Major Rotating equipment assets availability and reliability is critical for oil and gas companies. Current practice to ensure high availability and reliability is carrying out fixed running hours based preventive maintenance, which then dictates the Plant shutdown intervals, and increase the operating cost. Operational excellence, high efficiency and reliability, can be maintained and even enhanced further with latest digital technology enablers, Digital technology that uses advanced analytical and modeling techniques that understand equipment and operating behavior – to predict deviations in "optimal performance" versus "current performance" months ahead of time ("hidden" plant opportunities early identified). The company in its pursuit to operation excellency has identified and deployed solutions to enhance efficiency, reliability, improve performance and reduce operating costs related to Major rotating equipment operation and maintenance (Centrifugal, screw & Reciprocating & Compressors, Gas turbines, Steam turbines, Pumps, Power turbine and turbo Expander). The solution installed, commissioned and operates Smart Predictive analytics & diagnostics solutions (CPAD) to monitor analysis, anomaly predict and assess the conditions of Major Rotating Equipment. The Predictive diagnostics are based on modelling techniques coupled with machine learning algorithms deployed to achieve the early prediction of conditions and performance degradation causes & symptoms, ensures timely intervention by making small changes on line to prevent subsequent failures and extend the equipment remnant live, expand the planned shutdown intervals and reduce unplanned shutdowns. The solution is a data-driven to leverage existing data and infrastructure, provide insights and actionable warnings on equipment performance, reliability and process problems using the existing instrumentation on any type of equipment or processes, regardless of equipment manufacturer or agnostic to equipment age or class.

The value calculation for a new digital and innovative technology is often requested by the executive management to justify the cost required for the implementation and maintenance of the technology. The value is normally segregated into a tangible and intangible value that correspond to a quantitative and qualitative description of those value elements. As part of the Digital Oilfield (DOF) assessment, the solution value has been defined using two approaches. Firstly, qualitative value is described using a "FEATURE_BENEFIT_VALUE" model. The qualitative value elements have been grouped to align with the company strategic pillars to achieve its vision. Secondly, the quantitative value has been estimated using an NPV model. It estimates the value of the complete digital solution (combined investment for all domains) being proposed for the Asset. The model estimates the net present value (NPV) of the expected Asset investment in digital enablement and digital capability as defined in the assessment report. Net cash flow graphs are also calculated. The approach used is to calculate an NPV for a GO-NOGO decision. Therefore, a conservative estimate of NPV is made with the mind-set that if even being conservative, the NPV clears the company's hurdle rate for such projects, then the decision to invest is undertaken. Sensitivity analysis has been performed using conservative estimates of production gain enabled by digital and conservative oil prices. The paper will detail out the approach for the value quantification of a DOF solution that will also correspond to the industry guidance. Example on how the value is calculated will also be outlined.

A new integrated growth strategy of an oil & gas company is focusing on maximizing the value of reserves and production in order to meet the value proposition of the highest possible return to the company. The strategy is built on the strategic foundation of the company of People, Performance, Profitability and Efficiency. From a business performance perspective, the strategy will bear fruit through increased production capacity, improved operational and cost efficiencies, re-energizing mature fields and uncovering new resources whilst maintaining safety and asset integrity. The objective of this global level exercise aims to assess and evaluate various Digital Oilfield (DOF) practices and initiatives against industry best practices, to perform a landscape assessment of the upstream assets, to review the asset digital gap, to develop a strategic framework and roadmap ensuring that the company strategic pillars are supported across all relevant aspects, by closing the digital gap between current and future states. The assessment scope covers the following domains: Reservoir management Production optimisation Operation management & integrity Engineering & projects Drilling Efficiency Logistics & Planning The landscape assessment and gap analysis consist of several stages that starts from documenting the information received from the assets capturing their current business practices and processes, analyzing the "as-is" condition, designing the future state, assessing the impact to the specific assets, define the benefits and value and creating a 5-year business roadmap. Aligned with the company DOF strategy, understanding the asset digital gap and enhancing the asset digital maturity will improve: HSE and asset integrity by reducing hazard exposure, optimizing energy usage and improving wells and facilities integrity Collaboration and faster analysis leading to timely decision making Integrated operations by optimized drilling planning, operations, optimized production forecasting and integrated planning Optimum Reservoir Management through enhanced reservoir surveillance and recovery

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.