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Abstract The deepwater operational environment worldwide poses a number of key challenges in the areas of real-time data accessibility, logistics, personnel skill assessment and training, and equipment maintenance, as well as heightened health, safety, and environment (HSE) requirements. A key to quality service delivery is to reduce or even eliminate costly incident and downtime by improving job planning and preparation, which heavily relies on the accuracy and timely availability of field data, and the ability to collaborate with onshore experts by the field crews. A rig-centered digital platform was developed that offers the following key features: reliable network connectivity; real-time data sharing across the globe; job monitoring via video and remote human-machine interface (or HMI, the computerized application interface for executing field jobs and acquiring operational data) viewing; field crew and onshore expert collaboration by chat, file sharing, and voice-over-Internet protocol (VOIP); on-rig asset tracking and reporting; mobile application for job workflow management; seamless two-way data exchange between field and corporate data center; and business continuity via offline operations support for an intermittent connectivity environment. The solution applied the best industry practices and cutting-edge digital technologies to provide a reliable, flexible, and secure platform for the best possible team collaboration practices, together with key improvements in processes, tools, and job workflows from both the operations and the maintenance sides. Pilot projects were launched at various offshore operations and insightful data were collected. Benefits such as improved decision making—anytime, anywhere—by enhanced collaboration, improved speed reacting to abnormal events, crew reduction, less exposure to HSE risks and downtime, and adherence to the best and most up-to-date service provider and industry practices, among other advancements, were achieved.
Abstract The upstream oil and gas industry requires a diverse set of political, personnel, mechanical, and technological capabilities as it possesses innumerable and voluminous data from seismic, drilling, completion, and production. In this competitive field, technical data mining and analysis are key to the creation of intelligent oilfields. However, there are major challenges associated with the generation and consumption of data in intelligent oil and gas fields, including the acquisition, storage, classification, transformation, visualization, and analysis of data. A service company's technical data mining application platform that has built-in analytical tools should aid field engineers in the retrieval of relevant data, as well as the analysis of data for their own requirements. Such an application, when combined with live notification capabilities, can help improve the operational productivity and lessen time lost during a job failure or any other events contributing to nonproductive time (NPT). It also would help standardize the measurement of key performance indicators across different areas or regions. Continuous surveillance and monitoring of wells, which are the basis for intelligent oilfields, help improve productivity and reduce operating costs. This paper discusses one service company's state-of-the-art application for big data archiving algorithms and practices that are distinctive for improving data mining in intelligent oilfields. This application acts as an enabler for extracting relevant information to improve predictive models, making more reliable decisions, and, ultimately, sustaining existing business and creating new business opportunities.
Abstract Chevron has a longstanding association with the use of dedicated operations centers to support drilling operations. This dates back to the pioneering work of Tenneco in the early 80's, one of a few First Generation Drilling Operations Centers (Booth, 2009). After the acquisition of Tenneco in 1988, Chevron built upon this prior experience in developing a sophisticated support center intended for use throughout Chevron's global drilling operations. As with most of the first generation centers, reduction in drilling activity changed the business case and the strategy was curtailed in 1992. More recently, in 2004, Chevron established a Well Design Execution and Collaboration Center (WellDECC) to support high-cost technically challenging deep water operations in the Gulf of Mexico. With recent and planned changes in drilling strategies, including the prospect of supporting multiple rig onshore operations both domestic and international, Chevron is embarking on an updated strategy which will institutionalize access to and use of realtime drilling data on a global basis. This includes establishing a central facility staffed by Chevron personnel and operating on a 24/7 basis to monitor the acquisition of data and its integration with technical and operational work processes. This strategy will benefit from the experience derived from the earlier efforts mentioned above. It will also take advantage of significant subsequent advances in information technology and the development and broad implementation of the WITSML industry standard for exchange of data between the multiple parties typically involved in the drilling and completion of a well. This paper describes the strategy's underlying principles and provides information on the design and implementation of an appropriate solution.
Abstract Objectives/Scope Supply chain optimization is now an imperative for corporations, unfortunately existing track and trace functionality has not been previously available to cover the end to end supply chain. This is especially true in the Oil & Gas industry which is hampered by poor visibility of assets and equipment affected by onshore and offshore locations, large lay down yards and harsh environments. Historically, one of the greatest impediments to a complete solution has been the varied proprietary active tagging systems that do not allow for interoperability. Methods, Procedures, Process Unlike Passive RFID, which has been based on a universally accepted standard protocol, Active RFID has been based primarily on proprietary protocols. As a result, Active RFID systems have been highly expensive and inflexible. This has driven industry leading companies to express their support for an interoperability standard, similar to the EPC standard for passive RFID. The IEEE 802.15.4 standard, has risen to the top of that list. Specifically developed for active RFID, and based on Wi-Fi, this standard promotes interoperability for asset tracking using active RFID based tags and systems. Driving the movement forward are new products such as the first (and only) intrinsically safe, dual technology tag – IEEE based active and passive RFID. This dual technology results in quickly locating the area of the asset as well as locating the specific item among a stack of like items. Results, Observations, Conclusions The acceptance of the IEEE 802.15.4 open standard for active RFID will encourage innovation and product interoperability that customers have been demanding and will ultimately benefit them by offering a choice of providers and thus eliminating licensing fees and legacy encumbrances, and unreliable technical performance. While end users will realize lower overall costs associated with implementing an active solution, manufacturers will benefit from the lower entry to market which will lead to the greater acceptance of active RFID across the marketplace.
How Do We Accelerate Uptake and Fulfill the Value Potential of Intelligent Energy? Summary The objective of this paper is to identify ways to accelerate the uptake and fulfill the value potential of Intelligent Energy (IE). The paper is coauthored by a cross-industry group drawn from operators, service providers, and product vendors, all of whom have been involved in the IE arena for 10 years or more. We have analyzed past experiences to identify both ways in which IE has been successful and the improvements that could be made to add value across a broader scale amid the challenges of today's commercial environment. In this paper, assessments are given on IE implementations to identify practical ways in which we can expand deployment and deliver results more quickly, including the importance of collaboration and competition in the IE domain, and how longer-term business models and new organizational ideas could improve the industry's uptake of IE. We have identified two areas in which we believe changes to our approach could deliver significant benefits--through the expanded use of integrated work flows and shared subject-matter-expert (SME) services. We discuss the benefits and challenges of this integrated approach to solution design, work processes, technology, skills, and competencies. Field cases from two major operators are given as best-practice examples on advanced use of IE in the oiland-gas industry. Introduction After more than 10 years of IE initiatives, the industry has increasingly published lessons learned from the early years (e.g., Lilleng et al. 2012; de Best and van den Berg 2012; Dickens et al. 2012; Dhubaiki et al. 2013; Lochmann and Brown 2014; Gilman and Nordtvedt 2014). As IE moves into its second decade, the landscape is changing. The decline in oil price, the resulting pressure on costs, and the rise of unconventionals are just some of the changes that present both risks and opportunities for IE to flourish (Pickering and Sengupta 2015). IE solutions during the first decade focused mainly on new technologies, better use of real-time data, new applications to analyze and visualize data, improving the data foundation, and increasing collaboration. Frequently, this has led to an increase in operational complexity with an associated increase in personnel. The financial climate allowed (or perhaps encouraged) us to work in this way, because the high oil price meant that the greatest benefits came from increasing production rather than cutting costs, and adding personnel made sense if they could deliver increased production. Most operators took a technology-driven, functional approach to provide us with improved surveillance, analysis, and collaboration tools. This has driven us mostly toward developing better tools to improve existing work processes.