Systematic Decisions Under Uncertainty: An Experiment Towards Better Geosteering Operations

2021 ◽  
Author(s):  
Sergey Alyaev ◽  
Andrew Holsaeter ◽  
Reidar Brumer Bratvold ◽  
Sofija Ivanova ◽  
Morten Bendiksen
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Controlled Environment ◽  
Full Potential ◽  
Time Data ◽  
Decisions Under Uncertainty ◽  
Winning Strategies ◽  
Operational Decision Making ◽  
Quality Decision ◽  
Further Development

Abstract Geosteering workflows are increasingly based on updated quantifications of subsurface uncertainties during real-time operations. These workflows give tremendous amounts of information that a human brain cannot make sense of. To advance value creation from geosteering, the industry should develop and adopt decision support systems (DSSs). DSSs might provide either expert tools which inform decisions under uncertainty or optimization-based recommendations. In both cases the adoption of a DSS would require new skillsets to dynamically and systematically interpret uncertainties and parameters required for operational decision making. The aim of this work is to identify the relevant skills and ways to aid good geosteering decisions. We present an experiment where 54 geosteering experts took part in performing steering decisions under uncertainty in a controlled environment using an online competition platform. In the experiment we compare the decisions of the experts with an AI bot that had the same information at its disposal. Two of the participants beat the AI bot. A survey was conducted to reveal their winning strategies. The survey shows that both of the winners had extensive prior geosteering experience. That, together with luck, allowed them to beat the AI bot. At the same time neither of the winners utilized the full potential of uncertainty tools in the platform. While geosteering experts possess insights due to prior experience, the information in the real-time data will still be overwhelming, sometimes resulting in inconsistent and unreliable geosteering choices. The AI bot guarantees reliable and consistent decisions by optimization based on systematic uncertainty analysis. Further development of DSSs, and their use as training-simulators for experts, should lead to improved well placements through adopting well-established principles for high-quality decision-making.

scholarly journals Real-Time Data Processing

2021 ◽  
pp. 147-156
Author(s):  
Fabiana Fournier ◽  
Inna Skarbovsky
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Processing System ◽  
Event Processing ◽  
Time Data ◽  
System Architectures ◽  
Real Time Processing ◽  
Operational Decision Making ◽  
Real Time Data Processing ◽  
High Level

AbstractTo remain competitive, organizations are increasingly taking advantage of the high volumes of data produced in real time for actionable insights and operational decision-making. In this chapter, we present basic concepts in real-time analytics, their importance in today’s organizations, and their applicability to the bioeconomy domains investigated in the DataBio project. We begin by introducing key terminology for event processing, and motivation for the growing use of event processing systems, followed by a market analysis synopsis. Thereafter, we provide a high-level overview of event processing system architectures, with its main characteristics and components, followed by a survey of some of the most prominent commercial and open source tools. We then describe how we applied this technology in two of the DataBio project domains: agriculture and fishery. The devised generic pipeline for IoT data real-time processing and decision-making was successfully applied to three pilots in the project from the agriculture and fishery domains. This event processing pipeline can be generalized to any use case in which data is collected from IoT sensors and analyzed in real-time to provide real-time alerts for operational decision-making.

scholarly journals The Importance of Implementing Cyber Physical Systems to Acquire Real-Time Data and Indicators

J ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 147-153
Author(s):  
Paula Morella ◽  
María Pilar Lambán ◽  
Jesús Antonio Royo ◽  
Juan Carlos Sánchez
Keyword(s):  
Decision Making ◽  
Data Acquisition ◽  
Real Time ◽  
Failure Detection ◽  
Cyber Physical Systems ◽  
Future Research ◽  
Time Data ◽  
Physical Systems ◽  
The Real ◽  
Real Time Data

Among the new trends in technology that have emerged through the Industry 4.0, Cyber Physical Systems (CPS) and Internet of Things (IoT) are crucial for the real-time data acquisition. This data acquisition, together with its transformation in valuable information, are indispensable for the development of real-time indicators. Moreover, real-time indicators provide companies with a competitive advantage over the competition since they enhance the calculus and speed up the decision-making and failure detection. Our research highlights the advantages of real-time data acquisition for supply chains, developing indicators that would be impossible to achieve with traditional systems, improving the accuracy of the existing ones and enhancing the real-time decision-making. Moreover, it brings out the importance of integrating technologies 4.0 in industry, in this case, CPS and IoT, and establishes the main points for a future research agenda of this topic.

Lifting Operations with Wind Turbine Installation Jack-Ups Using Real-Time Data

2021 ◽  
Author(s):  
Kayo Vanderheggen ◽  
Joost Janssen ◽  
Nate Meredith
Keyword(s):  
Wind Turbine ◽  
Real Time ◽  
Support System ◽  
High Load ◽  
Full Potential ◽  
Catastrophic Failure ◽  
Time Data ◽  
Real Time Data ◽  
Jack Up ◽  
Turbine Installation

When a wind turbine installation jack-up performs a heavy lifting operation with the crane it affects the loads on the foundation. For these units the crane typically encircles a leg or is positioned close to it. Consequently, that leg attracts most of the loads due to crane operations. For each location jack-ups prove the capacity of the foundation by applying a controlled, high load at each of the footings before commencing operations. This process is known as preloading. The achieved preload at the jack-up’s foundation determines the operational limit. Exceedance of the preload value may result in foundation instability. Depending on the site’s foundation characteristics the consequences of such an exceedance range from negligible to catastrophic failure. GustoMSC has developed Operator Support System (OSS) software with the purpose to make the operator aware of the limitations imposed by the preloaded foundation. The application outlines operational limits based on real-time data from the jack-up, jacking system and crane which enables the operators to safely unlock the full potential of their wind turbine installation jack-up.

scholarly journals Still normal? Contextualizing real-time data with long-term statistics to monitor anomalies and systematic changes in storm surge activity – Introduction of a prototype web tool storm surge monitor for the German coasts

2021 ◽  
Author(s):  
Xin Liu ◽  
Insa Meinke ◽  
Ralf Weisse
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Storm Surge ◽  
Storm Surges ◽  
Added Value ◽  
Time Data ◽  
Storm Activity ◽  
The Public ◽  
Real Time Data

Abstract. Storm surges represent a major threat to many low-lying coastal areas in the world. While most places can cope with or are more or less adapted to present-day risks, future risks may increase from factors such as sea level rise, subsidence, or changes in storm activity. This may require further or alternative adaptation and strategies. For most places, both forecasts and real-time observations are available. However, analyses of long-term changes or recent severe extremes that are important for decision-making are usually only available sporadically or with substantial delay. In this paper, we propose to contextualize real-time data with long-term statistics to make such information publicly available in near real-time. We implement and demonstrate the concept of a ”storm surge monitor” for tide gauges along the German North Sea and Baltic Sea coasts. It provides automated near real-time assessments of the course and severity of the ongoing storm surge season and its single events. The assessment is provided in terms of storm surge height, frequency, duration, and intensity. It is proposed that such near real-time assessments provide added value to the public and decision-making. It is further suggested that the concept is transferable to other coastal regions threatened by storm surges.

Supporting Natural Hazards Management With Geospatial Technologies

2019 ◽  
Author(s):  
Diana Mitsova
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Natural Hazards ◽  
Spatial Data ◽  
Disaster Response ◽  
Early Warning Systems ◽  
Unmanned Aircraft ◽  
Time Data ◽  
Geospatial Technologies ◽  
Collaborative Efforts

On a global scale, natural disasters continue to inflict a heavy toll on communities and to pose challenges that either persist or amplify in complexity and scale. There is a need for flexible and adaptive solutions that can bridge collaborative efforts among public agencies, private and nonprofit organizations, and communities. The ability to explore and analyze spatial data, solve problems, visualize, and communicate outcomes to support the collaborative efforts and decision-making processes of a broad range of stakeholders is critical in natural hazards and disaster management. The adoption of geospatial technologies has long been at the core of natural hazards risk assessment, linking existing technologies in GIS (geographic information system) with spatial analytical techniques and modeling. Practice and research have shown that though risk-reduction strategies and the mobilization of disaster-response resources depend on integrating governance into the process of building disaster resilience, the implementation of such strategies is best informed by accurate spatial data acquisition, fast processing, analysis, and integration with other informational resources. In recent years, new and accessible sources and types of data have greatly enhanced the ability of practitioners and researchers to develop approaches that support rapid and efficient disaster response, including forecasting, early warning systems, and damage assessments. Innovations in geospatial technologies, including remote sensing, real-time Web applications, and distributed Web-based GIS services, feature platforms for systematizing and sharing data, maps, applications, and analytics. Distributed GIS offers enormous opportunities to strengthen collaboration and improve communication and efficiency by enabling agencies and end users to connect and interact with remotely located information products, apps, and services. Newer developments in geospatial technologies include real-time data management and unmanned aircraft systems (UAS), which help organizations make rapid assessments and facilitate the decision-making process in disasters.

scholarly journals Internet of Things in E-Government

2020 ◽  
Vol 10 (2) ◽  
pp. 99-118
Author(s):  
Panagiota Papadopoulou ◽  
Kostas Kolomvatsos ◽  
Stathes Hadjiefthymiades
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
Early Stage ◽  
Holistic Approach ◽  
Smart Devices ◽  
Full Potential ◽  
Time Data ◽  
Legal Nature ◽  
Real Time Data ◽  
The Creation

E-government can greatly benefit by the use of IoT, enabling the creation of new innovative services or the transformation and enhancement of current ones, which are informed by smart devices and real-time data. The adoption of IoT in e-government encompasses several challenges of technical as well as organizational, political and legal nature which should be addressed for developing efficient government-to-citizen and government-to-society applications. This article examines IoT adoption in e-government in a holistic approach. It provides an overview of the IoT potential in e-government across several application domains, highlighting the specific issues that seek attention in each of them. The article also investigates the challenges that should be considered and managed for IoT in e-government to reach its full potential. With the application of IoT in e-government being at an early stage, the article contributes to the theoretical and practical understanding of how IoT can be leveraged for e-government purposes.

IoT-based system for communication and coordination of football robot team

2017 ◽  
Vol 27 (2) ◽  
pp. 162-181 ◽  
Author(s):  
Zhuming Bi ◽  
Guoping Wang ◽  
Li Da Xu ◽  
Matt Thompson ◽  
Raihan Mir ◽  
...  
Keyword(s):  
Decision Making ◽  
Information System ◽  
Sensor Networks ◽  
Real Time ◽  
System Level ◽  
Time Data ◽  
Content Type ◽  
Iot Applications ◽  
Real Time Data ◽  
Communication And Coordination

Purpose The purpose of this paper is to develop an information system which is based on the Internet of things (IoT) and used to support the communication and coordination in a cooperative robot team. Design/methodology/approach The architecture of the IoT applications for decision-making activities in a complex system is elaborated, the focus lies on the effective implementation of system interactions at the device-level. A case study is provided to verify system performances. Findings The IoT concept has been introduced in an information system of a football robot team to support the coordination among team players. Various sensors are used to collect data from IoT, and data are processed for the controls of robotic players to achieve the better performance at the system level. The field test has shown the feasibility and effectiveness. Research limitations/implications To investigate how IoT can be utilized in an information system for making complex decisions effectively, the authors use the decision-support system for a football robot team to illustrate the approaches in developing data acquisition infrastructure, processing and utilizing real-time data for the communication and coordination of robot players in a dynamic competing environment. While the presented work has shown the feasibility of an IoT-based information system, more work are needed to integrate advanced sensors within the IoT and develop more intelligent algorithms to replace manually remote control for the operations of robot players. Practical implications The proposed system is specifically for a football robot team; however, the associated approaches are applicable to any decentralized system for developing an information system to support IoT-based communication and coordination within the system in the real-time mode. Originality/value The exploration of IoT applications is still at its early stage, existing relevant work is mostly limited to the development of system architecture, sensor networks, and communication protocols. In this paper, the methods on how to use massive real-time data for decision-making of a decentralized team have been investigated, and the proposed system has its theoretical significance to developing other decentralized wireless sensor networks and decision-making systems.

scholarly journals BUSINESS MODEL FRAMEWORK FOR USING REAL-TIME PROCESS DATA FOR DESIGN DECISION MAKING

2011 ◽  
Author(s):  
Matty Janssen ◽  
Paul Stuart
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Business Model ◽  
Environmental Data ◽  
Design Decision ◽  
Time Process ◽  
Time Data ◽  
Process Data ◽  
Model Framework ◽  
Business Decision

In recent years real-time data management systems have become commonplace at pulp and paper mills, and mills seek to use this important resource for improved operation of production facilities as well as for business decision-making. This paper presents a comprehensive and holistic approach to business modeling in which real-time process data, cost data, and environmental data are used in a “bottom-up” manner to exploit their potential for process decision-making. The paper describes a hypothetical case study in which the business model concept is illustrated by application to a process design problem at an integrated newsprint mill.

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