bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Measure of Success: Measurement of Digital Oil Field Success Focusing on Hard and Soft Measures
Authors: Crockett Brian 
Published: February 2008

Abstract
Many business cases for embracing technological improvements around Smart Fields®1 "oil fields of the future," or "e-wells" have been justified by predicting an increase in production; the industry-accepted figure is approximately seven percent. In this paper we want to examine the benefits that this new way of working brings to operators and to demonstrate what can be done to measure the directly related benefits as well as the "knock-on effect" that it has other areas.
We want to examine what happens when the value loop of physical assets, data gathering, models and decision making is closed, and to identify the underlying measurable benefits which can be seen at each stage of a production optimisation process.
Most benefits boil down to "faster, cheaper, better" and that is converted to value by: Reduced elapsed time to arrive at desired result – know soonerReduced amount of effort involved – number of man hours – decide fasterReduced cost of effort – cost of man hour – cheaperIncreased quality – reduce errors, improve performance – perform better.
There is a need to determine how improvement takes place and which production items need to be considered. This paper uses a framework for identifying these and attempts to measure benefit by: Determining a baselinePopulating historical metricsIdentifying new perceived metricsComparing results.
Based on experience, we can now show value by identifying the problem and addressing a need in real time. This will be demonstrated by looking at implementations in Brunei, Norway, Louisiana and some cross-project observations.
"If we don't know what we don't know, how will we know what we need to know?"
That perhaps is the big question that the smart digital oil field of the future will answer for us if we embrace the foundations of integrated work flows, which include people, processes, and technologies. This will give us the wealth of data we need to model our results and optimise our production using collaborative decision making, and, as identified, we will discover hidden benefits along the way.
Guided Workflow for the Digital Oil Field: A Practical Example
Authors: Milligan Greg , Deutekom Mark , Buchan Chris 
Published: February 2008

Abstract
As is often seen with new concepts, there is a lot of confusion on both the customer and market sides as to what the term "guided workflow" actually means. Applications exist that claim to offer guided workflow solutions, yet the fundamental questions remain: What is workflow? What makes a workflow "guided"
In this paper, we answer these questions by discussing how we have applied guided workflow within the digital oil field domain. We provide a focused dissection of two case studies in which guided workflow is applied in key decision-making processes. We then use the findings of the case studies to report the strengths and limitations of the approach within a real business context.
The first case study discussed is within the area of automated surveillance and alerting. Here, guided workflow is used to facilitate intelligent alarming and enable a better decision-making process. The guided workflow helps to filter alarms by collating data from various sources and presenting pertinent information to users based on a series of defined business rules.
In the second case study, we use guided workflow as a tool for governance of a change management process and demonstrate how collaborative decisions can be reached through a series of branched, looped, and linear steps within the workflow.
In both cases, we will discuss performance measurement, roles and responsibilities, knowledge capture, and the decision trail.
Reliable IT for Integrated Operations
Authors: den Hamer Pieter J. , Skramstad Torbjørn 
Published: February 2008

Abstract
The oil & gas industry and especially integrated operations, depends heavily on reliable and robust information technology (IT). Systems and components are increasingly "software intensive" and interconnected. However, at the moment IT is often not reliable enough, resulting in serious risks for production continuity and safety. To manage these risks, the oil & gas industry needs to mature its IT reliability, supported by guidelines that are developed in the "GOICT" joint industry research project, initiated by DNV. So far, this project has identified a number of critical areas, summarized in this publication, that need to be addressed to improve IT reliability for integrated operations.
Subsea Condition Monitoring: A Path to Increased Availability and Increased Recovery
Authors: Friedemann John D. , Varma Anil , Bonissone Piero , Iyer Naresh 
Published: February 2008

Abstract
The application of subsea technology to reservoir development has been accepted as a valid production solution despite the known effects on facility availability and on ultimate recovery. The primary causes of the reduced availability for subsea tree-based solutions are directly related to the differences between the facility designs. A topsides drilling unit provides simple and direct access to the well for purposes of well logging and other data acquisition, and well interventions to replace equipment.
Other benefits of surface tree solutions are related to ease of well testing and chemical treatments. These in turn simplify the hardware maintenance because the facilities can be inexpensively directly accessed. In essence, the surface access solution gives increased well recovery because maintenance and diagnostic investigations are based on existing infrastructure (a permanently mounted drilling rig).
The subsea industry shares a common feature with other, more traditional, industries like Energy and Rail: the occurrence of unplanned outages results in increased costs and reduced revenues in each of these industries; a condition-based planning approach is the more desirable solution. Rail and Energy industries have successfully evolved to solutions based on the use of contractual frameworks aimed at guaranteeing equipment availability and efficiency.
This paper will examine the applicability of condition-monitoring technologies to subsea infrastructure in the oil production industry. The paper will present relevant case studies from the Energy and Rail transport industries. It will describe data and information handling which are required to enable the full development of a qualified predictive maintenance tool for the oil industry, with the view of taking the oilfield towards a paradigm of a contractually managed asset with the goals of improving service life and availability.
The Application of Knowledge and Continuous Learning to the Implementation of Collaborative Work Environments at Shell
Authors: Knoppe R. , Holloway S. 
Published: February 2008

Abstract
Broad industry trends that are reshaping exploration and production (E&P) operations warrant a rethinking of traditional operating models as part of strategies designed to optimize the development and production of oil and gas assets. Shell E&P is introducing a new collaborative operating model as part of its global digital oilfield strategy. The collaborative model leverages the expertise of its global workforce through redesigned business processes and specially designed collaborative facilities to capture maximum benefits from its investment in smart digital oilfield technologies. Each collaborative environment shares a common, standards-based information technology (IT) architecture that can enable the linking of offices, platforms, and remote operation sites into a single global network providing real-time access to Shell E&P's community of expert practitioners and a common, shared institutional knowledge base. An important contributing factor to Shell E&P's success in introducing collaboration has been its ability to effectively shape a culture of collaboration and teamwork through trust, knowledge sharing, and continuous institutional learning. This paper examines one key element in the success of these collaborative centres by adopting innovative methods that Shell E&P is using to more effectively capture and share its institutional knowledge and experience through a culture of continuous enterprise learning. While this organizational transformation remains work in process, initial findings confirm the initiative is delivering tangible results towards the goal of optimizing production and recovery from assets.
Predicting Fluid Paths By Integrating Production and Drilling Data: Seeing the Invisible
Authors: Al-Dossary Saleh , Al-Hawas Khalid 
Published: February 2008

Abstract
Natural fractures and faults in the subsurface play an important role in fluid flow and accumulation. Therefore, identifying and mapping the distribution of fractures and faults systems is critical to understanding the fluid dynamics within a reservoir.
Although fractures and small-throw faults are not easily identifiable using conventional 3-D seismic techniques, their orientation and intensity can often be inferred using seismic attributes such as coherence and seismic curvature.
This case study will demonstrate how seismic curvature was used to map small scale fractures in a Saudi Arabian oil field which has been affected by premature water breakthrough. Premature water breakthrough is an increasing concern to all the geoscientists and engineers involved in developing the field. Curvature illuminates subtle fracturing that was difficult to detect with conventional seismic amplitudes. Using curvature allows geoscientists to map, for the first time, small-scale fractures believed responsible for bringing water prematurely to the top of the reservoir. The integration of image logs, zones of lost fluid circulation, production test and well test data has increased our interpretation confidence and helped optimize the placement of future horizontal wells.
New Drilling and Completions Applications for a New Era
Authors: Sawaryn S. J. , Pickering J. , Whiteley N. 
Published: February 2008

Abstract
Most of the existing drilling and completions engineering applications in use today were designed to compute snapshots at a single point in time for one user, rather than presenting the acceptable operating envelope and its associated constraints over time and supporting interaction of multi-disciplinary teams in collaborative environments.
The massive increase in data now available from real time sensors can make identification of critical factors more difficult and can hinder, rather than enhance the decision making capability and response to alarm conditions. Currently, interaction between individual team members is cumbersome and it takes place outside the applications. Teams are increasingly multi-cultural, which places additional demands on the human-computer interface and cultural and linguistic preferences need to be considered, particularly where collaboration centres span international boundaries. The applications are also part of a growing portfolio, including office and knowledge management tools. Their usefulness and efficiency depends on successful integration. In turn, this depends critically on standards. The working practices emerging from the use of these environments means the earlier applications are no longer optimised for the circumstances in which they are to be used.
The paper contains a discussion of these changes and the new functionality required of the applications using a popular model in industrial psychology. It draws on practices from other industries, observations in collaborative environments and other, earlier work within our own industry that appeared before their time. It is concluded that new applications are needed for this new era and that some may bear more resemblance to gaming software than raw calculating engines. It also concludes that a number of the constraints may be self-imposed, by our failure to keep pace with the rapid and continuing developments in information and communications technology and the business models developed for the virtual world.
Winning the War for Talent
Authors: Miller Mark 
Published: February 2008

Abstract
How do oil companies compete for the short supply of technical talent? Is there another approach to attract and develop the necessary skills across the globe to fill the expanding void of engineers?
In the mid 1990's the explosive growth of information technology signalled a new challenge for many industries; the impending shortage of talent to develop and deploy technology. And the competition for talent isn't just limited to technology companies; competition for top talent starts early when people are planning their lives and continues throughout their lives, regardless of their initial career intentions. The oil industry competes with high tech, financial services and medicine for the best and brightest.
Cisco recognized this challenge and chose a novel approach, one that addresses sustainable economic development, corporate social responsibility and the pursuit of the best and brightest. In 1997 Cisco founded it's first the Cisco Networking Academy. Over the past 10 years over 2 million people have passed through Cisco Network Academies. Today over 9,500 academies span 168 countries admitting 500 students per day. Over 50 percent of the graduates entered the IT world, 71 percent of those went on for additional technology education and 91 percent say they still use the skills acquired in a Cisco network academy on a daily basis.
In this paper we'll explore how the academies are run across a variety of venues and environments. What is the cost and how are alternative funding mechanisms employed? What is the payback? How are governments and other companies supporting and benefiting from the program? What are the critical success factors? How could this model be applied to enhance the global shortage of technical talent facing the oil industry?
Saudi Aramco Intelligent Field Development Approach: Building the Surveillance Layer
Authors: Al-Dhubaib Tofig A. , Issaka Mohammed Ben , Barghouty Murad F. , Mubarak Saeed , Dowais Ali H. , Shenqiti Mohammad S. , Ansari Najmul H. 
Published: February 2008

Abstract
The Intelligent field is the oil industry's new trend that enables continuous monitoring and optimization of individual wells and overall reservoir performance. This is achieved by integrating fields’ real time data in the reservoir management business processes. The results from this integration are anticipated to increase production rates, identify opportunities for higher hydrocarbon recoveries and reduce operating costs and future capital expenditures.
Saudi Aramco has embarked on implementing the Intelligent Field (I-Field) initiative through new pilot projects in Qatif and Haradh increment III fields. The objectives of the pilot projects are to provide real-time diagnostic capabilities, highlight and address implementation challenges, and develop a comprehensive architecture for I-Field implementation in Saudi Aramco fields.
This paper discusses the implementation approach of the intelligent field initiatives in Saudi Aramco. It will shed light on the challenges encountered and will present the process and methodology of developing the roadmap of the "surveillance layer," the first building block of Saudi Aramco's I-Field architecture.
eDrilling Used on Ekofisk for Real-Time Drilling Supervision, Simulation, 3D Visualization and Diagnosis
Authors: Rommetveit Rolv , Bjørkevoll Knut S. , Ødegård Sven Inge , Herbert Mike , Halsey George W. , Kluge Roald , Korsvold Tørbjorn 
Published: February 2008

Abstract
eDrilling is a new and innovative system for real time drilling simulation, 3D visualization and control from a remote drilling expert centre. The concept uses all available real time drilling data (surface and downhole) in combination with real time modelling to monitor and optimize the drilling process. This information is used to visualize the wellbore in 3D in real time. eDrilling has been implemented in an Onshore Drilling Center in Norway.The system is composed of the following elements, some of which are unique and ground-breaking: An advanced and fast Integrated Drilling Simulator which is capable to model the different drilling sub-processes dynamically, and also the interaction between these sub-processes in real time. The Integrated Drilling Simulator is used for automatic forward-looking during drilling, and can be used for what-if evaluations as well.Automatic quality check and corrections of drilling data; making them suitable for processing by computer modelsReal time supervision methodology for the drilling process using time based drilling data as well as drilling models / the integrated drilling simulatorMethodology for diagnosis of the drilling state and conditions. This is obtained from comparing model predictions with measured data.Advisory technology for more optimal drilling.A Virtual Wellbore, with advanced visualization of the downhole process. A new generation visualization system designed to integrate all participants involved, will enable enhanced collaboration of all drilling and well activities in a global environment.Data flow and computer infrastructure
eDrilling (Ref. 1) has been implemented in an Onshore Drilling Center on Ekofisk in Norway. The system has been used on several drilling operations. Experiences from its use will be summarized and presented; both related to technical and work process issues. The supervision and diagnosis functionalities have been useful in particular. The system has given very early warnings on ECD and friction related problems. This paper will present the eDrilling system used on a specific Ekofisk wells with focus on experiences from its use.
ADMA-OPCO Process Management System (APMS)
Authors: Al Badawna Alaeddin 
Published: February 2008

Abstract
This paper will demonstrate how information technology is invested in automating the reporting of activities within the plant operations in our Organization ‘ADMA-OPCO’. It will highlight how that automation has brought about change on People, Process and Organization (PPO). The paper will emphasize how the workforce becomes enabled to streamline the reporting of their shift activities in a coherent and standardized manner. It will finally conclude how safety standards get promoted, integration gets facilitated and decision making process enhanced.
Prior to that, a brief account will be given of the Company's profile, its core business and the issues that it has encountered in managing its operation activities at offshore sites. Afterwards, a description of the ADMA-OPCO Process Management System (APMS) will follow, covering various aspects: business functionality, technical specification and system features.
Abu Dhabi Marine Operating Company (ADMA-OPCO) is a major oil and gas producer in the region whose vision is to perform as a world class hydrocarbon producer from the offshore concession reserves, ensuring facilities integrity, protecting health, safety and the environment for the next 50 years.
Pace and Scale Deployment of a Real-Time Information System
Authors: Toth D. A. , Dickens J. S. , Overton D. 
Published: February 2008

Abstract
This Paper will describe in detail the process by which a newly developed real time information system was deployed at pace and scale to the Upstream community of a major integrated oil company. The primary focus will be a case study which demonstrates how an application can be successfully deployed across a wide range of cultures in order to bring standardization to the way real time data is accessed and used to generate value.
The ISIS (Integrated Surveillance Information System) program, developed by BP, provides distinctive real time well surveillance functionality. Delivering value from this technology development depends critically on successful deployment at a global scale.
This paper describes the Deployment Model used to guide such a full scale deployment program. Important pieces of background information will be presented first, followed by a review of the model and a description of its use.
Prior to full scale deployment of the final ISIS product, early beta versions were deployed. Learnings from these early deployments provided the basis upon which the final model was built. A review of lessons from these early efforts identifies potential pit falls and defines the elements of the final Deployment Model that are critical to an effective program.
This model has been applied to deploy ISIS to more than 20 fields spread over several regions worldwide, including amongst others, the UKCS, Gulf of Mexico, and West Africa.
Neural-Network based Sensitivity Analysis for Injector-Producer Relationship Identification
Authors: Demiryurek U. , Banaei-Kashani F. , Shahabi C. , Wilkinson Frank 
Published: February 2008

Abstract
Determining injector-producer relationships, i.e., to quantify the inter-well connectivity between injectors and producers in a reservoir, is a complex and non-stationary problem. In this paper, we present a neural-network-based sensitivity analysis approach to address this problem. To the best of our knowledge, sensitivity analysis has never been applied for identification of the injector-producer relationships, yet we show that it is an intuitive while fundamental approach to address this problem. Sensitivity analysis is based on a theory with which the functioning of a closed system is derived by analyzing the derivatives of the output with respect to each input combination. For the injector-producer relationship identification problem, we use sensitivity analysis to determine the injector-producer relationships by varying the injection rates, i.e., the inputs to a trained neural network model of the oilfield, and analyzing the outputs, i.e., the production rates.
With our approach, we first generated a neural network to define the mapping function between each producer and its surrounding injectors based on the historical injection and production data. We employed Back-Propagation-Through-Time (BPTT) learning algorithm to train the three-layer feed-forward neural network using real data collected from 1911 to 2005. Next, we utilized the generated neural network model to apply sensitivity analysis in order to quantify the significance of the injectors on the corresponding producers.
We evaluated our proposed injector-producer relationship identification technique by experiments with real oilfield dataset as well as field trials. Experimental results show that our sensitivity analysis approach is not only an efficient method for identifying injector-producer relationships but also reveals significantly higher correlation accuracy as compared to the correlation typically estimated by the field engineers.
Use of Agent Structures for Event Detection: Identification of Wells Watering Out on Troll
Authors: Halmøy Randi-Helene , Verhelst Frédéric , Díez Marta Dueñas , Halvorsen Martin , Nordtvedt Jan-Erik 
Published: February 2008

Abstract
The industry-wide focus on Intelligent Energy in recent years has lead to more and better data being available, both onshore and offshore. Regrettably, processing tools have not seen a proportional improvement, and therefore engineers experience a data overload. Fairly simple alarms along with manual routine checks using independent, "offline" tools are dominating the daily tasks in production optimisation, and more intelligence and flexibility is thus needed. In this paper we suggest an agent structure allowing online, real-time event detection.
In this work producing oil wells watering out on Troll were used as an example. The detection algorithm was designed to search for significant drops in the wellhead pressure. By detection of such trends at an early stage, a successful correction and restabilisation is more likely.