For the past several years, the problem of reducing time-to-decision in field operations and capital projects has been repeatedly described and analyzed in qualitative and anecdotal terms. In this paper, we take an engineering approach to measure and understand the problem in quantitative and fact-based terms. We first review the mission of the SPE IT Technical Section-Oilfield Integration (SPE ITTS OI) subcommittee. Several contexts of oilfield integration and their role in Digital Oilfield of the Future (DOFF) initiatives are identified. We discuss the results of our study, and compare the results with those from other studies conducted by the SPE and also by two integrated oil companies (IOCs). We address the goal of "reducing time to decision," and show how even the most basic data-integration gaps can slow decisions with great economic impact. In information management and decision-making, the mondegreen "data commute" is the biggest problem area. The data commute absorbs over half the time that engineering and operations personnel could be spending making crucial decisions to effectively manage E&P assets. We review some case studies and their economic impact. Beyond "saving half of an engineer's time," several other more subtle gaps in the industry's current modeling and integration approaches are identified and evaluated. We conclude with showing how some of these gaps have been filled in other industries outside of oil & gas, and cite some examples that could be applicable in production surveillance and optimization. Introduction Every day engineers and geoscientists have to deal with time-consuming and manual search processes involving multiple applications, to answer even the most basic operational questions on the performance of individual wells to an entire field. DOFF initiatives are aimed at solving time-based problems by focusing on remote performance management and optimization, total producing asset awareness and visibility, right-time analysis and decision-making, and accurate and rapid operational execution. The oil & gas industry has repeatedly confirmed its shared interest and principles of DOFF, which first and foremost depends on enabling people to make decisions that avert problems, improve operations, and optimize production. The mission of the SPE ITTS OI subcommittee is to facilitate implementation of the digital oilfield through integration of information, technology, people, and processes. SPE ITTS OI identifies opportunities for improvement and supports the development and implementation of IT integration solutions, standards, and best practices spanning E&P business, surface, and subsurface domains. The SPE ITTS Oilfield Integration subcommittee and SPE Real-Time Optimization TIG have conducted several in-depth statistical studies that show that an unacceptable percentage of professionals in the E&P workforce are spending too much time searching for data, integrating it from multiple sources, and preparing it for analysis in applications.2,3 Once the data is in the application package for analysis, any updated or more recent data require a repeat of a tedious, uncreative, and nonproductive process to prepare and reload data. The time that could have otherwise been spent making operational or project decisions is lost completely to activity that has nothing to do with engineering and geoscience training. In this work, we recognize a fundamental tenet: Decisions drive actions that create value. We focus on the productive and economic impacts of making informed decisions sooner: "If I can make that decision accurately, but a month earlier, and can do this across many projects, many wells, many fields…". Obviously, faster decisions with precision have tremendous value, and provide much leverage in an industry hindered by a shortage of qualified people.
ExxonMobil is developing and implementing new systems and work processes that will increase the efficiency and effectiveness of well, reservoir, and facilities surveillance across their operated assets worldwide. For opportunities with a significant information technology component, often referred to as "digital oilfield" initiatives, ExxonMobil applies a broadly consistent, systematic approach to the identification of technologies or suites of related technologies which will add quantifiable value given our asset mix and organizational structure. To derive the greatest impact and efficiency, the new technologies are then implemented within established standard computing systems which allow scalable global solutions. Improved surveillance, whether it applies to well productivity, well integrity, reservoir performance, or surface facilities, has been identified as an area with a significant opportunity for volumes uplift and for improved work efficiency. ExxonMobil is developing a number of new surveillance tools, processes, and systems, some of which will utilize proprietary in-house technology with others developed jointly with vendors. This paper will focus on one such initiative, termed "Production Surveillance and Optimization" (PS&O). The PS&O initiative is a combination of enhanced IT capabilities and ExxonMobil-standard surveillance processes and best practices that will be employed worldwide starting in 2008. Key features of the PS&O tool are that it connects to disparate datastores such as corporate data repositories and data historians, allows automated alerting when production conditions deviate versus expectations, allows automation of follow-up diagnosis and analysis, and provides access to proprietary best practices relevant to the task at hand. Introduction Through its financial and operating performance, ExxonMobil has achieved value with its global functional organization. Increased upstream-wide standardization, integration, and automation will drive the next step-change in performance for the subsurface work environment. These capabilities will be applied to the associated work processes, tools and technology, and data and knowledge management practices as assets pass through the discovery, development, and production phases of their lifecycles. This will extend ExxonMobil's ability to realize both economies of scale and fit for purpose (scalable) subsurface solutions. 1
Management In information management and decision making, the "data commute" emerges repeatedly as a big problem in achieving more efficient workflows. SPE's Digital Energy Technical Section has conducted several in-depth statistical studies that show an unacceptable amount of time in the E&P workforce lost searching for data, integrating it from multiple sources, and preparing it for analysis in applications (Brulé et al. 2008; Hite et al. 2007; Mochizuki et al. 2006). Once engineering and operational data are in the application package for analysis, any updated or more recent data require a repeat of tedious, barren, and nonproductive processes to prepare and reload the data, a sort of "oilfield entropy" that is a drag on the E&P industry. The time that could have otherwise been spent making operational or project decisions is lost to activity that has nothing to do with engineering and geoscience. Some industry professionals might be resigned to dealing with data as just part of the workday, but most recognize a fundamental tenet: it is not the data per se, but decisions—based on data-derived information—that drive actions and create value(Fig. 1). We acknowledge the importance of engineering techniques, operational effectiveness, risk-factor evaluation, and project methodology, but here we separate them to examine and quantify just one assertion: making informed decisions would be quicker if the underlying necessary data are always ready to go. "If I can make that decision accurately, but a month earlier, and can do this across many projects, many wells, many fields…." Faster decisions with precision have tremendous value and provide much leverage in an industry already hindered by a shortage of qualified people. Contexts of Oilfield Integration Oilfield integration spans all areas of the oil and gas industry, from subsurface to surface to business. International oil companies (IOCs) currently have several oilfield-integration efforts as initiatives. Understanding the context of these oilfield integrations is important to understand what the IOCs are trying to accomplish. When we speak of integration, just what are we actually integrating? There exist several contexts of integration that must be recognized and accomplished to realize the vision of the digital oil field:Data integration—Data accessible to everyone, across disciplines, and consumable in softwareWorkflow and process integration—Combining and automating work processes for greater efficiencyDisciplines integration—The leverage of experts across disciplines like the geosciences, drilling, production, and reservoir (Mochizuki et al. 2006; Sankaran et al. 2009)
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