bluuebunny/crossref_metadata_2025_split huggingface dataset:
Integrated Operations Implementation in Samarang Field
Authors: Abdul Razak Chik Adnan , Sayung Colinus Lajim , Ahmad M Zul , Wong Lee Hin , Muhamed Salim Muzahidin , Mohd Som Mohamad Kasim 
Published: June 2014

AbstractIncreased demand in production and recovery, advancements in technologies and the desire to collaborate expertise across multiple assets are changing the work process at many oil and gas companies. Integrated Operations (IO) program describes the process, performance improvement and transformation of Petronas Carigali (PCSB) production operations. The program aims to help PCSB to address growth, organization and environmental challenges by integrating new transformational technologies with streamlined work processes and enables the followings: Enables a more effective working environmentWork processes are streamlined and automatedQuality information is available and accessible across the organizationCollaborative expertise of multiple locations, teams and domains across distanceIntelligent alarms and alerts for continuous asset awarenessIncrease hydrocarbon production and recoverySamarang was the first field selected for end-to-end asset management IO project. Its implementation deliver objective and focus at the whole of the asset operation optimization through providing increasing levels of monitoring and surveillance, diagnosis, optimization and operations transformation in a way that fits PCSB's current IO state as well as future expansion plans.The case study has shown following benefits since its inception in 2011: An innovative parallel design process was invented to improve the efficiency and integrity of the design processAn Integrated Operations model was described and defined for framing, planning, design and execution of the projectHeightened monitoring and surveillance through installation and retrofitting of measurements and control devicesIntroduction of "Functional Base with Asset Mindset" collaborative working environment across multiple locations, team and domainsTotal asset optimization hybrid of steady-state and transient-state optimizationProduction enhancement and reserve improvement based workflowsThe goal of this paper is to describe the IO framework and underscore its benefits that can be drawn from the Samarang IO implementation.
Remote Field Management of Greenfield Assets in Australia and East Timor: Delivering Value by Automated Production Surveillance and Optimization Platform
Authors: Biniwale Shripad , Trivedi Rajesh , Tran Andrew , Derrij Joseph , Yokote Ryosuke 
Published: June 2014

Abstract
Eni Australia is operating the Blacktip gas field offshore Australia and Kitan oil field offshore East Timor. The main challenge was to manage these green fields remotely, with lean resources and strict deadlines covering tasks like data capture and acquisition, data validation, application integration and field analysis efficiently. The implications of the decisions made during the development of a green field are imperative to the optimization of reservoir production. Therefore, an integrated production decision support system was required for performance monitoring of asset health and optimizing production to meet the targets.
This paper describes how these challenges were overcome at Eni Australia by centralizing the operations of both fields into a standardized production platform, providing a seamless data transfer from offshore assets to the onshore technical office and establishing the foundation towards a digital oilfield. The platform framework automates the process of acquisition, transfer, conditioning, aggregation and storage of production and operations data into a secure centralized data repository with an auditable amendment history. The production platform provides improved operational and reservoir visibility, which forms the basis for all subsequent analysis and underpins the engineering justification to support operational decisions.
The current solution framework provides a multifunctioning system that can be expanded for future assets and fields as they come online by leveraging the investment in the existing system. All the domain experts, from production operations to reservoir engineering, will have the required information at their fingertips for collaborative decision making. Thus, a centralized production platform provides engineers with an improved field visibility for remote field management, proactive decision making and help them to strategically develop fields by optimizing production.
Field Management by Proactive Optimisation of Intelligent Wells - A Practical Approach
Authors: Haghighat Sefat Morteza , Muradov Khafiz , Davies David 
Published: June 2014

Abstract
Intelligent wells (I-wells) are one of the core elements of the "digital oil field". Numerous publications have described their ability to simultaneously increase recovery and "Add Value". Maximum "Added-Value" is achieved via operation of the wells’ zonal flow-control valves in a manner that respects the field’s optimisation objectives at both a Well (short-term, Reactive control) and a Reservoir (long-term, Proactive control) level.
Relatively simple, well-proven algorithms are available for Reactive (mainly well out-flow) control. By contrast, techniques for Proactive control (or reservoir fluid front displacement management) are much less mature; despite them being capable of delivering greater "Added-Value" in many reservoir scenarios. Coupling Genetic Algorithms (GA) with a commercial reservoir simulator is the most commonly used Proactive optimisation technique (Alghareeb et al., 2009, Almeida et al., 2010, Pinto et al., 2012). However, GA has not achieved universal acceptance since, like many other optimisation algorithms, it either fails to find the maximum production improvement and/or requires excessive computational time and resources due to the large number of control variables associated with the optimisation process.
This paper discusses the use of the parallel Simultaneous Perturbation Stochastic Approximation (SPSA) algorithm for Proactive optimisation of an I-well in a simplified, real field. The algorithm’s parallel processing capability speeds-up the optimisation process when appropriately employed with a commercial reservoir simulator. A properly tuned SPSA algorithm was found to rapidly converge to a near optimum solution. Algorithm tuning by the engineer was shown to be aided by use of a novel, multi-dimensional, projection scheme to visualise the algorithm’s performance and monitor its progress towards the global optimum solution.
Computationally, SPSA is significantly faster (3 – 5 times in the examples tested to-date) than GA. This decrease in processing time can significantly increase the practicality of introducing proactive optimisation for large real field models on a routine basis where it is used alongside the more commonly applied reactive control strategy for managing the individual well performance (Yeten et al., 2002, Grebenkin and Davies, 2012).
Real-time Evaluation of Acid Stimulation Performance in Extended-Reach Carbonate Wells with DTS-enabled Intelligent Completions
Authors: Wang Xiaowei , Bussear Terry R. 
Published: June 2014

Abstract
Our industry has long searched for a means of evaluating the efficacy of acid stimulation of extended reach carbonate wells. Intelligent completion architectures and technologies have enabled the pre-compartmentalization of these wells, and delivered the means to selectively and remotely control zonal inflow/outflow along with the ability to make real-time measurements within these zones. This paper describes the development and in-well usage of a unique modeling technique combined with a Distributed Temperature Sensing (DTS)-enabled intelligent completion system to evaluate the coverage and effectiveness of intra-zonal acid stimulation.
This system leverages a proprietary thermal model that accounts for three in-well thermal effects occurring during compartmentalized bull-head treatments. The technique quantitatively evaluates the acid distribution and acid-rock interaction in each treated zone. The acid distribution measurement can be generated immediately following the acid treatment, enabling real-time determination of the acid volume and its distribution within the target completion interval(s). The operator can then decide if retreatment(s) is needed.
The paper focuses on the modeling technique for matrix acid stimulation in which acid is delivered by bull-heading down the tubing string to each pre-compartmentalized zone where sliding sleeves have been positioned at the lower end of each zone. The flow of acid into the tubing/perforated-casing annulus thus produces a counter-flow condition (within the annular space) to reach all perforations within that respective zone. A direct measurement of acid movement and placement is immediately generated based on a full-length DTS measurement within each zone during treatment. The paper also demonstrates the capability of the system in the generation of a type-curve. The operator can then qualitatively identify the under-treated or over-treated sections by comparing the DTS measurement results to the type-curve. A synthetic case study is used to demonstrate the technique. Full field applications using this model will be discussed in a future paper.
Bringing ESP Optimization to the Digital Oil Field: Rockies Field (USA) Case Studies
Authors: Ratcliff Dustin , Cetkovic Ivan , Gomez Cesar 
Published: June 2014

Abstract
Marathon Oil operates several brownfields in the Rockies, most of which are approaching an operating life of 100 years. To optimize the production from these mature fields, Marathon Oil is implementing several technology upgrades under the banner of the digital oil field—using information technology innovations to better monitor, record and analyze field data for faster and more informed optimization decisions.
One area receiving particular focus is the artificial lift method of electrical submersible pumps (ESPs). In 2010 Marathon Oil began installing downhole sensors in all ESP wells that were pulled for either a failure or a workover and downloading the data into an ESP real-time monitoring, diagnosis and analysis software system. The system brings intelligence to ESP operations by monitoring pump data from each well in real time, and collecting this data in a central location. The operator can then select from different software tools—also centrally located—to analyze the information, verify ESP operation within required parameters and if necessary, decide how to change the operating parameters to improve pump performance and boost production. The system also can be set with alarm capabilities to provide real-time notification of a problem.
The intelligent capabilities of the system plugged into Marathon Oil’s digital oilfield architecture help field engineers work smarter and more efficiently. Instead of spending needless hours travelling from field to field to monitor pump performance, engineers are notified of problems early and receive instant verification of field performance. The system minimizes nonproductive time (NPT) and frees up the field crews to work on other projects designed to increase production.
This paper provides several case studies that highlight through a digital oilfield solution how an intelligent ESP-optimization option is identifying problems early and extending the economic production life of Marathon Oil’s mature fields in the Rocky Mountain (Rockies) region of the United States (US). At the time of this paper, Marathon Oil installed downhole sensors in more than 430 of its 770 ESP wells, which are all presently being monitored via the ESP real-time monitoring and analysis program. Within this short period of real-time monitoring, Marathon Oil has realized production gains of over 700 Barrels of Oil per Day (BOPD) in one of the fields.
The Process Control Aspects for Well Head Control
Authors: AL-Mawali Salim 
Published: June 2014

Abstract
Feedback control is not new in the Exploration and Production (EP) industry. Almost all the units in a hydrocarbon production station are controlled with an automatic controller of some sort. However, the above statement does not hold true for any equipment outside the boundaries of production stations such as production wells and injection wells. The aim of this paper is to focus on an area that has been for a long time considered outside the process control engineering domain. Driven by positive trials with clear demonstrated benefits, this picture is changing at Petroleum Development Oman (PDO). This paper will show how simple control schemes are having a great impact on PDO’s oil production optimization and gas constraint reduction with the minimum of cost. The paper will present two utilizations of such control schemes and how much value PDO is reaping from these two implementations. The first is employed on production wells that exhibit an unstable behavior and the other is used for water injection systems. Finally, the challenges facing these technologies are discussed.
Model-Driven Development for Safety-Critical Projects in Intelligent Energy
Authors: Fechtelkotter Paul , Bleakley Graham , Douglass Bruce Powel , Amaba Ben 
Published: June 2014

Abstract
A responsive organization is one whose engineering processes and platform can sense and respond with flexibility, accuracy, precision, and speed to macro trends impacting the energy industry, including increased complexity, rapid adoption of new technologies, increasing use of Engineering, Procurement and Contract Management (EPCM) companies, modularity, internationalization of supply chains, and new regulatory mandates, while constantly improving operations and capital efficiency. IBM has developed an engineering approach and platform that will improve the transformation to Digital Intelligent Energy. The approach and platform reuses best practices harvested from adjacent complex, safety-critical industries. This paper describes Model-Driven Development (MDD) for Safety-Critical Projects using analysis and assessment of instrumentation, control and embedded technologies.
MDD allows organizations to first analyze problems and then derive and evaluate potential solutions using various analytical techniques, including simulation, prior to final decision-making. Stakeholder needs are verified and validated in a formal manner, creating a common understanding of the requirements. Graphical representations of the requirements improve communication by breaking down barriers between domains, better aligning the process and organization as understanding between the domains improves. This reduces the number of issues encountered when commissioning an asset, leading to reductions in cost and schedule risk. This approach has been applied successfully in many safety critical industries, including aerospace, defense, nuclear, automotive and medical devices.
IBM has been successful in helping companies manage through this change process and has codified our knowledge in a series of best practices applicable to any organization. Working in a strong partnership with the organization, our approach is to first understand the capabilities of the organization, how it operates, and then extends the analysis to its future needs, resulting in a roadmap for the transformation from the current practices to the future state. By leveraging this approach, we have changed the operating philosophy of many companies, improving their efficiency, effectiveness, and profitability.
A New Intervention-less Completion System using Radio Frequency Identification (RFID) Techniques
Authors: Yuan Feng , Blanton Eric , Mason Jane , Murdoch Euan 
Published: June 2014

Abstract
With the increase in drilling activity in new subsea and deep water exploration and development, a reliable means of intervention-less completion technology has become a major consideration in helping to reduce operational risk and achieve economic exploitation of new hydrocarbon reserves. Although intelligent completion methods have been in use for some time, the communication system they require can be expensive and time consuming and the need for a simpler, more cost effective, method of intervention-less well completion and management is clearly an attractive option.
To simplify the completion process, a new system has been developed which uses the well tried and trusted communication method known as Radio Frequency Identification (RFID). RFID is a reliable well proven technology which is used in countless applications in daily life; however its applicability to the oil and gas industry is only now beginning to be recognized. In this system tubing mounted control modules, which are capable of performing a number of key completion operations, are activated by simply dropping and pumping down RFID tags or, where pumping down is not possible, by the application of pressure cycles.
This system consists of several primary components as follows: Battery powered control module with antenna and processors, motor, pumps and closed hydraulic reservoir.A circulating control valve functioning as a sliding sleeve.A hydraulic set packer.A barrier valve.
Using these modules all the operations involved in an upper well completion can be performed free of interventions.
This paper will give an introduction of RFID technology and present operational mechanism in detail for key accessories of this new intervention-less completion system; and also display one typical logic application of sequence of operations for a new intervention-less upper completion system.
IOR / EOR Operations: Can the recent developments in Intelligent Wells Technology Advance the concept?
Authors: Ahmed Usman 
Published: June 2014

Abstract
The short answer to the question if the recent developments in Intelligent Wells Technology Advance the concept of IOR /EOR operations as posed in the title is "yes". However, lets’ explore and allow the reader to decide for themselves. IOR / EOR operations and projects in general are expensive in nature and any cost saving opportunity and process optimization is welcome. This is the premise of this paper.
More than 70-80% of the world’s remaining conventional reserves are contained in fields that are already on production. IOR and EOR methods are needed to access even a fraction of these remaining reserves. Deployment of Intelligent wells and associated monitoring and maintenance in conjunction with IOR and EOR processes can be expensive and as such has been restrictive only to high end operations. The industry is faced with the dual edge sword syndrome: enhance productivity with lower cost system. This translates to the need for deploying efficient systems to monitor IOR / EOR operations. This paper specifically addresses this topic.
One of the ways to address the above scenario is to come up with an extremely reliable system that is electronic and IP based rather than hydraulic (the current tradition) to address the intelligent monitoring and control. Combining such system of data monitoring with the most up to-date reservoir simulation system using the Jewel Earth platform that allows the use of unstructured gridding can result in fast and accurate response to reservoir monitoring and response with the ultimate goal of enhancing the reservoir recovery factor. The paper uses field examples to illustrate the features as described.
A Real Case Study: "Efficient Monitoring and Evaluation the Superficial Production Network" - Litoral de Tabasco Asset
Authors: Mijares F.. , Molina E.. , Escalona C.. , Montes De Oca L. A. , Jageregger W.. 
Published: June 2014

Abstract
The Litoral de Tabasco Production Asset (APLT) in Pemex southwest marine region has a technological solution of automated workflows which allow the operations department, captures all operational conditions, volumetric wells, production facilities and equipment. Furthermore, meters asset allows the generation of operational daily reports, as well as the integration of engineering workflows to estimate the production of wells daily and detection of faults of production in the wells that are published promptly on panels for monitoring the well production.
In order to support the current processes and future growth plans of APLT and standardization in nationwide PEMEX in the processes of both departments, Wells Operation (COPIE) and Design (CDE), a network model is created to integrate to existing operation data base which allows automating workflows to estimate production parameters, to evaluate scenarios and detect faults under current operation conditions.
The technological solution measures the impact caused by schedule shutdowns, increases or reduce the production in the pipelines, changes in the philosophy operation of network, incorporate the production in the flowline, backpressure or bottlenecks and provide an alternative method to estimate flowrates and pressures in each network node.
The interconnection with the existing operational data base permits the automatically update the network model, this process analyses the production facilities conditions continuously, as well as support assessment of development scenarios in order to generate recommendations to maximize profitability the Asset.
Deepwater-Reservoir Characterization by Use of Tidal Signal Extracted From Permanent Downhole Pressure Gauge
Authors: Wu Xingru , Ling Kegang , Liu Dexin 
Published: June 2014

Summary
Permanent-downhole-gauge (DHG) technology has been used widely in deepwater-reservoir development in the last decade and is playing an increasingly significant role in real-time reservoir/well surveillance and management. Tidal signals extracted from this highly accurate and precise device can be used for reservoir characterization such as monitoring the changes of saturations and estimating rock/pore compressibility. Most previous works have treated tidal signals as pressure "noise," and little has been discussed on how to use tidal information in reservoir characterization.
This paper will address how to use the fast Fourier transform (FFT) to extract tidal signals and the theories and methods for processing the signal to achieve reservoir characterization. In addition, a couple of examples from a deepwater field will be discussed to illustrate how to use tidal information to estimate pore compressibility, monitor dynamic fluid-saturation change, and detect the presence of a secondary gas cap. This paper will show that FFT is a fast and reliable method for processing the DHG pressure data for tidal signals that can be used for reservoir characterization in multiple dimensions. Furthermore, the results (pore compressibility and saturation) obtained from the tidal signals are unique because they cannot be obtained in the laboratory, by simulation, or by direct measurement because of the scale affected by tides.