bluuebunny/crossref_metadata_2025_split huggingface dataset:
Measuring Development and Adoption of New Oilfield Systems Using Technologies With Real-Time Capability
Authors: Veeningen Daan , Kanvinde Sanjay , Coffin Guillaume , Udezue Olisa 
Published: February 2008

Abstract
If a brand-new oilfield product or service becomes widely used in less than a decade, that's fast. The fact is that the petroleum industry is one of the most conservative when it comes to adopting new technology. This paper proposes and describes the use of a capability adoption index to benchmark and measure the development and adoption level of oilfield systems with real-time capability.
The capability adoption index is a tool for measuring and managing the advance of real-time technology in the industry. The application tracks incremental change and provides a roadmap for technology development and adoption. There are three main reasons for deploying systems with real-time capability. First is the growing shortage of skilled professionals. Second is the need to operate in harsh or environmentally sensitive regions, where monitoring and controlling operations from a distance can improve safety and limit the environmental footprint. The third driver is that systems that feed back data in real time may increase production by allowing operators to respond quickly to changing conditions in the well.
The 10-level index provides a bigger picture of the maturity of real-time technologies within the global market. The different levels of technology adoption are illustrated both for geographic areas and for different services. The roadmap towards autonomous automation provides more efficiency and profits for the operating company. For service companies, the ability to drill, test, operate, and control wells with real-time capability helps maintain the quality of service delivery. It creates more efficiency for people and systems.
In the industry's journey toward autonomous automation, the significance of the index is a measurement allowing companies to look back at their progress, manage change, and plan the road ahead.
Extensions to and Roll Out of Data Driven Production Surveillance and Optimization
Authors: Moncur C. E. , Jakeman S. , Berendschot L. , Cramer R. , Briers J. , Stroobant F. , Ahmad R. , Goh K. C. 
Published: February 2008

Abstract
Oil and gas production from a cluster of wells is conventionally relatively difficult to manage, at least partly due to field conditions, subsurface uncertainty and the multiphase nature of the well effluents. This can lead to late diagnosis of production problems, slow and conservative handling of production constraints and restricted understanding of subsurface potential. FieldWare Production Universe (FW PU) is a software application developed by Shell International Exploration & Production and Shell Global Solutions International that allows data driven well models to be constructed and updated from real time production data, and thereafter applied to track well-by-well production in real time. This paper updates on extensions of FW PU data driven techniques and also on the experience so far on the wide scale field implementation, roll out and support of the technology.
The successful embedding of a real time technology that such as FieldWare PU, which allows a step changes in the level of surveillance of well-by-well production, and the realization of maximum value from its use is a non-trivial exercise. In an ideal implementation, the software application needs to match the dynamic physical production elements (reservoir inflow, well performance, production processing and testing facilities) and the capabilities of the production staff as well as their production management processes. Key elements of the FW PU roll out in field operations include evaluation of actual production surveillance challenges vis-à-vis the value of the tool to be introduced, hardware and software readiness checks, clear setting of goals and expectations, post implementation evaluations, training of users and super-users, adjustment of workflows, and embedding the use of the application into the relevant operational processes.
This paper further discusses extensions of the data driven approach to a wide spectrum of applications, including real time operational optimization, the tracking of well productions in subsea and smart wells, and for specific types of production operations such as for beam pumped wells as well as wells which are intermittently operated. In particular the application of data driven techniques to beam pump pump-off controls, circumventing the need for load cells, is highlighted.
"If Tesco can do it why can't we?": The Challenges and Benefits of Implementing RFID and Mobile Computing in Upstream Environments
Authors: Morris Carl 
Published: February 2008

Abstract
We live in a fast moving consumer world where pocket PCs are common place and auto-identification technology is everywhere - mainly barcoding but increasingly Radio Frequency Identification (RFID). So why isn't Upstream Oil and Gas adopting these technologies at a faster rate to improve business performance? "If Tesco can do it, why can't we"?
This paper examines the major applications for the use of hand held devices (HHDs) and auto-identification within supply chain, maintenance and operations. It describes the benefits in terms of the ability to link offshore and onshore operations more effectively and accurately pass real-time or near real-time information between assets, support organisations and supply chain partners, to allow earlier and improved decision quality, as well as the traditional efficiency gains. Upon detailed analysis, moderate investment yields high potential returns.
One of the fundamental differences between the supermarket chains and the Oil and Gas industry in this area is the lack of agreed technical standards in terms of RFID hardware and data transfer standards, acting as a barrier for supply chain integration. This paper touches on the work that is underway to address this issue, but goes on to explain how an appropriate application of technologies and attention to process and change management considerations can deliver robust solutions for operations and maintenance today.
Design of Visual Facilities Within Collaborative Decision Environments
Authors: Clark Alex 
Published: February 2008

Abstract
"How big does the screen need to be"? This was the innocent first question asked near the beginning of a deployment of multiple collaborative decision environments (CDE). Slowly, the complexity of the problem surfaced as we were forced to consider the following questions: What are the limits of current display technology?How will people be seated in the physical space and how many seats are required?What is going to be on the display? How can we use that space most effectively?
A large quantity of information exists from vendors detailing the optimum size of display and placement for a television or cinema screen. A large body of data exists for individuals using computer monitors. Each has very different usage characteristics.
CDEs created a scenario that falls between these extremes — computer display characteristics (able to clearly read data) within a group environment (like a cinema). The display itself will be divided into sections, effectively providing users with a matrix of individual computer monitors that need to be examined both individually and as a whole.
To achieve this, there was a need to go back to first principles and answer some important questions. What is 20/20 vision? What are the ergonomics of the eyeballs, neck, and body? What types of information exist and how is it visualized? The final solution needs to be deployable in the office, to locations offshore, and perhaps even in a portable environment to teams ranging from a single user to 10 or more.
This paper examines this problem and provides some methodologies about how to determine the best display for a facility and where to place users within a room so that they can see clearly the full extent of the display. It also explores how this information should be laid out to maximize the usefulness of the display area. This information should prove beneficial to future CDE designers.
Downhole Multiphase Metering In Wells By Means Of Soft-sensing
Authors: Leskens M. , de Kruif B. , Belfroid S. , Smeulers J. , Gryzlov A. 
Published: February 2008

Abstract
Multiphase flow meters are indispensable tools for achieving optimal operation and control of wells as these meters deliver real-time information about their performance. For example, multiphase flow meters located downhole can improve the production of multilateral and multizone wells by timely allocating the zone where a gas or water cone occurs. However, multiphase meters are either expensive, inaccurate, or cannot be used downhole due to the harsh conditions. An alternative that can be used to overcome these disadvantages is to use multiphase soft-sensors, i.e. to estimate holdups and flow rates from relatively cheap and reliable conventional meters, such as pressure and temperature measurements, and a dynamic model connecting these measurements with the unknown quantities. The aim of this paper is to demonstrate, via two simulation based case studies, some possibilities and limitations of such multiphase soft-sensors. In the first case study the question is adressed whether it is possible to use only downhole pressure and temperatures measurements to estimate in real-time the water, oil and gas flow rates in a well. This question is of practical importance as these measurements are relatively cheap and reliable. The second case addresses the question whether it is possible to allocate the gas cone in a well with multiple inflow points or zones. This question is relevant as the estimated flow rate and holdup profiles can be used to manipulate Inflow Control Valves in such a way that gas breakthrough is prevented.
Using amongst others OLGA data as "real-life" data, an additional question addressed here is what the influence is of soft-sensor model error and measurement noise on the quality of the estimates.
From the first case study it can be concluded that, due to bad observability, pressure and temperature measurements alone are not sufficient to accurately estimate in real-time well flow composition parameters in a practically relevant situation. The preliminary results discussed in the second case study indicate that a soft-sensing solution to the gas cone allocation problem may very well be feasible.
Real-Time Integrated Field Management at the Desktop
Authors: Issaka M. B. , Dahan M. W. , Alburaikan M. M. , Verjan E. A. 
Published: February 2008

Abstract
Accurate individual well production rates are essential to meet corporate production target plans, optimize reservoir performance and make reservoir management decisions that may require well intervention. Short of installing rate measurement devices on each well, a "back allocation" method is generally employed to assign well production rates, using multiplying factors based on well tests conducted the month before. Apart from the inherent errors, based on the assumption that the wells produce at the same rate throughout the month, the process is also not suited for real-time field management that requires production rates to be known much more frequently.
This paper describes the implementation of a system that automates the calculation of individual well production rates using real-time pressure data from permanent sensors installed on the wells. The system, based on integrated physical models of the reservoir, well and surface network, has been successfully used to implement crude blend management in a large Saudi Arabian field, producing from three different reservoirs. The paper also describes how the system is used to automate the validation of well test measurements, allowing the engineers to focus their time on problem wells while ensuring that all wells are reviewed. In addition, field models are kept evergreen and can be utilized by different disciplines for production forecasts.
Application of the system could result in significant cost savings, due to reduction in the requirements for physical metering of well production. The system also provides unique optimization opportunities, allowing the engineer to determine the optimum settings to maximize production or revenue. Other benefits include, faster resolution of production problems due to early problem detection, focus on exceptions rather than bulk and massive troubleshooting, and zero-latency application-assisted decision making, all combining to bring real-time field management and optimization to the engineer's desktop.
Information Technologies That Enable Human Competence Development and Assurance
Authors: Omar Samir , Al Hosani Hassan , Moore Robert L. 
Published: February 2008

Abstract

Description of the Material
This paper describes the experience of an Abu Dhabi upstream operating company in the implementation of a competency assurance system for entry-level employees. The implementation and tracking processes which form the core of the system were designed with project management and engineering principles in mind. They therefore lend themselves to the technologies that project managers and engineers use, such as databases, project planning systems, and graphical reports and scorecards. The company's use of these technologies based on coupling clarity of business requirements with simplicity of IT solutions resulted in a rapid and successful implementation of the competence assurance system.

Application
This material is applicable to organizations considering or implementing a competence development and assurance system.

Results, Observations, and Conclusions
The methods described in this paper, derived and proven in practice, have helped the company:
As a result, the company has achieved a high success rate in moving employees through the system quickly and efficiently.
The paper will also describe how the engineered approach alone is not enough when developing human competencies. Effective marketing, leadership, reward, and knowledge management systems are also critical to successful implementation.

Significance of Subject Matter
As oil and gas companies strive to achieve performance excellence and meet tough HSE goals, the challenge faced by all is to find, develop and retain competent people. This challenge is magnified as the current employees' demographics alert high risk of skills dilution and when advances in technology drive renewed development efforts. Competence assurance processes that are structured, systematic, and measurable are important tools for companies to use for achieving this desired result.
Improving Production By Use of Autonomous Systems
Authors: Ølmheim Jørn , Landre Einar , Quale Eileen A. 
Published: February 2008

Abstract
Several companies have reported from 2% to 5% increase in oil production, and in some cases up to 10%, by a closer collaboration between onshore-based production optimization groups and offshore personnel. Several aspects have become apparent: shorten reaction time to implementation of optimization measures enables staff to take full and immediate advantage of opportunitiesthe work is manpower-intensive during the collaboration sessions, but ensures continuity and easy access to technical competenceengineering resources are already scarce, and there is a need to relieve staff of minor, routine tasks to enable attention to be focused on realtime issues requiring human expertiseincreased level of instrumentation complicates the work because it becomes increasingly difficult to utilize the available information to make better decisions
Other industries in information rich and highly dynamic domains have over years utilized the capabilities provided by autonomous systems and their dominant implementation platform, software agents to improve the decision making process. Over the last few years in collaboration with an autonomous software platform vendor, StatoilHydro have tried to apply the experience from other domains on some of our core business processes, concentrating on improving the volume of produced hydrocarbons and the regularity of the production process.
The work so far shows that in certain circumstances, autonomous systems can contribute to more effective production. In particular they enable more frequent adjustments in response to the actual well conditions. The main difference between the autonomous systems and more traditional automation is the ability to keep the human in control.
In our latest attempt we have applied the concepts of variable and delegated autonomy from the domain of unmanned flight on our production process. Compared with more traditional automation, the concepts of delegated and variable autonomy introduce negotiation between different sub-systems and a much more adaptable human-machine interaction.
Streamlining Quality Through Technology – An Electronic Workflow for Assessing Quality of Well Log Data
Authors: Boudreaux M. D. , McCracken D. D. 
Published: February 2008

Abstract
For wireline service companies, delivering accurate well log data to clients is crucial. Until now, assessing the quality of well log data was handled at the local level, with no global visibility or standardized assessment procedures. To address this issue, a streamlined electronic workflow was developed to monitor and significantly improve data quality, standardize log presentation throughout the organization, and ultimately ensure the quality of data delivered to customers.
Leveraging existing company processes, the Log Quality Assessment (LQA) system workflow allows field engineers, operations managers and geoscientists to share well data electronically and use this data to quickly and efficiently assess the quality of client deliverables at an individual service level. By directly linking the LQA grading system to the well log data uploaded to the company's existing WellLink well data management system (for the purposes of this paper, referred to as WDMS), the LQA system electronically streamlines the movement of log quality data from field engineers to operations managers to geoscientists, thereby speeding the process of problem identification and resolution. In addition, the LQA system is designed to allow expansion, including the evaluation of other data sets, services and business units. Reports generated nightly allow managers to evaluate log quality progress, spot emerging trends, and monitor overall performance by field engineer, service type, grade criteria, customer or geographic area. With this global electronic system, identifying negative trends in log quality can occur in a matter of days.
Development of a Multi-Skilled Onshore/Offshore Team
Authors: Allan Derek , Pace David 
Published: February 2008

Abstract
One of the key factors impacting the performance of remote operational teams is the relationship between the onshore and offshore crews. Too often it is assumed that the crews will simply continue on a "business as usual" basis. This ignores, and furthers, the behavioural divide between the well-site and remote operating centre.
This paper discusses the training and development of a rotational crew and its work processes as designed to minimise, and indeed enhance, the impact of remote operations on performance.
Initial required skill sets and bespoke training are identified. The process is further enhanced by the identification of specific roles and responsibilities for each core section and completed with development of a transitional procedure to ensure that the rotational crew is competent not just in the necessary technical skills but also in the critical behavioural practices.
Applying Sand Management Process on the Lunskoye High Gas-Rate Platform Using Quantitative Risk Assessment
Authors: Gunningham M. C. , Addis M. A. , Hother J. A. 
Published: February 2008

Abstract
This paper is a case study, which describes how Quantitative Risk Assessment (QRA) is applied to sand management in the specific case of Lunskoye, to minimise risk of failure, while maximising production, reducing cost, and safeguarding reserves. Lunskoye is a high-rate gas development offshore Sakhalin island. The key concern is safely producing gas at high velocity, while minimising the risk from sand production.
In order to develop a safe method of producing gas, an integrated multidisciplinary team was put together to address the key parameters to manage potential sand production, using QRA.
In particular, consequences, probabilities of occurrence and means of monitoring and control were addressed. The key aspects of this approach are using the right kind of technology to design a safe production system, and then using the appropriate data to monitor and manage the impact of sand production.
The "intelligent tool" that was used allows an experienced integrated team to focus on the practical aspects of managing sand production in a structured and systematic manner to quantify the residual risk to people, facilities, and the asset as a whole. That tool also allowed us to integrate the inputs from widely spaced geographical locations - the production system was designed in the Netherlands, and was being built in Korea, then relocated to Sakhalin island.
The QRA involved the operator (Sakhalin Energy) and technical advisor (Shell), combining input from the corporate knowledge base with that of the asset team. This delivered operational plans that provide the key guidance for safe operation, which was endorsed by the operator and its shareholders. Overall, the value of this work has significantly reduced the risk exposure to the project, while reducing well completion costs and safeguarding production in the long term.
Optimization of Smart Well Production through Nonlinear Model Predictive Control
Authors: Meum Patrick , Tøndel Petter , Godhavn John-Morten , Aamo Ole Morten 
Published: February 2008

Abstract
In this paper, we present an algorithm for optimizing reservoir production using smart well technology. The term smart well is used to indicate an unconventional well equipped with down hole inflow control valves (ICVs) and instrumentation. This additional instrumentation extends the degree of freedom in the field production planning, since production can be efficiently distributed on the different well segments available. By proper utilization of the ICVs through optimal production planning, an increased oil recovery for the reservoir can be expected.
We propose a method for optimal closed-loop production known from control theory as model predictive control (MPC). A commercial reservoir simulator, ECLIPSE, is used for modeling and predictions. MPC is chosen for its ability to provide an optimal solution for the constrained multivariable control problem. To compute the optimal ICV settings, we propose using a nonlinear MPC (NMPC) application, which can handle the severe nonlinearities found in reservoir models. The NMPC uses a single shooting multi-step quasi-Newton (SSMQN) method to solve the optimization problem. As the term multistep suggests, this is an iterative method which solves a sequence of quadratic problems (QPs) in each time step.
We apply our method to a benchmark reservoir model with multiple geostatistical realizations. This model has already proven potential for increased oil recovery by using optimization techniques. We show an even additional increase over the former approach in production totals, using the SSMQN method, with as much as 68% increase in one case, and 30% on average compared to a reference case.