Implementing the IIoT paradigm into the classical oil & gas field OT systems is one of the essential concepts for Digital Oilfield 2.0. The transition in architecture and the corresponding technology changes can create a new cyber-physical security risk profile through alterations in the digital information structure of the oilfield OT system. With the onset of IIoT implementations in the industry, it is an opportune time to review and assess the emerging cyber-physical risk landscape. In the paper, we identified and compared the current oilfield OT logical structures with the designs emerging through the IIoT implementations. The analysis includes extensive reviews of developing standards, such as those proposed by Industrial Internet Consortium, and ongoing published experiences to find the primary points of transition. The security risks stemming from the IIoT implementation appear to raise significant concerns with regard to potentially severe cybersecurity outcomes, which could materially impact the integrity and safety of oilfieldoperations. The study concentrated on the cybersecurity threats that could pose negative physical and operational conditions resulting from loss of visibility and / or loss of control of the operational processes in field facilities. Extensive literature reviews were the basis for identifying the implications of cybersecurity risks in the ongoing stages of integrating the IIoT into the field. The reviews identified the modified strategies for cyber-physical systems, including potential threats and counter measurements for the field IIoT model. However, these proposed strategies still miss a fundamental denominator - the assessments generally ignore that it is the fundamental nature of IIoT structure itself that creates cyber-security vulnerabilities. To investigate further, we performed a contrasting analysis based on specific case studies of field IIoT devices such as the pump-off controller and OT architectures. Three foundational threat implications emerged on the transformation of IIoT architecture into the oilfield: 1)The exponential growth of connected distributed artificial intelligence (DAI) devices enormously increases the complexity of designing the software of each facility and system. 2)The cutting-edge Machine to Machine (M2M) characteristic in the IIoT model pushes the human out of the traditional control and monitor loop. 3)The widespread scale of DAI devices with the unique IP address in the network shifts cybersecurity risks to each connected endpoint. The cornerstone of the distinctive IIoT attributes illustrated in the paper contributes to the potential loss of control, leading to potential for serious damaging operational outcomes in the field. The goal of this paper is to aid oilfield security planning and design processes through animproved recognition of the cyber-physical security impacts emerging from the implementation of IIoT architectures and technologies integration into field OT domains.
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