Trading braces for digital transformation

The age of big data is transforming not just the upstream but energy’s spot markets

The oil and gas industry is rapidly investing in and accelerating a digital transition throughout its value chain. This means not just technological innovation in the E&P, midstream and downstream sectors, but across trading floors as well.

Data’s ability to transform the markets space may be less physically tangible, but that does mean its impact will be lesser. Trading business now aim to fuse billions of data points from—necessarily backwards-looking—customs data with synthetic aperture radar (SAAR) imagery from vast new constellations of satellites to create a real-time picture of global oil supply and demand balances.

Three pillars

The digital revolution has certainly been heralded before but there have historically been significant challenges with achieving the promised transformational impacts. But advances in three main areas—cloud storage, big data and machine learning (ML)/AI—may at last help to deliver on previous promises.

IoT solutions are able to tie together multiple threads of information

While the concept of cloud computing arguably traces its roots back to the early 1980s, the broader cloud computing revolution has not really taken hold until far more recently. In the context of digitalisation, its advent has facilitated leveraging HPC clusters—and the technologies that have become symbiotic with them such as ML and AI—to not only store the petabytes of data that the oil and gas industry generates in its normal course of business but also, more importantly, to facilitate the generation of actionable insight.

For participants not yet exploiting these opportunities one must only note the dedicated oil and gas solutions teams now housed within technology giants such Microsoft and Google to have a steer on how this story is only just starting to unfold.

Satellites gone up to the skies

On big data collection, the global industry is now being furnished with an ever broader array of tools in its arsenal; and with which it can then develop far faster feedback loops on process improvements, system optimisation or identify opportunities. In the trading sector, this is most manifest in the explosion in the number of satellites now orbiting the globe and the dramatic improvements in the quality and frequency of the information they are able to provide.

These ‘eyes in the sky’ are replacing the traditional ‘boots on the ground’ and are enabling technology startups—including OilX and a number of other cargo tracking specialists—to build a real-time digital picture of the global oil supply-demand balance. Crucially, this information is replacing far less granular data as the lynchpin around which oil majors, traders, end consumers, producers and refiners are basing their decision making around where surpluses and shortages may appear on both a time and geographic basis.

Whilst building up a picture of the global oil market has been a practice that has been commonplace for trading desks and research houses for decades, it has historically been extremely heavy on manpower—with huge gaps in information coverage in geographic regions with poorer data collection at grass roots.

This more granular aproach is unlikely to plateau, but instead to intensify. A potentially even more valuable data collection source tool that is really only starting to come into its own is the Internet of Things (IoT). Through firms like Disruptive Technologies—an IoT start-up based in Bergen, Norway—increased longevity of remote sensors, which can be deployed on mass at extremely low cost with almost no maintenance, changes the landscape for the possibilities of the volume of data that is now in scope for collection.

IoT solutions are able to tie together multiple threads of information and are able to not only minimise error rates on data collection but also provide real-time insight beyond what pre-existing instrumentation has been able to provide

The third and final piece of the digitalisation puzzle is data science techniques. The much vaster treasure trove of data can now be analysed in real-time to deliver actionable intelligence and generate immediate value—be it faster detection of potential structural defects in equipment in the upstream, or seeing potential shortages in specific geographic regions to exploit trading opportunities.

ML has become an invaluable weapon in predictive modelling to discover patterns based on an ever-growing variety of inputs which are being unlocked through the cloud and new data collection tools. Combined with AI, it allows the sector to test potential impacts of new developments at a scale never before achievable.

Andrew Toumazi is CEO and founder of Bloc-X, responsible for its strategy, vision, identity and capital position. Bloc-X’s mission statement is to be a cornerstone of catalysing efficiency in derivative markets.

This story was originally published at Petroleum Economist.