Fusion of Engineering and IT Transforms the E&P Business

Abstract

Management The case for information technology’s (IT’s) direct value in E&P has been made for technical computing, real-time monitoring, workflow automation, data integration and quality, unified communications and collaboration, data mining, and artificial intelligence (AI) (Marks 2008; Brulé 2009). But few reservoir and production engineers acknowledge the fundamental need for IT in their everyday activities. E&P leadership abets this attitude with unofficial indifference to IT. The isolation of IT from the core E&P business was demonstrated when SPE held two Americas forums simultaneously, one reservoir engineering-oriented and the other IT-oriented (Shillings 2009). The two forums focused on the E&P business themes of “making better decisions” and “maximizing oil recovery,” but there was little interaction between them. E&P industry biases weigh against IT. IT has been characterized as “too thin” in E&P engineering and integrated operations (IO), and less relevant as digital oilfield (DOF) formulation moves into DOF 2.0 implementation (Holland 2009). One notion is that “E&P data analyses are different and we do more full-physics modeling than in other industries.” Another is that “we have advanced visualization and enough other technologies.” Further submerging IT below other E&P business concerns, decision-makers tend to focus more on where to explore and drill, and less on using IT to standardize and optimize subsequent operations (Mahdavi et al. 2009). Several case studies of companies outside the oil & gas industry show that when executive leadership mandates that IT be part of the company business model, corporate performance is clearly improved (Weill and Ross, 2009). Yet making IT a central part of the E&P business model is still among the “burning issues” of E&P chief information officers (CIOs). Different Backgrounds IT’s lack of familiarity is especially evident in modeling and simulation. A grasp of how to model the behavior of oil & gas systems is normally gained through formal training in math, physics, chemistry, engineering, and geoscience. Most IT specialists are unfamiliar with the basic laws of thermo-dynamics and fluid flow, and “bean-up guidelines for sand-control completions.” The tables turn when engineers transfer to an IT role without any computer-science training. Few engineers are familiar with IT architecture and governance frameworks such as TOGAF, ITIL, and CMMI, and “idempotent capability in cloud patterns.” Without a sound background in data structures, event-driven architecture, or development platforms, engineers may flounder in software and systems development. In IO and DOF 2.0 efforts, the engineer’s lack of an IT background may also lead them to confuse operations monitoring, control, and visualization vs. complex event processing and predictive analytics (Brulé 2009; 2010). To bridge the gaps between engineering and IT, some universities have begun offering a hybrid “digital petroleum engineering degree” with a dose of computer-science courses (Ershaghi et al. 2009).