bluuebunny/crossref_metadata_2025_split huggingface dataset:
Keep Calm and Carry on: How Dynamic Modelling and Optimisation has Helped to Maintain Production across the Azeri-Chirag-Guneshli Field
Authors: Calvert Patrick , Pashayev Ahad 
Published: June 2014

Abstract
The Azeri-Chirag-Guneshli (ACG) field is a giant oil development located in the Azerbaijan Sector of the Caspian Sea. The presence of multiple layers and a secondary gas cap has seeded a range of transient phenomena that includes well slugging, cross flow and gas coning.
Dynamic transients seen across the field have contributed to a detrimental impact on production. Well slugging has led to the failure of downhole screens and decreased production. The cross-flow of water between the different reservoir layers is another problem that can increase the water cut by 30% during start up, making it extremely difficult to return a well to production. The gas to oil ratio (GOR) remains very dynamic. When shut in, gas will migrate away from the well bore leaving little free gas to lift the oil. Similarly, the GOR will rise during periods of production as gas is coned into the well. As a result production can be backed out.
Underpinned by extensive dynamic modelling work, BP, together with its Partners and the State Oil Company of the Azerbaijan Republic, has been successful in deploying technology to assist in stabilising and enhancing production across the ACG field.
Well uptime has been improved by optimising the dynamic transients during start-up. Conditioning the well before it is shut in has proved effective at reducing the cross-flow of water that occurs immediately afterwards.
In this paper, the challenge of optimising the dynamic transients across the ACG field will be discussed. Particular emphasis will be given to the solutions developed to address the underlying transient phenomena and how these solutions were deployed at scale and pace across the field.
Development of Hybrid Intelligent System for Virtual Flow Metering in Production Wells
Authors: Bello Oladele , Ade-Jacob Sam , Yuan Kun 
Published: June 2014

Abstract
The demands placed on operators to effectively manage production operations become more complex and challenging with increasing numbers of high recoverable oil and gas fields in frontier environments (remote onshore, deepwater and ultra- deepwater). Predicting flow rates of wells located in these frontier environments accurately is of great importance to enable asset performance monitoring, field surveillance, production accounting, production optimization, reservoir management decision, volumetric input to reservoir simulators and reservoir estimate tracking, though out the field life cycle. Although several studies have focused on real-time well rate estimation using physical multiphase flow meters, theoretical approach (mass, momentum and energy coupled with real-time field data) and artificial neural network models, little attention has been given to continuous flow rate surveillance based on hybrid intelligent systems. Hybrid intelligent systems combine intelligent techniques synergistic architecture in order to provide solution for complex problems. These systems utilize at least two of the three techniques: fuzzy logic, genetic algorithm and artificial neural networks. The goal of their combination is to amplify their strengths and compliment their weaknesses.
This paper presents a novel approach of using hybrid intelligent modeling technique, available time series field data and well configuration information to develop a virtual flow meter for production wells. The simulation results from the hybrid intelligent based virtual flow rate meter are compared to those obtained from real life field data. The validated model is used to predict future performance of existing wells. The effects of various parameters are performed to determine their impacts on the predictive accuracy of the new approach.
Cloud-Based Data Management in Oil and Gas Fields: Advances, Challenges, and Opportunties
Authors: Bello Oladele , Srivastava Deepak , Smith David 
Published: June 2014

Abstract
Use of automation, control and information technology for creating automated workflows and real-time assets management in the petroleum industry has rapidly grown in recent years. This integration of automation and communication produces large amounts of data, especially with optical fiber-based sensor systems and the need for providing real-time controls and optimization based on data-driven predictive analytics. The transition to the intelligent paradigm opens up new opportunities but also poses a number of challenges. Currently, most organizations are struggling to reduce their computing cost through the means of virtualization. This demand of reducing the computing cost has led to the innovation of cloud data management technologies. Cloud computing offers better computing through improved utilization, reduced infrastructure and maintenance costs, and increased flexibility to help meet changing business requirements.
This paper gives a complete overview of cloud data management systems and their usefulness. In addition, it highlights some of the general cloud data management technologies available in the market and describes some of the development trends. It also examines the current challenges and risks facing the cloud data management technology deployments and provides highlights on the business opportunities.
Real-Time Modelling of Drilling Using Nitrogen Enriched Mud: A Case Study
Authors: Cayeux E , Kucs R , Gibson N 
Published: June 2014

Abstract
This case study involves a well drilled in the Erbil area of the Kurdish Region of Iraq, a region characterized by challenging geological conditions for drilling. To achieve the key drilling objectives, the drilling mud was made less dense by the addition of nitrogen into the mud column. In order to get a full understanding of the downhole conditions using this mud, the complete drilling process was modelled in real-time. The model was driven using a real-time WITSML data feed. This transient modeling software calculates downhole pressures, temperatures, torque and drag and cuttings density at all depths in the well bore in real- time, including the depths where there are no physical measurements.
The transient model is continuously updated in real-time to reflect the drilling processes undertaken on the rig (e.g. pipe movement, mud pump activity, thermodynamics). Surface system variables including virtual mud pit levels are also calculated in real-time. The modelled data is then continuously compared to the sparse data points that are being recorded in real-time, allowing both a continuous calibration of the model with the "as drilled" well operation. The calculation of important drilling parameters such as sliding friction, rotational friction, and hydraulic friction is performed in real-time.
The paper will present the key observations upon the matches between the modelled data and the "as drilled" data and summarise the key lessons learned during the well operations and the real-time modelling processes.
Global Mnemonics: The Dual Challenge of Supporting Decisions and Users
Authors: Krupa James , Beach Jaynee , Stiffel Zoltan , Bharath Sharada 
Published: June 2014

Abstract
Historically the role of data aggregation storage systems has been to acquire and manage real-time drilling data in support of the viewing, analyzing, reporting and preservation of the information provided by service companies during drilling activities. When this practice is applied to all wells in a global organization and additionally available to multiple roles within an operating company the challenges multiply. Global Mnemonics (GM) provides a common mnemonic naming convention that overcomes those challenges. The GM concept attempts to provide a level of standardization to the real-time data acquisiton industry in the realm of naming measured data or computed paramenters. The intent is to allow useful information to be deduced from the names based on regularities. Several service companies supply real-time data services to the oil industry with each company displaying the same or similar data with different names.
This paper explores current applications of GM including the value of abstracting data away from acquisition point naming conventions within a real-time infrastructure. Additionally, we examine complex use cases which are improved by the use of GM. For example – some users only require a standardized real-time data management system to support the preservation of decisions. A completely different class of consumer of the information is looking to the real-time infrastructure to aggregate and abstract the data into the "best available" information at any point in time.
Are Machines Better Than Humans in Crisis?
Authors: Wilkins M. J. 
Published: June 2014

Abstract
There have been several well publicized incidents over the past few years in refinery and petrochemical facilities. Incident reports from amongst others, the Chemical Safety Board and papers from ARC and Marsh McLennan Insurance Company show that many of these incidents can be attributed to operational errors. On closer examination of possible actions during a crisis, such as mistakes due to confusion and time taken to understand the value of information being presented, it begs the question - "Are Machines Better than Humans in a Crisis". In fact, could technology provide better safety and business benefits? On November 4th 2010, Quantas Airlines flight 32, an Airbus A380, took off from Singapore to Sydney en route from London Heathrow. At the time, the A380 was the world’s largest and most technically advanced airliner.
Not long after take-off over Indonesia one of the engines exploded. The incident report said that had there not been five experienced pilots on board that day, the plane could have crashed. Thankfully they saved the aircraft which landed back in Singapore. The conclusion was that the balance of advanced technology and human thinking saved the day. In essence, in a stressful situation both humans and machines have a role to play. This presentation will discuss several plant incidents and see how technology could maybe aid the operator in a crisis and help him to focus on the problem.
Intelligent Energy: The Past, the Present, and the Future
Authors: Gilman Helen , Nordtvedt Jan-Erik 
Published: June 2014

Abstract
The first ten years of Intelligent Energy have been interesting and rewarding. The oil and gas industry has seen many successful IE implementations with significant value delivered. We have established improved communication and collaboration, and seen changes enabled by real-time data and new technologies such as predictive analytics.
However, we have not yet delivered the level and scale of transformation that was envisioned at the start. Our industry has moved more slowly at the same time as the "outside" world – our own homes and other industries – has moved much more quickly. As individuals, we consume information and communicate very differently from ten years ago – e.g., through online booking, social media, and the use of map-based solutions. There is an ease of connecting across the world and "things talk" 1 – but not in the oil patch to any large degree.
In this paper, and based on more than ten years of experience working exclusively with IE and with more than a dozen of the key industry actors, we will present an analysis of the IE domain, lessons learned and suggestions for where we should go from here. We will consider the reasons for our current state, attempting to answer why it might be more difficult to transform in the oil and gas industry than elsewhere 2. Why have some of the barriers been much bigger than we expected? The business case is as strong as it was ten years ago, the technology is more robust, and we have more young people in the industry as well as a higher level of acceptance of technology and change in our personal lives. So we should find it easier to make more rapid progress now than in the past. What must change to achieve that progress?
Use of Computational Fluid Dynamics Model for Evaluating Performance of High Pressure High Temperature Wells
Authors: Yuan Kun , Bello Oladele 
Published: June 2014

Abstract
The importance of performance monitoring is growing as the number of high-pressure, high-temperature (HPHT) wells continues to increase in deepwater and ultra-deepwater fields. Accurate prediction of HPHT well performance is essential for enhancing deepwater oil and gas production operations. Applying computational fluid dynamics (CFD) modeling to three- phase gas-oil-water flow in HPHT well conditions is an emerging concept. Multiphase flow in HPHT wells is extremely complex and depends on a multitude of effects including the properties of gas/oil/water, well geometries and configurations, operating pressures and temperatures, and multiphase flow patterns.
In this work, simulations have been performed for three-phase flow in HPHT wells using CFD modeling techniques. The calculated results for phase velocity, pressure and temperature distribution are discussed in detail. The CFD simulation results are compared with measured field data and a finite difference-based mechanistic model. Reasonable agreements are achieved.
Extensive parametric analysis of the three-phase flow system is performed to validate the viability of the CFD model as a predictive tool. The CFD model is demonstratively capable of predicting pressure drop and multiphase flow profiles in the HPHT well throughout various simulated production conditions. The experience gained from the CFD model studies can potentially improve the operations of HPHT wells in terms of increased productivity and enhanced reservoir management. In addition, results demonstrate the capability of the CFD model to predict various multiphase phenomena associated with HPHT well operations.
The Pace of Change: Can We Keep Up? A 35 Year Reflection and Projection on the Future of our Industry
Authors: Roberts Steve 
Published: June 2014

Abstract
35 years ago, when the author joined the industry, the tools of the trade were coloured pencils, ten point dividers, hand drawn maps and contours, with computers just coming onto the horizon. The fax hadn’t been invented, neither had the CD, the laptop computer or multi-terabyte hard drives. The method of communication was mainly via telephone or telex and the internet didn’t exist in the public domain. Computers were accessed quite remotely via a deck of cards, punched by a typing pool of coders, with most jobs running or failing overnight.
The pace of digital change over the last 35 years has been accelerating at a frightening rate. Faxes have come and nearly gone, so has the CD, and the main frame. It looks like the Desktop and laptop computers are in decline too. What will the next 35 years bring? How will we ensure that the oil and gas industry can continue to keep up with this accelerating pace of change?
This paper offers some thoughts on what might be coming next. More importantly, it offers approaches that might help the industry prepare and embrace the ever increasing pace of digital change, allowing the opportunities it provides to be incorporated in an industry where extraction technology changes relatively slowly and major investments last for decades. The paper discusses approaches to managing digital obsolescence and ‘future proofing’ to help anticipate and adapt to new digital technologies. The next generation coming into the industry will expect it to be operated in a digitally enabled way, otherwise they will go and work elsewhere. The paper proposes that there is no choice but to embrace the oncoming wave of digital experience and intelligence.
Managing Safety Overrides across your Upstream Business
Authors: Richardson David , Grange Brett , Hickey Greg 
Published: June 2014

Abstract
Safety trips are a key element of the safe operation of every facility. As a part of the Emergency Shutdown System, safety trips primary function is to shut-down a facility if any parameter is about to breach a safe operating limit. It is also necessary, however, that during abnormal operating situations these safety trips need to be overridden or defeated in order to facilitate operations which are not possible without the overrides in place. Common examples include starting up a facility and overrides configured for disused equipment. These safety overrides are often carried out as and when required for operational reasons and are not then subject to a rigorous permit to work process. When this happens, it is important to avoid unsafe situations which could increase the risk of incidents.
When safety overrides are applied, it is essential that there is a robust process for managing this to prevent unsafe situations arising. This process needs to be easy to implement and operate to ensure that the risk associated with overriding a trip is properly assessed. It must assure that the operating team are aware of the overrides and that this information is effectively transferred between shifts when they change. It must highlight the most important defeated overrides affecting current operations while ensuring that long term overrides are managed effectively.
This paper describes how BP has used the digital oilfield toolset to roll out a new standardised process for managing Safety Overrides to more than 10 assets in diverse geographical locations in the year after a new management process was published. It describes the approach of integrating the capability into the company’s standard logbook for control room operations to speed up the implementation and for ease of operation.
Trusted Operations--Integrating Operational Performance, Safety and Security Assurance
Authors: Jose S.J. , Arango G. , Flichy P. , Featherly J. 
Published: June 2014

Abstract
Industry reports identify human and organizational factors as contributors to operational incidents. These include lack of standardization, enablement, and compliance with operating procedures at the well site or by the broader (local or remote) support personnel. There is consensus among practitioners and regulators about the need to pro-actively reduce our exposure to these factors, both to avoid potential incidents and to reliably contain the impact of realized incidents.
In this paper we argue that we should improve operations assurance by building trust into our operations and we discuss how to combine existing principles, methods and information technology to achieve this in practice. The approach we will describe takes advantage of a framework developed by the HS&E profession--the "bow tie"-- to analyze what contributes to incidents, what barriers could be put in place to prevent them and how to contain them.
The diagram shows an abstraction of the bow tie model. The left side of the diagram (top event prevention) makes explicit the various threats we face during an operation, the precursor that signal the presence of a threat, and the preventive barriers--people, process, technology--that we should activate to avoid the propagation of the threat to become a top event(at the center of the bow tie). The right side of the diagram (top event response) makes explicit the response workflows that may follow an incident, the escalation barriers that we should activate to contain the impact of the incident, and the consequences that we would face if the barriers fail.
Addressing and Managing Cyber Security Risks and Exposures in Process Control
Authors: Pitzer Darrell R. , Girdner Ana M. 
Published: June 2014

Abstract
Management of cyber security risks and exposures in the industrial process control environment has emerged as an important and dynamic element in the operational safety, security, and reliability of the infrastructure in the oil & gas industry. In the last 10 years, the number and complexity of cyber security intrusions and malware infections has exponentially increased. In 2010, the entire threat landscape changed with the appearance of Stuxnet, which demonstrated that targeted attacks to control systems were not only possible, but very likely and very hard to defend.
This has prompted the industrial and commercial sectors to develop and continuously improve cyber security policies, programs, and procedures to address and manage the risks and exposures associated with these threats. Similarly, government sectors have launched programs, enacted cyber security laws, and developed policies, procedures, and standards to address the steadily increasing threats and vulnerabilities in the industrial control systems area.
The connected, digital oil field must include comprehensive and robust controls to protect against these risks and exposures. It requires continuously evolving and improving cyber security programs, and requires diligent, ongoing management to address evolving and advanced persistent threats.
This paper will provide an oil and gas industry insight into cyber security programs and countermeasures, and will share ExxonMobil’s* approach to cyber security in the industrial process control environment.
Permanent Downhole Flow Metering Improves Reservoir Management in Subsea Environment: A North Sea Case Study
Authors: Akil Ihab , Das Kaushik , Yunusov Manuchehr , Figueroa Martin 
Published: June 2014

Abstract
Development of remote offshore fields has unique technical challenges because quite often, such fields have only a few subsea wells tied to adjacent fields. This scenario is especially the case in small and/or marginal offshore fields where the profitability is very dependent on capital and operational expenditures. Therefore, quite often a group of marginal offshore fields located nearby are developed together with several gathering points and pipeline systems joining different subsea wells. Flow metering is usually performed at gathering points on the seabed using multiphase flowmeters rather than at individual wellheads. While this method can be very efficient from an economical point of view, it may, on the other hand, compromise the data acquisition process, resulting in an insufficient understanding of individual well performance. The situation may get even more complicated when wells from different fields are tied together. Because well interventions for individual well performance evaluations are generally expensive and not always possible, it is necessary to have a reliable and cost-effective permanent downhole monitoring system that provides continuous real-time data necessary for updating and improving the field development strategy.
This paper presents a case study of a subsea oil producing well in the North Sea where one such system—a venturi downhole flowmeter—was installed to obtain continuous pressure and temperature measurements for downhole fluid density and flow rate calculations. This type of flowmeter is useful only in liquid environments because the underlying Bernoulli principle is applicable only for single-phase flow and tenable in low-slip liquid/liquid flow regimes, such as in the concurrent flow of oil and water at high velocities. Surface flow rate validation is always a good complement but not compulsory. The goal of this cost-effective monitoring method was to facilitate production (oil and water) allocation so as to simultaneously improve well performance and reservoir modeling.
The continuous pressure and temperature data obtained from this downhole flowmeter were translated into valuable information during well flowing and shut-in periods. The application of specific workflows transformed the downhole data into fluid flow rates, which allowed to accurately evaluate performance of the well. Successful calculation validations were performed using a multiphase meter data due to the inability to test the well. The results allowed the operator to properly allocate flow, assess reservoir performance, and identify improvement opportunities in the field-development plan.
This case study demonstrates that with the installation of reliable, cost-effective downhole flowmeters and the appropriate interpretation of downhole real-time data, well performance evaluation and reservoir management strategy can be improved simultaneously in subsea environments where the risks are high and expenditures are tight.