The term "Real-Time Optimization" (RTO) has rapidly found its way into common usage in the oil and gas industry, as it already has in many others. However, RTO in the oil and gas industry is usually used more as a slogan rather than describing a system or process that truly optimizes anything at all, let alone does so in real-time. In this paper, we describe what RTO means in the exploitation of hydrocarbons and what technologies are available now and are likely to be available in the future. We discuss how it is misunderstood and what real financial benefits await those who adopt it. Furthermore, we are working toward developing a method of classification to allow us to establish where a field operation lies on the RTO ladder, and to help plan a strategy to generate the benefits that moving up the RTO ladder can offer on specific fields and assets. The paper also describes a new SPE Technical Interest Group (TIG), explaining why it has been formed, and outlining its objectives and some planned deliverables. Real-time Optimization - Concepts and Definitions What is optimization? Intuitively most people agree on what we mean by "optimize." This comes down to understanding the dictionary definition; that is, to make the most of; to plan or carry out an economic activity with maximum efficiency; to find the best compromise among several often conflicting requirements, as in engineering design. Therefore, examples of what is usually meant by optimization in the oil and gas industry include:Maximizing hydrocarbon production or recovery,Finding the best solution in the region of physical and financial constraints to produce a decision,Maximizing net present value (NPV) through changes in capital expenditure (CAPEX) and/or operational expenses (OPEX). These elements, in turn, improve financial efficiency in portfolio management and risk analysis, andAdvanced real-time optimization: behavioral prediction and inference, pattern recognition to identify states of a group of wells, continuous adaptation and self-tuning ability. Although we may readily agree on these (and other) descriptions of what would be the outcome of optimization, agreeing what it actually means appears to be more complex. The reason for this is that the term optimization is usually used very loosely, whereas it needs to be defined rigorously and mathematically, while honoring the real-life physical system constraints that exist in the overall production process.

We propose a decision-making approach for optimizing the profitability of hydrocarbon reservoirs. The proposed approach addresses the overwhelming complexity of the overall optimization problem by suggesting an oilfield operations hierarchy that entails different time scales. We discuss system identification, optimization, and control that are appropriate at various levels of the hierarchy and capitalize on the abilities of permanently instrumented and remotely actuated fields. Optimization is performed in real-time and is based on feedback. We provide details on real-time identification of hybrid models and their use at the scheduling and supervisory control levels. Case studies using field-calibrated simulation data demonstrate the applicability and value of the proposed approach. Directions for future development are given.

The Real-Time Optimization Technical Interest Group (RTO TIG) has endeavored to clarify the value of real-time optimization projects. RTO projects involve three critical components: People, Process, and Technology. Understanding these components will help to establish a framework for determining the value of RTO efforts. In this paper, the Technology component is closely examined and categorized. Levels within each Technology category are illustrated using spider diagrams, which help decision-makers understand the current status of operations and the impact of future RTO projects. Uncertain value perception in our industry has been one of the critical issues in adopting RTO systems. Therefore, case histories are reviewed to demonstrate the impact of RTO projects. To assist RTO project promotion, we list lessons learned through case histories, suggest a justification process, and present a simple economic example. Introduction Industry case histories demonstrate many types of benefits from RTO, such as volume increase, ROI increase, decision quality, HSE improvement, and opex reduction. However, they have lacked systematic project evaluation methods or processes for justification. Today, promoting RTO is in essence a competition for capital within producing companies. The project teams that recognize this fact and then clearly outline the purpose, benefits, costs (direct or indirect), and strategic business alignment of their proposals will be in an advantageous position to secure funding. Because RTO is still an emerging discipline, classifying projects of this nature is still dependent on an individual's point of view. This paper is intended to enable classification of RTO in an objective manner and to help provide a common vocabulary to address issues. Three Cornerstones in Adopting New Technology In adopting any new technology, TIG members realize that there are three major factors: People, Process, and Technology, as shown in Fig. 1. New RTO technology can achieve the benefits we seek, but it is not likely without corresponding changes in the way we work with others and in the processes or workflow in which we perform tasks. This challenge is common to the implementation of any new technology, whether RTO or not. Engineers tend to emphasize the technology aspect because we are most familiar with it, but the other aspects are equally important. For example, the lack of workflow modification, which requires training and possible organizational changes, is tends to result in unsustainable efforts and ultimately underperformance of the investment in RTO. People People issues manifest themselves in several ways1: corporate culture, organizational structure, and training. Corporate culture is the set of tacit understandings and beliefs that form the foundation of how an organization works. It is a mental model that people have about the nature of an organization and how it sees itself. Within an organization, culture is "how things are done around here." The culture of an organization can be appropriate and supportive to an organization's goals and strategies, or it can hinder its initiatives and projects. Usually any major change in an organization, such as deployment of new technology, radical strategic shifts, or new initiatives, is countercultural. That is, the change breaks existing cultural rules and assumptions, and the change is automatically resisted and thereby impeded.

Summary In this work, we present an industrial automation framework for control and optimization of hydrocarbon-producing fields while satisfying business and physical constraints. The all-encompassing reservoir-management problem is decomposed into a hierarchy of decision-making problems at different time scales. We exemplify the proposed approach through a case study on a multiple-layer reservoir with a classical waterflood problem, in which a numerical reservoir model is used as a virtual field. A model-predictive control (MPC) strategy is used to regulate well and field instrumentation at economically optimal set points determined by an overlying supervisory control level. The study demonstrates significant reduction in water-handling costs and increased oil recovery. This work is a starting point for further development in automatic intelligent reservoir technologies, which capitalize on the abilities of permanent instrumented wells and remotely activated downhole completions.