bluuebunny/crossref_metadata_2025_split huggingface dataset:
Implementing New Technology Securing Availability And Quality Real-time Drilling Data Onshore
Authors: Halland Thomas , Steinsbø Lie Stian , Hoff Lene , Solnørdal Dag 
Published: March 2012

Abstract
In 2009 Statoil rolled out a performance incentive business model ensuring high quality real-time drilling data deliverables [SPE 127799]. But how do you measure performance? And how do you create a system automatically monitoring quality all the way from the rig and into target systems onshore?
Talking to operators and service companies, Statoil concluded that our industry seemed to be at a starting point when it comes to deploying automated monitoring systems targeting both availability and data content.
A technology development project was established in parallel with the performance incentive business model [SPE 127799], with the following goals:
Ability to monitor real-time drilling data streams from Statoil's drilling operations into all target systems Automated alarms triggered by data content automatically notifying operators on e-mail/SMS Automatically monitoring service company performance, including KPI's
The idea was simple: Implement a proactive monitoring system tailor-made for the drilling domain which automatically alerts user whenever there are problems. Instead of having 15 resources on a continuous 24/7 rotation manually monitoring the data streams, the system shall automatically monitor and alert on SMS/E-mail whenever a problem needs attention.
We will present our initial thoughts, what we learned, and the final results:
Use cases for a real-time drilling data monitoring system Design, specification and algorithms Implementation and deployment Experiences and challenges along the way
We will present our observations and conclusions on developing this technology, the main conclusion being that a proactive alarm system has drastically improved the quality of real-time data deliverables to Statoil's drilling assets, and also reduced the number of people needed to maintain quality data streams.
Innovative Intelligent Technologies used for Production Optimization and Infrastructure Integrity Surveillance
Authors: Roberts Ian , Albert Alexander , El Hares Layla , Rossi Marcus 
Published: March 2012

Abstract
In the oil & gas industry sporadic studies are developed to analyse the flow conditions and operations procedures through the life of the field. The objective of those studies is to understand the environment, boundary conditions and properties changes along the fluid journey. For characterization of the production behavior, engineers use model-based multiphase flow simulation via various applications available on the market.
A constant understanding of the fluid flow conditions is valuable for the decision process on the execution of operational procedures. A robust flow assurance strategy is dependent on the level of awareness of the real production conditions prior to a fluid flow interruption event. Fiber optics distributed sensor system has been recently used mainly for integrity monitoring purposes; the proposed methodology unlocks the additional values for interfacing disciplines as flow assurance by the provided simultaneous distributed measurements of temperature, strain, and vibration.
The model-based multiphase flow simulations represent flowlines and production networks and as output of those simulations operating profiles are used to evaluate the risk of solids precipitation and deposition along the flow path. A regular update of simulation models by real-time data from field sensor results in a more reliable representation of the production system operating profile that can support the flow assurance strategy by the detection, monitoring, and location of events.
This paper proposes the use of real-time data acquisition from an optical-fiber distributed sensor for the assurance of fluid flow along the production system. It outlines a methodology to perform flow assurance automated surveillance based on multiphase flow simulation models constantly fed with real-time field measurements to estimate fluid flow conditions throughout the system to avoid potential problems, such as flow restrictions due to solids deposition.
Temperature Transient Analysis in a Horizontal, Multi-zone, Intelligent Well
Authors: Muradov K. M. , Davies D. R. 
Published: March 2012

Abstract
Intelligent, or I-wells, are a core element in the delivery of the "digital oil field". Numerous publications have described how their control and monitoring capabilities can lead to an increase in reserves. Such monitoring systems provide the data which, when analysed with the appropriate algorithms, is turned into real-time information; viz. the quantitative values of the multiphase flow rate distribution across the multiple completion intervals. This transformation of data into information is the first step in a real-time, selective, zonal production management methodology. A second use of this information is the updating of the reservoir model, providing improvements in the reservoir description, the production performance prediction and the reservoir depletion strategy.
Temperature data plays an important role in downhole monitoring. It may be the sole source of downhole data or it may complement downhole, pressure gauge data. However, temperature data analysis workflows are less well developed than their pressure equivalent. Further, the installation of distributed temperature sensors is not always possible across the lower completion of many multi-zone, I-wells.
To fill this gap we have set ourselves the target of developing transient temperature analysis techniques based on the use of data from discrete, relatively accurate, temperature gauges installed across each production zone. We recently reported our first step in this process, the mathematical basis for temperature transient analysis of a single zone. This paper extends our first step in the development of a comprehensive, temperature analysis workflow to the analysis of a horizontal, multi-zone, I-well.
The workflow necessary to calculate the sandface temperature for each zone in a multizone completion will be presented. The novel aspect of this new workflow is that allowance is made for the affect of fluid flowing from deeper zones. Its utility will be demonstrated using a real case history.
Automation of Safety Valve Travel Timing Delivers Business Value in the Caspian
Authors: Marinai Luca , Khetarpal Ajay , Grange Brett , Mackinnon George , Houghton Christopher 
Published: March 2012

Abstract
Over the last three years the BP AGT Region in the Caspian has deployed a new Field of the Future technology to automate the monitoring of safety critical valves' actuation time. This paper discusses the deployment of this tool, particularly focusing on the business value delivered and the lessons learnt. The Azerbaijan-Georgia-Turkey (AGT) Region is a BP organisational unit, operating a number of major upstream and midstream assets in Azerbaijan, Georgia, and Turkey, including six large integrated offshore platforms in the Caspian Sea, and three export pipelines.
Automating the monitoring of valves is not always included in the business case for intelligent oilfields, and the operations focus may be seen as less value-adding than some of the reservoir or well based applications, but the business value is clear. The operational prize is relatively easy to measure and capture when retrofitting to a brownfield site that has reached a steady state of performance. BP in Azerbaijan chose to initially deploy this technology about two years after startup, once the maintenance team's focus shifted away from post commissioning problems, and comparison to steady state operation was possible, and the application had reached maturity.
Detailed valve time tracking adds value by reducing the need to plan safety valve testing, if a plant shutdown occurs -planned or unplanned during the window within which procedures dictate a valve test must be conducted. In addition, the application provides performance tracking over time that might not be available from routine planned testing. The avoidance of yearly function checks has resulted in significant savings in manpower costs and plant outages and early warning of valve performance degradation can be acted upon before they result in failures.
Running this application in the Caspian has demonstrated business value to BP locally through improved reliability and reduced maintenance costs, and has resulted in the take up of this new technology across BP worldwide.
Field of the Future is a registered trademark of BP.
Seria North Flank: Development and Management of a Smart Field
Authors: Yong Ivan 
Published: March 2012

Abstract
Brunei Shell Petroleum (BSP) first started completing Smart Wells in 1999, trialing standalone technologies such as permanent downhole gauges and inflow control valves in individual wells. Once these were seen as successful, the technology was used extensively on a single platform. This was later extended to application in a whole field, taking advantage of refinements such as variable downhole control valves and multiphase flow metering.
Learning from the successes of other oil producing fields such as Champion West and Bugan, Seria North Flank was planned and designed as a fully Smart field. Seria North Flank would be the first field to fully integrate Smart technology with Smart field processes, improving the efficiency of Well and Reservoir Management activities and accelerating reservoir understanding in order to reduce uncertainties for future development. This resulted in the development of over 120 million barrels of oil, with improved Unit Technical Costs compared to an offshore development.
Review, Analysis and Comparison of Intelligent Well Monitoring Systems
Authors: Silva M. F. , Muradov K. M. , Davies D. R. 
Published: March 2012

Abstract
Intelligent Well (IW) technology has built-up several years' production experience. Numerous publications have described how remote flow control and monitoring capabilities can lead to fewer interventions, a reduced well count and improved reservoir management. Despite the maturity of IW equipment, the concept of the integrated IW as a key element in the "Digital Oil Field" still not fully developed. Today's practice is to evaluate the IW value chain in a "fit-for-purpose" manner rather than by an integrated modeling workflow. Reservoir engineers still struggle to convince their management of the IW's value, while the well engineer is only consulted immediately before completion deployment. Hardware and software interface problems result because appropriate technology was not selected.
An increasing variety of real-time, downhole, monitoring and measurement systems are now available for deployment or are in development. Sensors for high resolution pressure and temperature, high frequency pressure (acoustic), multiphase flow rate, phase-cut, electric potential (electro-kinetic), seismic (accelerometers) and casing condition monitoring (strain) are all now (at least semi-) commercial; not to mention the option of installing quasi-distributed and/or distributed rather than a single point measurement. The former sensors provide a wealth of information about flow performance and in-well and near-wellbore formation conditions. However, each extra sensor increases the well's installation complexity and operational risk. A well-founded understanding of what data is actually needed; the most suitable sensor types and interfaces together with avail liability of the necessary data reconciliation and validation methodology are key factors for the success of an integrated IW project.
This paper will review intelligent well monitoring systems, their availability, applicability and limitations. It will discuss data acquisition issues in-depth; e.g. resolution, data processing and reliability. Examples of fit-for-purpose sensor/data sets applicable to different IW applications will be given. This paper will guide the completion engineer to identify the appropriate set of downhole sensors for a specific, integrated, IW application.
Permanent Distributed Temperature Sensing (DTS) Technology Applied In Mature Fields: A Forties Field Case Study
Authors: Costello Craig , Sordyl Peter , Hughes Cledwyn , Figueroa Martin , Balster Emmanuel , Brown George 
Published: March 2012

Abstract
Permanent distributed temperature sensing (DTS) using fiber-optic technology provides measurements over the complete length of the fiber in the wellbore. The temperature profiles can be monitored at surface in real time, minimizing the need for production logs, preventing deferred production losses, decreasing well interventions, and reducing operating costs. This technology has been applied by Apache North Sea Ltd in the Forties field to monitor and optimize the performance of two wells producing by gas lift in the Delta platform and, at the same time, examine their completion integrity.
To accomplish these objectives, a hybrid fiber-optic electrical cable was installed in two Forties wells, allowing the continuous measurement of temperature and acquisition of pressure data from a downhole gauge located below the deepest gas-injection point. The combined benefit of reducing both the number of well interventions, and thus eliminating the associated QHSE risks, and the operating costs made this well monitoring strategy the appropriate one in this mature field.
The analysis and interpretation of downhole pressure and DTS data provided rapid feedback to the platform production team regarding the status of the well, allowing a better and more informed decision-making process.
In this paper, we outline the deployment of the hybrid DTS system and describe the analysis performed in each of the two wells. Data handling, analysis, and interpretation are described as well as the methodology and workflow for well monitoring and optimization using permanently installed DTS.
Improving Management and Control of Drilling Operations with Artificial Intelligence
Authors: Gola Giulio , Nybø Roar , Sui Dan , Roverso Davide 
Published: March 2012

Abstract
In oil and gas industries, drilling is a complex and critical operation which require constant and accurate real-time monitoring. To this aim, real-time models are required to provide an overview of the drilling operations when direct and reliable measurements are not available. Given the harsh operating environment, sensor reliability and calibration are critical issues and bad data quality is a typical problem which affects the accuracy of the model. As a result, the driller may be misled about the down-hole situation or receive conflicting claims about operating conditions. This paper presents two approaches based on the use of artificial intelligence to improve monitoring of drilling processes in terms of reduced uncertainty and increased confidence. The first exploits the aggregation of the opinion of different experts within a so-called ensemble approach; the second is based on a so-called grey-box approach which combines a physical model and artificial intelligence. The two approaches are applied to the problem of predicting the bottom-hole pressure during a managed pressure drilling operation to demonstrate the improved accuracy and robustness.
The Critical Role of Digital Data in a Drilling Performance Workflow
Authors: Dupriest F. E. , Pastusek P. E. , Prim M. T. 
Published: March 2012

Abstract
The paper will discuss the role of digital data in a performance management process implemented by the operator in 2005. The Fast Drill Process (FDP) has resulted in an 80% worldwide increase in average drilling footage per day since its implementation across 23 drill teams and numerous papers have described the workflow and specific operational practices (Dupriest, 2006, Dupriest et. al, 2010). However, the critical role of digital data within this process has not previously been discussed. Although FDP workflow is tailored to the operator's organization, there are many leanings discussed that are believed to be relevant to other data-driven field operations.
FDP is a continuous improvement workflow. As footage per day is increased, the next dominant factor limiting footage per day is identified and redesigned until some other factor becomes the limiter. The new limiter then becomes the object of redesign. Over a period of years, the pursuit of the next limiter has led to higher performance, but also to more complex operations. Continued gains have become increasingly dependent on the development of physics-based models and the collection of new types of data. We have observed a direct correlation between the level of data usage an operator can achieve at the rigsite and the drill team's performance.
This paper discusses some of the challenges that have arisen in deploying a data-driven workflow in an industry that has historically worked from empirical experience. Examples include actions taken to achieve the level of rigsite knowledge needed to sustain physics-based operations, steps taken to share critical data across global operations, the manner in which complexity impacts the use of digital data, and some of the specific types of performance limiters extended and new types of data that are being collected to support the physics-based models used to make the required real time decisions.
A Perspective for a National Oil Company to Transition from Traditional Organizational Management to a Digital Culture
Authors: Ershaghi Iraj , Al-Abbassi Adel 
Published: March 2012

Abstract
This paper presents transformational steps taken by a national oil company, KOC, and lessons learned to introduce the digital culture within its management and professional organization. The drivers were many, mostly emanating with the concerns for enhancing production of green fields, arresting production decline in mature reservoirs, minimizing workovers, enhancing health and safety issues with oilfield operations and reducing decision-cycle time by effective professional engagement of subject matter experts. Solutions required planning steps to unload the engineering task force from the burden of getting and managing information to deciding on options and consequence analysis presented by interpreted data.
The acceptance of transitioning to a digital culture was natural and intuitive among the top brass. They supported step changes for creating appropriate decision space, for developing and cataloguing work processes and for training staff. On the technology side some tasks identified were advanced measurement and telemetry technologies, data handling, access and analysis, information visualization, automatic control and integrated decision making. As a transition, the process started on three pilot projects each providing the training ground to transform the way subject matter expertise can be harvested within the entire organization. Experienced professionals from different assets were selected and trained for utilizing their expertise for team assignments related to multiple critical projects.
Accomplishment of this complex task within a national oil company is in principle a lot more complex than perhaps in the IOC's; but the vision communicated within the organization was effective in developing a successful roadmap to the transition.
Leveraging Technology and Support Infrastructure and Experience in Upstream Digital Technology Application
Authors: Killian Keith E. , Jones Chris G. , Nye Johan B. , Wiemers Suzan 
Published: March 2012

Abstract
Implementing digital technology in the oilfield introduces non-traditional technology, equipment and applications to our oil & gas operations. The long term success and sustainability requires the ability to support this technology effectively and efficiently. ExxonMobil* has a global, standard IT infrastructure. ExxonMobil's downstream has implemented a global, standard advanced control architecture and deployed a suite of applications to optimize various aspects of these operations. Leveraging this experience, infrastructure design and support structure has been recognized as a significant opportunity in the upstream to facilitate quicker deployment and benefits realization, and leverage proven support models. This paper shares ExxonMobil's approach with leveraging our existing corporate IT and advanced control technology foundation, experience and support models for upstream deployment of advanced digital technology.
Challenges in Managing People to Implement an Integrated Operations Systems: A Petrobras Case Study in An Operational Unit of Exploration and Production
Authors: Siqueira Cézar Augusto , da Cunha Vaney Nascimento , Meneghelli Regina Buzetti , Barreto Francisco Antônio , Sesma Ericsson Jussim , Simões Roberto Carlos 
Published: March 2012

Abstract
Integrated operations systems have been consolidated as an important management tool in the global oil industry. In this context, considering the objectives of reducing operating costs and investments, increasing recovery factor and, therefore, increasing production efficiency, Petrobras has begun to implement the Integrated Operations Management (GIOp) as a supporting element to achieve the long term goals of the company, as established in its 2020 Strategic Plan. The GIOp is an initiative of the Exploration and Production (E&P) branch at Petrobras. This initiative is guided by the articulation of technical disciplines and companies involved in operational activities, focusing on the proactive role, bringing quality and comprehensive view in the planning of operations. Its implementation is occurring in the operational units of the south and southeast regions of Brazil, an area that responds for more than 80% of national oil and gas production. As in other operating units of the Petrobras E&P, Operations Unit of Espírito Santo, responsible for the management of production assets in the Campos and Espírito Santo basin, began the process of GIOp implementation through pilot projects. The results obtained so far are considered positive; however, beyond all the technical challenges observed for system implementation, it is noteworthy emphasizing the importance of managing people in the process, an element that has been confirmed as relevant in the GIOp implementation of one of the pilot projects. This paper aims to highlight the main challenges in managing people for the implementation of an integrated operations system and to present the case study of the early implementation of GIOp in the Jubarte and Cachalote Asset, whose production fields are located north of the Campos Basin.