A Modular End-to-End Framework for Secure Firmware Updates on Embedded Systems

Firmware refers to device read-only resident code which includes microcode and macro-instruction-level routines. For Internet-of-Things (IoT) devices without an operating system, firmware includes all the necessary instructions on how such embedded systems operate and communicate. Thus, firmware updates are essential parts of device functionality. They provide the ability to patch vulnerabilities, address operational issues, and improve device reliability and performance during the lifetime of the system. This process, however, is often exploited by attackers in order to inject malicious firmware code into the embedded device. In this article, we present a framework for secure firmware updates on embedded systems. This approach is based on hardware primitives and cryptographic modules, and it can be deployed in environments where communication channels might be insecure. The implementation of the framework is flexible, as it can be adapted in regards to the IoT device’s available hardware resources and constraints. Our security analysis shows that our framework is resilient to a variety of attack vectors. The experimental setup demonstrates the feasibility of the approach. By implementing a variety of test cases on FPGA, we demonstrate the adaptability and performance of the framework. Experiments indicate that the update procedure for a 1183-kB firmware image could be achieved, in a secure manner, under 1.73 seconds.

Cloud Computing and Information Systems Strategy in Multi-National Companies

This chapter explores how information systems (IS) strategy is developed and implemented in multi-subsidiary international groups, and how this has been influenced by the advent of cloud computing and the solutions offered by the major cloud providers. Using an inductive, qualitative research approach, the chapter assesses learnings to date from cloud adoption, reports on individual expert interviews, and discusses future challenges for those companies embarking upon cloud projects. Key issues distilled from the literature and the in-depth interviews with practitioners are identified and discussed. The chapter concludes that cloud has significantly impacted IS strategy within multi-national organizations, allowing flexibility in various scenarios like, for example, moving from monolithic enterprise resource planning applications to a micro-service based architecture. There are nevertheless a range of strategic and operational issues that must be carefully managed and planned for, including multiple aspects of compliance and security.

Implementing just-in-time inventory management to address contextual operational issues: a case study of a commercial livestock farm in southern Nigeria

PurposeThis research focuses on the implementation of Just-in-Time (JIT) inventory management, drawing on a case study of a commercial livestock farm located in a swampy area of southern Nigeria.Design/methodology/approachThe research adopts a qualitative approach. Interviews and workshops were used for data collection.FindingsFindings from the study reveal that the commitment on the internal organisational members and skilful collaboration with supply chain partners are required for effective use of JIT, especially in an odd contextual situation such as the case in this study. This also justifies the embraced of additional cost of securing JIT inventory management practices such as the situation in the case study organisation that could not allow conventional inventory management.Originality/valueIt is suggested for further research to consider the topic from a mixed method approach as well as extend the focus on the possibility of legal regulations and government support to exceptional operational practices among organisations, especially those in the context of the food production sector, where this research was based.

Going beyond Cryptocurrencies: The Social Representation of Blockchain

This study investigates the social representation of Blockchain from the perspective of professionals in Brazil, herein considered as a proxy for emerging markets, and then compares the results found with the existing academic literature on the concept of Blockchain. To do that, the social representation theory was applied, operationalized through the words evocation technique. Security, bitcoin and decentralization were the categories located in the central nucleus of the social representation of Blockchain, while innovation, data, network, cryptocurrency, and technology were the categories located in the peripheral system. Based on the results obtained, there was a perceived strong association of Blockchain with bitcoin, one of its applications, and a dissonance between the existing academic literature and the perception of Brazilian professionals about the concept of Blockchain, as the latter is a privilege of the technical and operational issues of Blockchain to the detriment of its strategic potential. This dissonance can cause Blockchain initiatives to have results below expectations. Finally, Brazilian professionals did not realize the potential for inclusion of Blockchain in an emerging market such as Brazil and did not notice the need and relevance of a specific legal governance for Blockchain, an issue also forgotten by academia.

Prediction of Subsidence during TBM Operation in Mixed-Face Ground Conditions from Realtime Monitoring Data

The prediction of settlement during tunneling presents multiple challenges, as such settlement is governed by not only the local geology but also construction methods and practices, such as tunnel boring machine (TBM). To avoid undesirable settlement, engineers must predict the settlement under given conditions. The widely used methods are analytical solutions, empirical solutions, and numerical solutions. Analytical or empirical solutions, however, have limitations, which cannot incorporate the major causes of subsidence, such as unexpected geological conditions and TBM operational issues, among which cutterhead pressure and thrust force-related factors are the most influential. In settlement prediction, to utilize the machine data of TBM, two phases of long short-term memory (LSTM) models are devised. The first LSTM model is designed to capture the features affecting surface settlement. The second model is for the prediction of subsidence against the extracted features. One thing to note is that predicted subsidence is the evolution of settlement along TBM drive rather than its maximum value. The proposed deep-learning models are capable of predicting the subsidence of training and test sets with excellent accuracy, anticipating that it could be an effective tool for real-world tunneling and other underground construction projects.

Remote Activated Completion Technology Enhances Operational Efficiency of Offshore Wells in Middle East

To access a larger amount of pay zone, well trajectories are becoming longer and more complex, creating greater challenges for running completion liners. A liner shoe is a casing accessory tool that aids in the running of completion liners in long wells by allowing auto-filling of the liner and enabling pumping through the bottom of the liner. Upon reaching planned liner depth, the liner shoe is closed to allow for pressure testing and subsequent completion operations. Conventional methods used to close a liner shoe involve well intervention to set plugs or by dropping a ball, and there are inherent costs and risks associated with these operations. This paper presents the development and deployment of a remotely activated electronic liner shoe (ELS) for offshore applications that enables interventionless closing of the liner shoe, thereby improving operational efficiency, and reducing potential operational issues that could occur while closing the liner shoe conventionally. The ELS allows the operator to precisely control when the liner shoe closes – either based on pre-programmed pressure signals, a timer, or a combination of the two. A major operator in the Middle East required an ELS to be developed and qualified specifically for their offshore well conditions. A new technology qualification program was devised in collaboration with the operator to qualify both the electronic and mechanical functionalities of the tool. This paper documents the methods and results of the extensive qualification test program. The development and qualification process were successfully completed within 10 months at research and development facilities in Norway. Following qualification testing, the ELS was first deployed for the operator in an offshore well in Q4 of 2019. Operational considerations in programming the remote functionality of the tool is presented in this paper. After a successful field trial, the ELS has been run in more than 15 offshore wells and has become the standard option in the operator's completion program.

Analysis of operational issues in hydrothermal liquefaction and supercritical water gasification processes: a review

Biomass is often referred to as a carbon–neutral energy source, and it has a role in reducing fossil fuel depletion. In addition, biomass can be converted efficiently into various forms of biofuels. The biomass conversion processes involve several thermochemical, biochemical, and hydrothermal methods for biomass treatment integration. The most common conversion routes to produce biofuels include pyrolysis and gasification processes. On the other hand, supercritical water gasification (SCWG) and hydrothermal liquefaction (HTL) are best suitable for converting biomass and waste with high moisture content. Despite promising efficiencies, SCWG and HTL processes introduce operational issues as obstacles to the industrialization of these technologies. The issues include process safety aspects due to operation conditions, plugging due to solid deposition, corrosion, pumpability of feedstock, catalyst sintering and deactivation, and high production costs. The methods to address these issues include various reactor configurations to avoid plugging and optimizing process conditions to minimize other issues. However, there are only a few studies investigating the operational issues as the main scope, and reviews are seldomly available in this regard. Therefore, further research is required to address operational problems. This study reviews the main operational problems in SCWG and HTL. The objective of this study is to enhance the industrialization of these processes by investigating the operational issues and the potential solutions, i.e., contributing to the elimination of the obstacles. A comprehensive study on the operational issues provides a holistic overview of the biomass conversion technologies and biorefinery concepts to promote the industrialization of SCWG and HTL.

WMO’s programme on tropical cyclone

ABSTRACT. The Tropical Cyclone Programmes of WMO was established to assist the many affected countries of the world in mitigating the impacts of tropical cyclones, through the development of their capabilities in monitoring, forecasting and disaster prevention and preparedness. The paper discusses the factors which have together led to significant progress in this regard. These include the organization and structure of the Programme, the systems and technologies in place, and the mechanisms for training and regional cooperation among the countries of the tropical cyclone basins. Specific tropical cyclone research and operational issues of concern are also presented.

Geology-Driven EUR Forecasting in Unconventional Fields

EUR (Estimated Ultimate Recovery) forecasting in unconventional fields has been a tough process sourced by its physics involved in the production mechanism of such systems which makes it hard to model or forecast. Machine learning (ML) based EUR prediction becomes very challenging because of the operational issues and the quality of the data in historical production. Geology-driven EUR forecasting, once established, offers EUR forecasting solutions that is not affected by operational issues such as shut-ins. This study illustrates the overall methodology in intelligent fields with real-time data flow and model update that enables optimization of well placement in addition to EUR forecasting for individual wells. A synthetic but realistic model which demonstrates the physics is utilized to generate input data for training the ML model where the spatially-distributed geological parameters including but not limited to porosity, permeability, saturation have been used to describe the production values and ultimately the EUR. The completion is given where the formation characteristics vary in the field that lead to location-dependent production performance leading to well placement optimization based on EUR forecasting from the geological parameters. The algorithm not only predicts the EUR of an individual well and makes decision for the optimum well locations. As the training model includes data of interfering wells, the model is capable of capturing the pattern in the well interference. Even though a synthetic but realistic reservoir model is constructed to generate the data for the aim of assisting the ML model, in practice, it is not an easy task to (1) obtain the input parameters to build a robust reservoir simulation model and (2) understanding and modeling of physics of fluid flow and production in unconventionals is a complex and time-consuming task to build real models. Thus, data-driven approaches like this help to speed up reservoir management and development decisions with reasonable approximations compared to numerical models and solutions. Application of machine learning in intelligent fields is also explained where the models are dynamically-updated and trained with the new data. Geology-driven EUR forecasting has been applied and relatively-new in the industry. In. this study, we are extending it to optimize well placement in intelligent fields in unconventionals beyond other existing studies in the literature.

Collaborative Working Environment CWE Strategy: An Enterprise Approach to Operational Excellence

Collaborative Working Environments (CWE) are a business solution that improve the quality and speed of decision making by enriching the collaboration between teams and individuals, which results in tangible business benefits. The advantages of working in a collaborative environment are well understood in the organization and the concept is widely embraced throughout the petroleum industry. CWEs provide seamless communication between disciplines and between teams in different locations. Traditionally, they have been used to connect staff in remote locations to teams in the headquarters, allowing real time monitoring of the health of the field, and fast decision making on operational issues and short to medium term optimization opportunities. The main goal is to be quickly alerted to events and make smarter, faster decisions using key capabilities available to the company with access to all relevant knowledge, data and analytical tools required to reach a decision. But this drive to make smarter, faster decisions is applicable to all levels of a company. In fact, it becomes increasingly important as more complex decisions are required at higher levels, which can be influenced by interpreted data, personal opinions and perceptions. In line with strategic objective of digital transformation, a national oil company (NOC) has extensive plans to develop asset specific CWEs and enterprise level CWEs. These will be centralized collaboration facilities to provide more rigorous, effective, and consistent surveillance & optimization to help reduce deferment costs and inefficiencies and accelerate decision-making with a measurable business value to enhance HSE, Reservoir, Drilling, Well and Production system performance through emerging digital innovation. All these centers shall be equipped to receive real time and episodic data and perform exception-based surveillance through trending, analysis, and condition diagnosis. All these CWE Centers shall enable decision making with efficient multi-disciplinary collaboration to address business challenges and increase the efficiency of day-to-day operations. They will have clear roles and responsibilities serving as an integral element of the value realization across the assets. The paper will describe the enterprise CWE strategy, key technical considerations, methodology and standards that have been set up to achieve the ultimate objective of the organization to maximize oil field recovery, eliminating non-productive time, enhancing HSE aspects and increasing profitability through the deployment of these various centers.