Understanding AI Application Dynamics in Oil and Gas Supply Chain Management and Development: A Location Perspective

The purpose of this paper is to gain a better understanding of Artificial Intelligence (AI) application dynamics in the oil and gas supply chain. A location perspective is used to explore the opportunities and challenges of specific AI technologies from upstream to downstream of the oil and gas supply chain. A literature review approach is adopted to capture representative research along these locations. This was followed by descriptive and comparative analysis for the reviewed literature. Results from the conducted analysis revealed important insights about AI implementation dynamics in the oil and gas industry. Furthermore, various recommendations for technology managers, policymakers, practitioners, and industry leaders in the oil and gas industry to ensure successful AI implementation were outlined. Doi: 10.28991/HIJ-SP2022-03-01 Full Text: PD

DexROV: Enabling effective dexterous ROV operations in presence of communication latency

Subsea interventions in the oil & gas industry as well as in other domains such as archaeology or geological surveys are demanding and costly activities for which robotic solutions are often deployed in addition or in substitution to human divers - contributing to risks and costs cutting. The operation of ROVs (Remotely Operated Vehicles) nevertheless requires significant off-shore dedicated manpower to handle and operate the robotic platform and the supporting vessel. In order to reduce the footprint of operations, DexROV proposes to implement and evaluate novel operation paradigms with safer, more cost effective and time efficient ROV operations. As a keystone of the proposed approach, manned support will in a large extent be delocalized within an onshore ROV control center, possibly at a large distance from the actual operations, relying on satellite communications. The proposed scheme also makes provision for advanced dexterous manipulation and semi-autonomous capabilities, leveraging human expertise when deemed useful. The outcomes of the project will be integrated and evaluated in a series of tests and evaluation campaigns, culminating with a realistic deep sea (1,300 meters) trial in the Mediterranean sea

Modular reactors: What can we learn from modular industrial plants and off site construction research

New modular factory-built methodologies implemented in the construction and industrial plant industries may bring down costs for modular reactors. A factory-built environment brings about benefits such as; improved equipment, tools, quality, shift patterns, training, continuous improvement learning, environmental control, standardisation, parallel working, the use of commercial off shelf equipment and much of the commissioning can be completed before leaving the factory. All these benefits combine to reduce build schedules, increase certainty, reduce risk and make financing easier and cheaper.Currently, the construction and industrial chemical plant industries have implemented successful modular design and construction techniques. Therefore, the objectives of this paper are to understand and analyse the state of the art research in these industries through a systematic literature review. The research can then be assessed and applied to modular reactors.The literature review highlighted analysis methods that may prove to be useful. These include; modularisation decision tools, stakeholder analysis, schedule, supply chain, logistics, module design tools and construction site planning. Applicable research was highlighted for further work exploration for designers to assess, develop and efficiently design their modular reactors

Evaluation of the potential for automation and robot technology, with focus on condition monitoring on static systems for topside offshore facilities.

Master's thesis in Offshore technologyDigitalization has become one of the most important development areas across industries and work processes. We know that this also has high focus in the oil industry today. Therefore, my contribution would be to try to see where the oil and gas industry is today, the trends and what are the potential moving forward. Automation and use of robot technology has developed very rapidly the last years. Technology trends indicates large potential for automated systems in maintenance and condition monitoring. We see that this technology is implemented to a large extent in other industries. The drivers for the oil and gas industry has historically been based on improved safety. We see now a potential for both cost avoidance, reduced downtime and less impact on the environment Maintenance and inspection is a large cost for the oil industry. In addition, these processes often cause shut down of the facilities. Condition monitoring and maintenance is based on the actual status of equipment and systems. Today’s technology makes it possible. In addition, robot technology has a potential for improving safety and reduce cost and downtime by avoiding human interactions. The oil and gas industry has not been a front runner compared to other industries. The conservatism driven by safety and reliability requirements might be one reason to this. At the same time, we see a growing interest and a lot of initiatives and developments. I have chosen to study topside static systems on offshore platforms. This to be able to narrow down the study. But in general, the descriptions, analysis and discussions may also be relevant for other systems

Oil spills detection by means of UAS and low-cost airborne thermal sensors

This paper provides an overview of oil spill scenarios and the remote sensing methods used for detection and mapping the spills. It also discusses the different kinds of thermal sensors used in oil spills detection. As UAS is becoming an important player in the oil and gas industry for the low operating costs involved, this research involved working with a cheap thermal airborne sensor mounted on DJI Phantom 4 system. Data were collected in two scenarios, first scenario is collecting data in Michigan’s Upper Peninsula at a petroleum company location and the second scenario was an indoor experiment simulating an offshore spill. The aim of this research is to inspect the capability of Lepton LWIR inexpensive sensor to detect the areas contaminated with oil. Data processing to create classification maps involved using ArcGIS 10.5.1, ERDAS Imagine 2015 and ENVI 5.3. Depending accuracy assessment (confusion matrices) for the classified images and comparing classified images with ground truth, results shows the Lepton thermal sensor worked well in differentiating oil from water and was not a good option when there are many objects in the area of interest. Future research recommendations and conclusions are presented

An overview of robotics and autonomous systems for harsh environments

Across a wide range of industries and applications, robotics and autonomous systems can fulfil the crucial and challenging tasks such as inspection, exploration, monitoring, drilling, sampling and mapping in areas of scientific discovery, disaster prevention, human rescue and infrastructure management, etc. However, in many situations, the associated environment is either too dangerous or inaccessible to humans. Hence, a wide range of robots have been developed and deployed to replace or aid humans in these activities. A look at these harsh environment applications of robotics demonstrate the diversity of technologies developed. This paper reviews some key application areas of robotics that involve interactions with harsh environments (such as search and rescue, space exploration, and deep-sea operations), gives an overview of the developed technologies and provides a discussion of the key trends and future directions common to many of these areas

Challenges in Collaborative HRI for Remote Robot Teams

Collaboration between human supervisors and remote teams of robots is highly challenging, particularly in high-stakes, distant, hazardous locations, such as off-shore energy platforms. In order for these teams of robots to truly be beneficial, they need to be trusted to operate autonomously, performing tasks such as inspection and emergency response, thus reducing the number of personnel placed in harm's way. As remote robots are generally trusted less than robots in close-proximity, we present a solution to instil trust in the operator through a `mediator robot' that can exhibit social skills, alongside sophisticated visualisation techniques. In this position paper, we present general challenges and then take a closer look at one challenge in particular, discussing an initial study, which investigates the relationship between the level of control the supervisor hands over to the mediator robot and how this affects their trust. We show that the supervisor is more likely to have higher trust overall if their initial experience involves handing over control of the emergency situation to the robotic assistant. We discuss this result, here, as well as other challenges and interaction techniques for human-robot collaboration.Comment: 9 pages. Peer reviewed position paper accepted in the CHI 2019 Workshop: The Challenges of Working on Social Robots that Collaborate with People (SIRCHI2019), ACM CHI Conference on Human Factors in Computing Systems, May 2019, Glasgow, U

LIFECYCLE MANAGEMENT OF OFFSHORE AND ONSHORE WIND FARMS

Since the demand for renewable energy sources on a global scale has increased substantially over the past few years, a great number of businesses have made investments in this industry and are doing their utmost to make additional developments and discoveries in the field of wind energy. Wind farms, both onshore and offshore, are considered to be key contributors to the production of sustainable energy because they offer significant benefits, including a reduction in the negative effects on the environment and the production of harmful gases. The purpose of this thesis was to analyse and explore the lifecycle activities of a wind farm, in order to determine the failure modes, failure effects, and failure consequences of the critical components, as well as the strategies that can be used to counteract these failures. As many wind farms are reaching their end of life, so this thesis also focused on the techniques and strategies that can be done before dismantling, The thesis also includes a reliability analysis, failure mode effect and criticality analysis of generator and gearbox of wind turbine, and also lifecycle cost analysis of an offshore wind farm. These studies improved our knowledge of offshore windfarm operations, maintenance strategies and give a brief information about cost reduction techniques. Several steps from maintenance strategies based on NORSOK Z-008 and ISO-14224, as well as knowledge gained from research papers and interviews with engineers in moreld, were implemented to achieve the goals of this thesis

Sustainable Decommissioning of Offshore Platforms: a Proposal of Life-Cycle Cost-Benefit Analysis in ItalianOil and Gas Industry

The decommissioning of offshore Oil & Gas platforms, at the end of their life cycle, has been a very controversial topic in recent years. Moreover, the decommissioning complexity increases if we consider a shift towards a linear economy to a circular one. The latter pushes to innovate business models and re-configure the value chain activities in a sustainable way. Starting from these considerations, this work aims to identify a cost-benefit model suitable for evaluating sustainable business models of offshore platforms. After a literature review of different models for analysing maintenance and decommissioning Real Options (ROs), the Life-Cycle Cost-Benefit (LCCB) analysis has been selected as the most adequate managerial tool for evaluating and comparing the Net Present Value (NPV) of platforms compared the maintenance and decommissioning costs. The LCCB tool could aid the managers in the oil and gas industry to quantify the decommissioning and maintenance costs including capital expenditure (CapEx) and risk expenditure (RiskEx). In the future steps, to test the LCCB model, an empirical analysis could be carried out on a sample of organizations interested in the sustainable decommissioning of offshore platforms