bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predictive Asset Maintenance
Authors: Kingsley Eliot 
Published: March 2012

Abstract

Predictive Asset Maintenance - The Business Challenge
Asset intensive industries such as Energy, Oil & Gas are continuously challenged to mitigate the risk of equipment failure to avoid unplanned costs, impacts on production, safety and environmental implications. It is a constant battle to balance the cost of preventative maintenance measures against the risk of equipment failures.

Predictive Analytics – A ‘Game Changing’ Capability
Predictive analytics is the application of powerful statistical modelling techniques to derive forward-looking ‘strategic actionable insights’ from historical data, as well as being capable of providing real-time ‘decision support insights’ on specific equipment.
It is applied to best advantage by mining multiple disparate data sources such as performance logs, sensor data, incident data, financial data, text based maintenance logs, human resources data and environmental data.
This paper describes an approach to: Accurately predict which subtle combinations of characteristics tend to lead to increased frequency of failures.Unearth patterns in maintenance operations over time that could point to opportunities for improvements.Identify the characteristics that tend to increase ownership cost and downtime over the life of a system.Predict what parts are likely to fail in the near future.Identify ‘at risk’ parts that have not yet failed so that they can be replaced just-in-time to avoid unscheduled downtime due to failure.Mine thousands of text based logs that describe the maintenance performed on systems to determine what important observations are being logged by the maintenance team.

Key Benefits
■ Scheduled maintenance can be adjusted and optimised on a dynamic basis so as to maximise equipment availability and avoid equipment failure. ■ Costly unnecessary maintenance can be avoided. ■ Maintenance resources can be deployed in an optimal fashion. ■ Analytical insights can be used to improve equipment design and maintainability.
Smart Oil and the Extended Enterprise
Authors: Forbes Peter 
Published: March 2012

Abstract
Following the successful paper "Smart Oil and the Development of the Networked Organisation", Chapman and Forbes 2010, SPE 128452 this paper goes beyond the Networked Organisation to explore the role of suppliers and partners in the extended enterprise. To date oil and gas organisations have implemented a number of intelligent energy solutions within their own organisations, the next logical step is to extend these into supplier and partner organisations, the extended enterprise.
Global integration and smart oil will require both technology, and further significant people, process and organisational change to make it successful. The extended enterprise will raise new challenges such as sharing information across company boundaries and compensation for services. This paper examines the challenges specific to supplier and partner collaboration and the latest thinking on: ■How do business processes need to change in the extended enterprise and how can intelligent energy solutions speed up execution of these processes?■How do supplier and partner relationships need to change in the extended enterprise?■How do you extend expertise leverage and community based working outside your organization into the extended enterprise?■What are the practical problems and how can they be overcome?■Have other industries addressed these challenges and what can be learnt from them?
Modular Procedural Automation Innovation for Upstream Processes
Authors: Wilkins Maurice J. , Lazok Steve 
Published: March 2012

Abstract
This paper explores a specific area of the upstream transformation innovation stage. Innovated new ways of increasing production and operation efficiency can be achieved from solutions developed in other industries. Energy companies have begun the innovation stage of deploying modular procedural automation (MPA) at on-shore oil/gas fields and at off-shore production platforms. The basis of MPA, its growth and development will be explained and upstream solutions that are occurring today will be introduced.
Cross-Industry Perspectives On Remote Collaboration, Optimization And Operations
Authors: Romatier Christophe 
Published: March 2012

Abstract
Regional, national and global businesses alike confront an array of diverse and often interconnected challenges that test their abilities to strengthen competitive position, sustain growth and increase profit margins.
In the face of such challenges, common imperatives emerge. Among them: the need to simplify work processes, improve knowledge management and find new ways to adapt and thrive in accelerating business environments.
In many instances, dissimilar industries are adopting similar solutions to meet common imperatives. One such solution is remote collaboration.
Drawing from experience across multiple industries, from mining and minerals to commercial business management, we will showcase remote collaboration solutions and highlight best practices—with an emphasis on how remote collaboration can be tailored to the petroleum industry to achieve transformative results.
Wireless Instrumentation in the Oil & Gas Industry - From Monitoring to Control and Safety Applications
Authors: Petersen Stig , Carlsen Simon 
Published: March 2012

Abstract
Wireless instrumentation, defined as the merger of wireless sensor network (WSN) technologies with industrial field instrumentation, has become increasingly popular in the process industries since the recent ratifications of the WirelessHART and ISA100.11a specifications. By providing reliable self-healing and self-configuring wireless communication, these standards offers a cost-efficient alternative to traditional wired field instruments.
In process automation, field devices can be classified in three categories according to the nature and criticality of their application; namely monitoring, control and safety. These can be further divided into usage classes, for instance enabling the distinction between open and closed loop control. The requirements of the wireless communication protocol vary depending on the usage class of the wireless instruments, e.g. there is a major difference from using a wireless sensor for history collection every few minutes, to being a part of a closed loop with a process time of a few hundred milliseconds.
This paper provides a survey of the current status of wireless instrumentation in the oil and gas industry. The requirements and challenges, along with financial drivers and benefits, are addressed, and an overview of WSN technologies and international standards are presented. Through extensive theoretical analysis, laboratory experiments and pilot installations, it has become apparent that wireless instrumentation is ready for adoption at scale in non-critical monitoring applications. For control and safety systems, however, the currently available solutions have limitations which must be addressed through research and innovation before they are able to fulfill the more stringent requirements found in these types of applications.
A Framework to Assess Value of Intelligent Petroleum Fields and Integrated Operations
Authors: Strasunskas D. , Tomasgard A. , Nystad A. N. 
Published: March 2012

Abstract
The petroleum industry implements integrated operations (IO) by adopting information technology, improving access to real-time data, integrating people and suppliers, changing work processes, and by doing so, enable better and faster decisions. IO brings benefits but the economic value is not always known or well understood. Insights to critical success and risk factors are prerequisites for sustainable integrated operations and its value.
We have developed a decision analytic framework to assess economic value of IO. The framework builds on contemporary literature that emphasizes the need to assess information technology in a broader context of organizational structures and work processes. Therefore it has a built-in qualitative assessment of intangible capital that provides indispensible insights into required competencies, capability and risks associated with a particular IO component (technologies, processes to be implemented) based on their maturity level. Yet, it allows assessment of performance and expected value using integrated formal decision analysis. Level of achieved benefits and how to maintain or even further improve them is a critical question that our framework provides insights to.
The framework was developed and validated in industrial case studies: integrated planning; and integrated drilling with companies operating on the Norwegian Continental Shelf. Hence, here we illustrate the framework and its application by a synthesized case from two industrial case studies, and highlight the lessons learned about the design and efficiency of the valuation framework.
We found the framework to be an efficient tool to evaluate projects implementing IO not only with regards to economic value, but also to gain deeper insights into determinants and uncertainties related to value. We can conclude that strength of the framework is a methodological process to analyze changes in competencies and capture downside risk reduction by IO.
The project has been performed at the IO Center (the Center for Integrated Operations in the Petroleum Industry, http://www.iocenter.no/).
WITSML: Laying the Foundation for Increasing Efficiency of Intelligent Wellsite Communications
Authors: Pickering J. G. , Shields J. A. , Gidh Y. K. , Johnson D. C. , AlShehry M. A. , Al-Khudiri M. M. , Farnan M. P. , Schey J. E. 
Published: March 2012

Abstract
When implementing an intelligent oilfield strategy it is tempting to focus on smart technology: advanced applications, novel instrumentation and collaborative environments. The data architecture is often overlooked. As deployments increase, it is important to review the industry data foundation and future direction.
WITSML version 1.4.1 is here and takes several bold steps to provide a robust, real-time foundation for data exchange and preservation. This version, the product of over two years of collaborative work by participants from oil companies, service companies and technology providers, is poised to be the keystone of the intelligent oilfield data architecture for wellsite communications.
WITSML 1.4.1 is simpler, more efficient and better defined than previous versions. It addresses several problems that hindered earlier versions by clearly specifying API behaviour and resolving ambiguities. It is also more prescriptive, which makes greater demands on software vendors but assures the one thing that matters most: interoperability. With a host of technical improvements, including new data objects, broader scope, data compression, query optimisation and change logs, version 1.4.1 will help increase the speed of information transfer and simplify use and deployment throughout the industry. To support WITSML adoption, Energistics is putting more emphasis on product certification and has initiated accredited training for developers and implementers.
WITSML uptake is growing rapidly. Server products enable efficient, secure storage with global access. The range of client products is evolving continuously and includes advanced well-logging, real-time geological and geophysical displays, automated reporting, interfaces to national data repositories and well delivery optimisation. There are now strong business drivers for making WITSML the preferred communications layer for all wellsite data. The authors will highlight the strengths of the new WITSML and its potential for increasing operational efficiency at the wellsite through improved data flow and analysis capabilities.
Saudi Aramco is a major user of WITSML technologies and v1.3.1.1 is the cornerstone of their Drilling Real-Time Data Hub (DRTDH). This paper includes a case study describing how Saudi Aramco is planning to use the enhanced capabilities of the newly released WITSML 1.4.1 to link together new drilling information with real-time data stored already in DRTDH to further increase drilling efficiency.
Transforming Remote Mountain Well Sites into Starbucks or Bridging (Layer 2) versus Routing (Layer 3) for Wireless Data Transmission
Authors: Barker David A. , Miller Mark A. 
Published: March 2012

Prelude
This technical document addresses some of the symptoms/problems associated with the current network architecture and should help foster collaborative discussions surrounding a long-term solution. While reading this paper in its entirety, the reader should ask himself/herself the question "What were the lessons learned from this predicament?" Identifying and understanding the root causes that spawned this predicament will have tremendous value towards preventing similar scenario in the future.
This document is divided into three major sections:
Introduction – Provides a brief narrative highlighting the major issues. Technology Background – A high-level explanation of the terminology used throughout this document. Risk Assessment – Identifies potential risk associated with technology.
Decision Support and Workflow Automation for the Development and Management of Hydrocarbon Assets Using Multi-Agent Systems
Authors: El-Bakry Amr S. , Romer Michael C. , Xu Peng , Sundaram Anantha , Usadi Adam K. , Morehead H. Lane , Crawford Mark L. , Holloway Bryce A. , Knight Charles A. 
Published: March 2012

Abstract
Asset management teams face many challenges with increasing asset complexity, increasing data volumes, and staff in high demand while optimal asset performance remains paramount. More effective development and management of hydrocarbon assets may be achieved through an increased level of automation of work processes and decision-support technologies across the upstream value chain. Asset management workflow automation poses special challenges as such workflows are multi-disciplinary, cross-functional, and human expertise-intensive. Advancements in the fields of artificial intelligence, software engineering, and decision sciences have led to the development of Multi-Agent Systems (MAS) which have been the cornerstone of achieving higher levels of system and work process automation and autonomy. Here, the human expertise, obtained via knowledge elicitation of domain experts, is encoded into the software in an extensible and sustainable way. Each agent functions as an entity of a distributed computing system, performing a broad range of tasks which may include advanced analytics, data quality checks, and oversight of other agents. Although agents may have competing priorities, they can convey information to one another to broker a feasible decision through collaborative and coordinated decision making. This approach is useful for distributed real-time monitoring and capable of providing technical recommendations under open-loop environments and process control in closed-loop environments. This paper provides insights into a multi-agent development process for hydrocarbon asset management workflow automation and decision support.
The Overlooked Drilling Hazard: Decision Making From Bad Data
Authors: Nybø Roar , Frøyen Johnny , Lauvsnes Anders D. , Korsvold Torbjørn , Choate Mei 
Published: March 2012

Abstract
It is widely known that data associated with oil well drilling is often noisy and otherwise of bad quality. It is also known that solutions need to draw on both people, processes and technology to make traction. However, both the severity of the matter and the complex causes of bad data are still not completely understood. In this paper we offer a new vantage point, by presenting the data quality issues as they appear in drilling operations which utilize a real-time wellbore model for supervision and decision support. We summarize experience from several pilot studies carried out by SINTEF and the Center for Integrated Operations in the Petroleum Industry, together with industry partners. We find that bad data quality is not only a cost driver, but a serious drilling hazard in its own right.
Production Gain and Optimization through the Implementation of Smart Well Completion Technology in Saudi Aramco, Case Study
Authors: Dossary Faisal M. , Dawsari Saud A. , Anazi Rayid S. 
Published: March 2012

Abstract
Saudi Aramco operates a field located in a remote area in Saudi Arabia. The field is equipped with measurement, communication, control and software systems allowing real-time automated field management. It has the highest number of smart well completion installations in Saudi Aramco with 78 smart wells and 135 permanent downhole monitoring systems (PDHMS). The smart completion ensures controlled flow contribution from each targeted area within the reservoir, unlike open hole multilaterals where the inflow of oil from each lateral is uncontrolled.
The productivity index (PI) of these smart wells is calculated based on the individual lateral productivity, which is quantified by measuring the lateral flow contributions at the surface testing facilities — multiphase flow meter (MPFM) or test trap. After the flowing period, the well is shut-in at surface allowing for pressure build up measurements. The same process is being carried out for the remaining laterals by operating the inflow control valves (ICVs).
The assessment of the laterals productivity indices revealed a huge contrast between laterals of the same well. The stronger lateral dominates the flow, thereby not allowing flow contribution from other weaker laterals. This paper will demonstrate how proper utilization of ICVs combined with well testing enabled production optimization of the multilateral wells in the field. Production was restored from dead laterals by inducing only that lateral to the production system, laterals which were cutting water were restricted to gain overall production and less hydrostatic head pressure at the wellbore and laterals with high gas-oil ratio were restricted to gain total oil production from the multilateral well.
Getting the Most Out of Networked Drillstrings
Authors: Nybø Roar , Sui Dan , Petersen Johnny , Frøyen Johnny , Jackson Thomas , Veeningen Daan 
Published: March 2012

Abstract
A dynamic real-time drilling simulator which includes all parameters essential to the well and drillstring system, is able to reproduce actual drilling with high precision. Examples of parameters are mud viscosity and density, borehole diameter, etc. It is however a challenge to collect all these parameters and the result of which can be misleading information for the drilling crew, increased NPT and increased risk of accidents.
Networked enabled drillstrings or wired drill pipe allow sensors to be positioned along the drillstring presenting a new opportunity for collecting and calibrating parameters not just from the BHA, but along the entire length of the wellbore up to surface.
This paper addresses the challenges in measuring and extracting downhole parameters for updating dynamic real-time models using the broadband network and establishes methods to integrate broadband drilling data into the critical real-time decisions performed by the wellsite and shore-based crews, while assuring trust in the conclusions from the data. Multiple measurements by several distributed sensors over time and under different conditions can be used to extract the crucial model parameters. This scheme can deal with sensor faults and distinguish a sensor fault from a kick or other unwanted events.
Moving Towards Sustainability: A 5 Year Production Engineering Experience with Intelligent Fields
Authors: Al-Zahrani Rashad M. , Dashash Alaa A. 
Published: March 2012

Abstract
It is evident that the oil and gas industry has moved from the adoption phase of intelligent fields and that the value added enabled developing and sustaining more production from complex wells. This observation is supported by various operators’ experiences with intelligent fields that have been shared in many conferences and workshops.
Haradh Increment-III (HRDH-III) is Saudi Aramco's first full field development as an intelligent field. This development has provided great utility in maintaining production plateau, very low water cut and a better-than-expected field performance. During the first few years of HRDH-III operation, numerous examples have been highlighted on the company's experience with intelligent fields and the benefits realized. At that time, we were still at the early phase in the innovation stage where applications were mostly on individual wells creating value at an individual asset level.
In the pre-injection stage (6 months before the field production start up), real time data enabled identifying an area in HRDH-III field characterized by high permeability zones because of the presence of faults and fractures. This paper picks up where previous papers stopped, giving more details on production engineering experiences in optimizing the production from this area of the field and controlling water production. The paper presents the company's continued success in utilizing intelligent fields to meet and sustain production targets and shows how we have been moving up the curve from individual assets to a regional level.
The lessons learned from this field case will help in developing best practices that boost the confidence in intelligent fields. Also, it will assure that we are on the right track for the transformation to the sustainability stage of our intelligent field applications.
Achieving Excellence in Offshore Logistics
Authors: Favilla Jose R , Claessens Dirk A , Mello Ulisses , Flach Bruno 
Published: March 2012

Abstract
New frontiers in deep water oil exploration have imposed a number of challenges for the oil industry. One of these challenges is to provide high service level to the oil platforms and drilling units to keep them operating 24/7 in the most cost effective manner. Thousands of people have to be transported to and from the platforms on a monthly basis and also food, maintenance parts, diesel and other fluids. Helicopters and special vessels are used. Drilling operations require allocation of very expensive equipments and their needs are sometimes less predictable. Complex onshore logistics, composed of suppliers, warehouses, ports, heliports, etc. are required to support the offshore operations. Currently, most of the offshore logistics are still conducted in a traditional way, breaking the logistics chain in silos with little synchronization across the entire process. The proposed approach enables a paradigm change, bringing together the concept of integrated operations, leading supply chain practices and advanced enabling technologies. The concepts presented are being discussed and adopted by leading offshore operators. Dramatic improvement in service levels and significant cost reduction can be realized, enabling the offshore operators to achieve logistics excellence.
Smart Fields - Sustaining and Accelerating Benefits from Intelligent Fields
Authors: de Best Leo , Van Den Berg Frans 
Published: March 2012

Abstract
The first decade of Smart Fields in Shell focused on the new technologies, making business cases and implementing the technologies as widely as feasible. This has led to major contributions to the bottom line, as shown in the Smart Fields Value Assessment. Entering the second decade, the focus of the Smart Fields programme is on accelerating the implementation of new technologies across assets in a way that value generation is sustained. To understand the key drivers and pitfalls in global implementation of technologies, a ‘Sustain’ methodology was developed which provided insight in where these successes and improvement areas are. Building on the results from the ‘Sustain’ assessments, the approach and focus of the roadmap ‘from technology to commodity’ was adjusted to deliver robust and sustainable deployment and continued value creation of Smart Fields technologies. This paper describes the methodology and steps which enables Smart Fields in Shell to achieve this in the digital oilfield, by deepening the integration in subsurface and surface management