Page 42: of Offshore Engineer Magazine (Apr/May 2014)

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Geology & Geophysics

An explosion of data and ever more complex work ? ows requires new ways of working in order to realize the digital oil? eld goal. Ray Millward ©iStock.com/DrAfter123 addresses the issue.

Image from Tessella-

Advanced analytics in the digital oil ? eld: A team game s sensor deployments prolifer- on their local drive, for example process- computing specialists have a more robust ate, and digital oil? eld tech- ing rate and pressure history data to ? nd mathematical background, and are able to

A nologies continue to mature, trends in order to formulate a model, or introduce new computational techniques operators are increasingly looking at how processing surfaces to ? nd features and to solve subsurface problems. to make best use of their data asset, from model time dependent behavior. It is now feasible to ask new kinds the raw seismic data through to generated These localized innovations could of questions of huge data sets, and to data from reservoir simulations. then be shared with other specialist use high performance computing to get

The goal for the digital oil? eld is to colleagues, or passed onto IT depart- answers in minutes instead of days. The create a more powerful fusion of historic ments for commercialization and large dif? culty, however, is in matching up the data, present knowledge, and predic- scale release. Today, however, there is an right kinds of algorithms to solve subsur- tive modelling, allowing future operat- explosion in data quantities from sources face problems in the most ef? cient way. ing decisions to be as near to optimal as such as ? ber equipped wells, continu- Problems can arise when there is makes economic sense. In an industry ous seismic monitoring, and increasingly insuf? cient overlap between the domain with so many expert disciplines, the big- large simulation grids, and there’s a cor- knowledge of the SME and of the techni- gest dif? culty is to ensure that specialist responding increase in the complexity of cal computing specialists. This runs the engineers are equipped with the right upstream architecture and work? ows. risk of delivering a project with a set of analytics tools and able to access the This makes it harder for SMEs to tools that ask the wrong questions and right data, at the right time. Only then maintain the necessary expertise in both delivers insight which does not meet the can they quickly gain the right insight their specialist area, as well as in profes- original brief. through which to make better decisions. sional software engineering, which itself An overlap in domain knowledge is

In the past, subject matter experts continues to evolve apace. Even those necessary to ensure that when the SMEs (SMEs), such as geophysicists, reser- SME’s with sharp software engineering and technical computing specialists col- voir engineers, and well test engineers, expertise struggle to make writing new laborate, they are able to understand each had been able to learn enough software code a priority amongst the other press- other suf? ciently to create a suitably broad engineering to analyze the data directly ing demands on their time. problem space that fully de? nes and available to them and, unaided, make To alleviate this, there has been an interprets the problem at hand, so that it improvements to their analytical tools emerging rise in the number of small is possible to explore a broad variety of and platforms. Typically, SME’s can write teams and departments responsible relevant solution strategies. In this way, functional programs that work with ? les for technical computing. Technical the SME is able to learn about how new

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