic web technologies appear to be a highly promising approach to deal with these information management issues in the oilfield domain, although performance and tool support remain the key areas of concern at this stage.
With the ever increasing complexity of upstream oilfield operations, it has long been recognized that there is a serious need for capturing, communicating, analyzing, and using real-time information for better decision making, improving safety and reducing the operational cost of the oilfield operations. During the last two decades, the use of information technology for advanced services such as wireless, voice, and video communication plus advanced algorithms for data cleansing, data mining, data-driven analytics have changed the landscape for many international and national oil companies. These types of enhancements can lead to an increase in efficiencies when all stakeholders in an organization can access networked applications and services anywhere at any time, Figure 1. Although the need for smart oil field technology was long recognized, the development of smart oil field tools did not keep pace with the increased complexity or the availability of large amounts of data. Even when these tools became available, there was a reticence to immediately utilize them. Managing the required organizational and cultural changes required to effectively deploy and apply smart oilfield technologies has been a challenge. But the key to success has been upper management resolve to utilize increased flows of information and work processes redesign to reduce operating costs and increase capital efficiency. Development and deployment of advanced technologies require a blend of information science expertise and domain knowledge in oilfield operations. Forming and successfully managing a strategic alliance between industry and universities can be an effective solution to forming a hub for critical technology development, and also preparing digital oilfield engineers to expedite deployment. This paper presents an analysis of a more than a decade of advances in smart oilfield technologies with examples of tools and techniques developed at USC Center for Interactive Smart Oilfield Technologies (CiSoft).). This globally unique strategic alliance (www.cisoft.usc.edu) was initiated in 2003 as an extended education and research partnership with the Chevron Corporation to build new capabilities, academic degree programs, and technology advancements for the first generation of digital oilfields. Through the unique collaborative efforts of USC researchers from information technology and petroleum engineering, smart working solutions have been developed to advance the cause of oilfield safety, efficiency, and enhanced economics using intelligent algorithms and tools. The success of the Center has been the development of innovative workflow processes addressing how typical human intensive oilfield monitoring and control can be transformed into solutions that can reduce failures, substantially enhance raw and interpreted data access, and help in engineering decision making with innovative machine learning algorithms. The alliance has included efforts of 180 Ph.D. students, producing 160 publications, over 50 inventions and 40 patents in a decade time. Many of these publications are source materials that can be used for development of organized courses and training programs on smart oilfield technologies. Topics discussed include the working model for this alliance, research management process, an educational component and a new dimension of the Center to commercialize certain technologies through service companies. Technologies already patented are discussed in the technical papers listed in the reference section. Focus on many projects has been on preventing failures and for lowering operational cost. Best practices and lessons learned from formation and operation of CiSoft can serve as effective ways for establishing more similar strategic partnerships between the industry and academia.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.