Information Technology (IT) and Operational Technology (OT) are converging as integration from the real-time to the enterprise gains ground across many industries. This paper focuses on accelerating the convergence of IT and OT to deliver increased safety, efficiency and productivity in the petroleum industry resulting from harmonizing processes, aligning technologies and enhancing governance. We start by contextually defining IT vs. OT to highlight key attributes of these capabilities as information technology vs. digital capability used in process operations. With this context and differentiating attributes of our industry, we discuss the need and present means to align business strategy, process capabilities, technical disciplines, work processes, and organizational models to achieve value in convergence – specifically, business and operational change management needed to realize better decision support through improved visibility, discovery, predictability and optimization. After presenting a structured approach to assess maturity and plan for convergance within the framework of existing and new digital oilfiled initiatives, we propose a way forward as a change management process. We conclude our discussion by presenting a recent example to highlight collaboration across the ecosystem to foster integration across disciplines, and enable utilization of internal and external expertise.

Since the Industrial Internet of Things (IIoT) became its own domain, in parallel with consumer-oriented IoT, various industries have been successfully deploying such systems – initially as pilot projects, and more recently at scale. Meanwhile, the O&G industry, hurt by the price of oil, postponed investments in new technologies. Nevertheless, there are now multiple successful case studies of IIoT in O&G. This paper contains a high-level review of several such IIoT projects in O&G and aims to help the reader gauge the results achieved in this area. By examining these cases and looking at the similarities and differences with applications in other industrial sectors (transportation, water management, utilities…), the O&G industry can derive guidance in its adoption of IIoT, in particular by identifying the "lowest-hanging fruit" to improve operations and reduce human and equipment costs. While there is still confusion in terms of standards, choice of technologies, and myriad actors of all sizes, this is neither new in our industry nor unexpected in an emerging field; these challenges should therefore not prevent others from moving forward.

Overview There is an emerging consensus in our industry and in regulatory agencies about the need to improve our visibility of operations and to standardize as well as orchestrate the execution of operation processes to achieve integrated operations, safety and security assurance. The complexity and risk of real-­-time exploration and production (E&P) operations is growing steadily along several axes: geology, operational environment, technology, distributed multi-­-discipline teams and multi-­-company teams. Operational performance, safety, and security assurance demand a high degree of situational awareness and real-­- time coordination. At present, situational awareness is based on the visualization and monitoring of sensor data and, in some cases, of video feeds. Although data, video and audio travel through digital channels, they are rarely correlated or integrated. Decision makers are confronted with large amounts of data that are difficult to parse in real time and monitoring cannot be sustained over long periods of time because of distractions and fatigue. Furthermore, most decision making and coordination is based on people-­-to-­-people communication. These interactions are rarely captured, shared or integrated with other forms of data. Other sectors involved in complex, high-­-stakes, real-­-time operations face similar conditions, for example, transportation, public safety or the military. They have learned to leverage digital technology to develop a "common picture of the operation" shared by all actors in a theater of operations. Sharing a common picture of the operation enables effective right-­-time response, efficient collaboration, and consistent decision making, In this paper we outline: The case for integration of operations, safety, and security assurance to create a common operations picture The capabilities of digital platforms to support a common picture of the operation How those capabilities can be leveraged in E&P operations.

Industry reports identify human and organizational factors as contributors to operational incidents. These include lack of standardization, enablement, and compliance with operating procedures at the well site or by the broader (local or remote) support personnel. There is consensus among practitioners and regulators about the need to pro-actively reduce our exposure to these factors, both to avoid potential incidents and to reliably contain the impact of realized incidents. In this paper we argue that we should improve operations assurance by building trust into our operations and we discuss how to combine existing principles, methods and information technology to achieve this in practice. The approach we will describe takes advantage of a framework developed by the HS&E profession--the "bow tie"-- to analyze what contributes to incidents, what barriers could be put in place to prevent them and how to contain them. The diagram shows an abstraction of the bow tie model. The left side of the diagram (top event prevention) makes explicit the various threats we face during an operation, the precursor that signal the presence of a threat, and the preventive barriers--people, process, technology--that we should activate to avoid the propagation of the threat to become a top event(at the center of the bow tie). The right side of the diagram (top event response) makes explicit the response workflows that may follow an incident, the escalation barriers that we should activate to contain the impact of the incident, and the consequences that we would face if the barriers fail.

Digital Oil Field's (DOF) practice's original promise was to gather data to help make better technical and business decisions. Some argue that a required step to enable a shift in the adoption of the DOF methodology is to treat data as an asset. Meaning data as an asset is as valuable as a physical asset. It should be maintained, protected, and respected in its own way with the same diligence we have for a field. Here we are presenting why data is an asset. With the advent of analytics, thanks to complex correlations “data can talk”; for it to be meaningful, data needs to be up to date, validated, and standardized so everyone can have access to a single version of the truth. Data is accepted and trusted if the process by which it has been validated is viewable and auditable. Enhancement and manipulations of this data need to be shared and stored centrally, not locally. The logic applied for its manipulation needs to be documented as well. Trusted data means that each member of the team trusts each other's methodology to transform data into information. An enabler is the generation of meta-data to encapsulate this logic with the shared output. Such fresh approaches to data validation and sharing will generate significant savings by eliminating duplicate efforts, increasing access time to information, and confidence in using the latest available source of information. Ensuring this seamless access to information requires identifying where the sources of data are and developing aggregators to make it accessible to all in a standard manner from a single point. Creating this bridge to scattered data from multiple sources over many vendors is a complex task requiring domain expertise from a very heterogeneous set of people… It requires data ownership identification and bridging inconsistencies in data types and quality. From the capture of data points and its validation to its refining and by-products, “Data as an asset” requires custodians of the integrity of the data, its storage and accessibility. “Data as an asset” means data is valuable and therefore needs to be protected from being misused or stolen. The fact we now “drink from the source” of data (getting data almost directly from the sensors) means we have to secure its acquisition and transmission very thoroughly and properly manage entitlement. “Data as an asset” and the corollary technical data management it implies, will contribute to maximizing production and reserves; while also reducing costs by applying efficiencies, and connecting the field to the back office.