bluuebunny/crossref_metadata_2025_split huggingface dataset:
Drilling Better Wells Cheaper and Faster
Authors: Brooks Robin , Wilson John 
Published: February 2008

Abstract
The control of a drill in realtime is demanding on the skills and experience of the drill operator and is variable across operating shifts because different operators have different levels of skill and experience. A mathematical model that could be shared by operators would eliminate this variability but few, if any, exist because of the mathematical difficulty and considerable expense of creating such a model in the first place and then of updating it as geology and hole depth and the type of drilling changes.
This paper describes and demonstrates a radically different approach and a solution to the problem by modelling the operating envelope of the drill operation as a multi-dimensional solid object so that the operating problem becomes a geometric problem of operating always as an interior point of the envelope. The beauty of this approach is that the model developers and maintainers do not need any mathematical knowledge or the ability to describe problems with algebraic or differential equations. The method is able to create models of high dimensionality using the original process variables only so is easily understood and accepted. It is well-placed for realtime exploitation of the increasing number of down-hole measurements. The geometric basis of the model makes the operating advice that it generates intrinsically safe. A realtime operator guidance model will be developed and shown during the presentation to show the concepts, mechanics and possibilities of the method.
The method is part of the overall technology known as Geometric Process Control (GPC) which is becoming well-established in downstream process industries and has already achieved success in problem-solving and offshore process improvement applications with several major North Sea operators. It has won awards for Innovation from EPSC, IChemE, IET and the CIA (Chemical Industries Association).
Alto do Rodrigues GeDIg Pilot—Case Study for Continuous Steam Injection Recovery Combined with Real-Time Operation
Authors: Lacerda G. M. , Patriota J. H. , Pereira J. I. , Torres J. S. , de Lima L. A. 
Published: February 2008

Abstract
Alto do Rodrigues (ARG) is an onshore heavy oil brownfield with continuous steam injection recovery located in the Rio Grande do Norte and Ceara Business Unit in the Northeast of Brazil and it was chosen as a pilot in Petrobras corporative program for Digital Integrated Field Management - GeDIg.
The ARG pilot consists of on-line monitoring of bullhead temperature of producers and injector of five spot networks connected with steam facilities measurements such as pressure and steam quality. The real time operation is combined with two collaborative environments integrated with SOLAR, an in-house development collaboration software.
Reservoir heterogenerity analysis like steam channeling is provided when steam generators parameters, well instrumentation, and historical data are combined in new workflow processes of steam analysis. Change management associated to process mapping guided the pilot implementation to minimize the side-effects of new process absorption.
The objective of this paper is to present the methodology and results from Digital Integrated Field Management in the onshore heavy oil brownfield of Alto do Rodrigues.
Application of Intelligent Well Completion for Controlled Dumpflood in West Kuwait
Authors: Rawding J. , Al Matar B. S. , Konopczynski M. R. 
Published: February 2008

Abstract
This paper describes the philosophy and design of an intelligent well installation in a water dumpflood well in Kuwait and analysis of data gathered. The paper examines the reservoir management capabilities of intelligent wells can lead to significant value in terms of reservoir management in this application.
Dumpflooding, the method by which fluids from one formation are allowed to flow into another formation, has been used for several years in Kuwait as a means of providing reservoir pressure support. Typically, a well is drilled to penetrate both a prolific aquifer and a producing oil reservoir. Under the right conditions, with a higher pressure aquifer, significant quantities of water flow from the aquifer to the oil reservoir.
As production from the oil reservoirs matures, this uncontrolled method of pressure support has led to several reservoir management challenges, including difficulties with flood front control, water breakthrough, conformance management, and inability to quantify the crossflow rate in each well. With declining oil reservoir pressure, the pressure differential between the aquifer and the oil reservoir has increased, leading to destabilization of the aquifer reservoir clastic matrix from excessive drawdown and high flow rates during perforating operations.
In early 2007, a West Kuwait well was completed as a controlled dumpflood well utilizing intelligent well technology. Water from the Zubair aquifer formation flows to the Minagish Oolite oil formation in a controlled and monitored dumpflood process. Utilizing a variable interval control valve, the amount of injection fluid is regulated, while permanent downhole monitoring devices transmit pressure data to surface, enabling evaluation of the flow rate. The intelligent well also permits "soft starts" of the dumplood to avoid borehole destabilization.
The methods described in the paper may be considered for improved reservoir management on a field wide basis wherever dumpflooding is used for pressure maintenance.
Reservoir Surveillance, Production Optimisation and Smart Workflows for Smart Fields—A Guide for Developing and Implementing Reservoir Management Philosophies and Operating Guidelines in Next Generation Fields
Authors: Konopczynski M. R. , Ajayi A. 
Published: February 2008

Abstract
Many oil and gas companies are joining the wave of forward looking operators implementing intelligent well and smart field technologies to improve their ability to optimise production, minimize expenses, and improve reserve recovery. Much has been written about the application of these technologies and steps to successful installation of the hardware. But the real value of intelligent wells and smart field systems come from the ongoing exploitation of the new technology in day to day operations. This paper compares the methods of reservoir surveillance and production optimisation in the "old world" to those of the next generation intelligent fields. Successful exploitation of the new technologies requires an understanding of information flow, control and automation capabilities, knowledge management, interpersonal communications, and decision processes to develop performance indicators, workflows, philosophies and protocols suitable for the fields of the future.
Three core elements are explored in the intelligent field workflow: the reservoir management philosophy, the production surveillance capabilities, and the operating guidelines. The requisite components of these elements are reviewed in the context of intelligent field capabilities. The concept of intelligent well and intelligent field optimization is explored examining the most recent developments in proxy modeling and feed-forward control technologies applied to well and reservoir management.
The value of these new optimisation tools will come not just from fine tuning of steady state conditions, but more likely from being able to react quickly to changes in operating conditions, whether reservoir, well or facilities related, to find optimum production solutions in near real time.
The concepts discussed in this paper are applicable to all intelligent well and smart field applications, particularly to those planning to implement "real-time" reservoir optimisation strategies. The information presented will provide a roadmap for the development of these strategies and protocols in the context of the smart field environment.
Rapid Model Updating with Right-Time Data—Ensuring Models Remain Evergreen for Improved Reservoir Management
Authors: Webb Stephen J. , Revus David E. , Myhre Angela M. , Goodwin Nigel H. , Neil K. , Dunlop B. , Heritage John R. 
Published: February 2008

Abstract
History matching reservoir models to production data has been a challenge for asset teams since the early days of reservoir simulation. Keeping these models evergreen as production data continues to arrive, knowing when a re-history match is required and being able to re-history match easily and efficiently is also a major challenge which is often not addressed in a timely manner. This need is becoming even more pressing as real-time reservoir performance data is increasingly available. Decisions can now be made with the support of the good quality real-time data from the reservoir usually in the form of pressure data from downhole gauges and rate data from multiphase meters.
With the recent integration of existing technologies, a rapid model updating workflow is now possible. The history matching workflow that was once a discrete process can now be a computer assisted continuous process. Using statistically-based assisted history-matching technology in conjunction with real-time data acquisition, data monitoring, and reservoir simulation software, new production data can be quickly assimilated into the reservoir model. Real-time data from the field measurement devices is filtered for consumption by the reservoir modeling software and compared with the forecasts from the reservoir simulator to determine if re-history matching is required. The new data can be added to the history file and the model (revised if necessary) can be used in operational performance optimization.
This rapid model updating workflow can be run semi-automatically on a continuous basis as new production data is gathered, thereby keeping reservoir models evergreen and providing the most up-to-date basis for the making of important reservoir management decisions.
Tap into the "Creativity of the Crowd"!
Authors: Paylow K. , Guidry A. , Braley N. 
Published: February 2008

Abstract
Many papers inside and outside our industry have discussed tapping into the ‘wisdom of the crowd' to meet organizational needs. Many papers have also discussed the need – and methods – to innovate. So perhaps we need to ask ourselves how we can tap into the ‘creativity of the crowd' to better understand what needs to change, identify opportunities for improvement or new market spaces to explore, share technologies across disciplines and industries and attract new types of talent.
Cultivating and supporting innovation can be a significant challenge within any organization. Empowering people to generate new ideas should be a part of successful business organization. One should be mindful that innovation knows no boundaries and can happen for anyone at anytime. This becomes apparent within each of us when we ask "What if…?"
There are several challenges in capturing these innovative thoughts in the proper context and putting them in front of the appropriate audience. This includes creating a mechanism for stakeholders to share their ideas, a process for management review and monitor submissions, the ability to bounce ideas off the ‘wisdom of the crowd' and tools to connect the R&D effort to stakeholders throughout the development process.
We have addressed this challenge through the creation of an IDEA system and using existing knowledge management tools to affect the development and commercialization process. The approach allows the entry and tracking of submissions through the process while maintaining intellectual property security.
This paper discusses cases where these new tools and processes effectively managed and nurtured innovation within and between product service lines. Typical barriers that have hindered end users from sharing innovative ideas will be highlighted along with solution measures utilized. Finally, areas of future exploration related to the effort will be identified.
Real-time Access to Expertise: Improving decision making and collaboration through unified communications
Authors: Munro Michael 
Published: February 2008

Abstract
The days of easy oil have gone. It is harder and harder to replace world oil reserves, requiring all the skills possible to find and extract hydrocarbons. Now, more than ever, decision making is critical to the success of exploration and production. And decisions made by experienced people who understand the complexities of each situation, colored by their years of activity and exposure to global conditions are the best suited for making those decisions. The expertise that they bring, coupled with a nuanced view of their current environment allows them to make better decisions, bringing reserves online faster with less cost, and improves ultimate field efficiency.
But the people with the best skills and experience, the ones that can best make those decisions at the point of activity are becoming scarce. Additionally, an expertise gap exists between the experienced workers who are getting ready to retire and new workers the industry has hired. This gap, plus shortages of rigs and crews to support the rigs are requiring new ways to staff them, a way to "virtualize" the expertise by placing them in centralized operations centers and have them support multiple physical operations.
So this brings us to the overarching question: "How do we connect the experts to the problem, provide them with complete awareness of the remote environment, and let them collaborate and share information in real-time with those who need that expertise?"
The answer to this lies in the ability to create a platform of connectivity that enables you to bring the problem to the expert, provides a complete picture of the context of the situation, and ensures seamless collaboration between participants regardless of their location. We call this platform, Unified Communication…the ability to transform the collaboration experience and provide real-time access to expertise.
This paper will explore that capability and provide examples of how exploration and production companies are leveraging convergence in communications to allow data voice and video collaboration between experts and explore the value that it brings. Specifically: Improving ad-hoc interaction by identifying expertise in real-time, connecting with them in the context of the operational workflowExtending transactions to interactions to allow transformation of workflows that have person-to-person collaboration inherent to their performanceIntroducing real-time decision making and new business models by leveraging this new platform of communication and collaboration
This paper will include various case examples of where exploration and production companies are creating these experiences, as well as examples from other relevant industries.
Decision Support System for Economic Analysis of E&P Projects under Uncertainties
Authors: Túpac Y. J. , Lazo J. G. , Faletti L. , Pacheco M. A. , Vellasco M. M. B. R. 
Published: February 2008

Abstract
This work presents the conception, modeling and development of an E&P projects economical analysis system under uncertainty that integrates the following modules: –an optimization hybrid system for oilfields development based in evolutionary algorithms with distributed evaluation, proxies and use of quality maps to optimize the place and quantity of wells in a delimited petroleum field to maximizing the NPV of the alternative. Also, this system considers some technical constrains as the minimum wells distance and maximum wells trajectory.–a model based on Genetic Algorithms and Monte Carlo simulation designed to find an optimal decision rule for some oil field development alternatives obtained from previous module, considering market uncertainty (oil price), that may help decision-making with regard to: developing a field immediately or waiting until more favorable market conditions.
In the economic analysis also is considered, for each alternative under evaluating, the option of investment in information taking in account interactions of different uncertainties types. This analysis considers the option of future production expansion by installing an additional well under reserve volume uncertainties in the in the area to be drained by the additional well.
Some computational intelligence techniques were applied in this system as: evolutionary algorithms, neural networks and fuzzy numbers; also, the system uses other techniques as Real Options and Monte Carlo Simulation to treat uncertainties.
The obtained outcomes show the benefits to have an integrated decision support system to the decision-making in the economic analysis of oilfields development.
Semantic Web Technologies for Smart Oil Field Applications
Authors: Soma Ramakrishna , Bakshi Amol , Prasanna Viktor , DaSie William J. , Bourgeois Birlie 
Published: February 2008

Abstract
In model based oil field operations, engineers rely on simulations (and hence simulation models) to make important operational decisions on a daily basis. Three problems that are commonly encountered in such operations are: on-demand access to information, integrated view of information and knowledge management. The first two problems of on-demand access and information integration arise because a large number of, and different kinds of simulation models, each modeling a different facet of the oil-field, are used. An engineer is generally an expert in one aspect of oil-field modeling and trained to use a few tools; therefore, accessing information captured in models that do not lie in an engineer's area of expertise is not easy. Moreover, since these models are created by different processes and people, the same information is represented differently across models. A unified view of the models and their simulations is desirable for decision making, and thus the necessity for information integration. In the third problem- knowledge management problem, we address the situation in which an engineer performs many analyses before making a decision. A systematic way to capture the rationale (knowledge) behind the various decisions is needed for audit tracking purposes as well as for future references. We examine the application of semantic web technologies to address these three problems, present a prototype implementation which addresses them and provide an evaluation of the technology.
A Framework for Design Space Exploration in Oilfield Asset Development
Authors: Zhang Cong , Bakshi Amol , Prasanna Viktor , Da Sie Will , Bourgeois Birlie 
Published: February 2008

Abstract
Design space exploration (DSE) is a common yet complex workflow in oilfield asset development. The "design" of an oilfield refers to a set of decisions about aspects ranging from well locations and number to facility sizing for optimum production. Evaluation of alternate designs – based extensively on reservoir simulations – corresponds to the evaluation of alternate development scenarios in face of uncertainty about subsurface structure and properties. The outputs of DSE influence many decisions in the development phase of an oilfield as well as operational decisions in a producing asset. In this work, we design and implement a generic framework to support DSE workflows in oilfield asset development. Our framework provides tools and services to allow rapid specification and evaluation of multiple design candidates using multiple realizations. The framework also supports hierarchical DSE workflows that allow users to first explore a large design space using proxy models and selectively refine the simulation quality of a smaller subset of designs via fine grained, detailed simulations. The usefulness of this framework is demonstrated through a case study that considers the design problem of selecting a drilling schedule for wells in an offshore oil and gas field.
IT Security and Architecture for Integrated Operations: Examples from deliveries to Ormen Lange and Draugen
Authors: Aarset Marius F. , Mo Olav 
Published: February 2008

Abstract
The introduction of Integrated Operations causes a demand for integrating process control systems with office systems. A secure and reliable connection between these systems enables considerable cost savings related to: Process OptimizationMaintenanceCollaborationRemote support
Shell operates two oil fields on the Norwegian Continental Shelf; Draugen and Ormen Lange. Draugen is an established oilfield having been in operation since 1993. Ormen Lange is a new gas-field based on subsea installations remotely operated from an onshore process plant.
In implementation of a technological basis for IT Architecture and Security supporting Integrated Operations, certain products and services are essential for achieving the ambitious expectations. The technological basis may be separated in three fundamental areas: Establishment of plant Security Policies, a management tool for establishing plant security.Design of a Plant Network, which will facilitate communication between the office and process control networks, and communication with other subsystem networks.Implementation of Remote Services, a solution for a secure connection between the Plant Network and the office network.
IT security is a major issue when integrating office systems with process control systems. Corporate, national and international standards must be adhered to, and good technical and procedural solutions must be developed. The technological nature of the underlying process control systems must be addressed when an architecture for integration is created.
Both Draugen and Ormen Lange have recently been designed to facilitate Integrated Operations according to Shell requirements, integrating information from various subsystems and making real-time data available in Shell's newly developed collaboration centre in Kristiansund, Norway. The collaboration centre will provide operational support to Draugen and Ormen Lange, and is part of a collaboration network in Shell Europe. Remote services are established enabling remote access towards vendor support centers, as the ABB remote operations rooms for Ormen Lang and Draugen.