Oil and gas industry as an example for peripheral cloud systems

Original author: Michael Hay
  • Transfer

Last week, my team hosted an exciting event at the Four Seasons Hotel in Houston, Texas. It was dedicated to the continuation of the tendency to develop closer relations between the participants. It was an event that brought together users, partners and customers. In addition, the event was attended by many representatives of Hitachi. When organizing this enterprise, we set ourselves two goals:

  1. Foster interest in ongoing research on emerging industry issues;
  2. Check the areas in which we are already working and developing, as well as their adjustment based on user feedback.

Doug Gibson and Matt Hall ( Agile Geoscience ) began with a discussion of the state of the industry and various problems associated with the management and processing of seismic data. It was quite inspiring and certainly revealing to hear how the volumes of investments are distributed between production, transportation and processing. Most recently, the lion's share of investment went into production, which was once the king in terms of the amount of funds consumed, but gradually the investments are transferred both to processing and transportation. Matt described his fascination with literal observation of the geological evolution of the Earth using seismic data.

In general, I believe that our event can be considered as the "first publication" for the work that we started several years ago. We will continue to inform you about various achievements and successes in our work in this area. Further, inspired by one performance by Matt Hall, we held a series of sessions that resulted in a very valuable exchange of experience.

Peripheral (boundary) or cloud computing?

At one of the sessions, Doug and Ravi (Hitachi Research in Santa Clara) had a discussion on how to transfer some analytics to peripheral computing for faster and more accurate decision making. There are many reasons for this, and I think that the three most significant of them are narrow data transmission channels, large amounts of data (both in terms of arrival rate, volume and variety), and tight decision-making schedules. Despite the fact that some processes (especially geological ones) may take weeks, months or years to complete, there are still many cases in this industry where urgency is of particular importance. In this case, the inability to access a centralized cloud can have disastrous consequences! In particular, issues related to HSE (health, safety and the environment), as well as issues related to oil and gas production, require quick analysis and decision making. Perhaps the best way is to show this using different numbers as examples — let specific details remain anonymous in order to “protect the innocent.”

  • Last mile wireless networks are being upgraded in places such as the Perm basin, with the passage of channels from the satellite (where the speed was measured in kbit / s) to a 10 Mbps channel using 4G / LTE or an unlicensed frequency range. Even these upgraded networks may not be able to cope with collisions with terabytes and petabytes of data at the border.
  • Sensor systems from companies such as FOTECH, which combine with many other new and long-running sensor platforms, are capable of producing several terabytes per day. Additional digital cameras, which are installed for security monitoring and anti-theft protection, also generate a large amount of data, which means that a complete set of big data categories is formed at the border (volume, speed of arrival and variety).
  • In the case of seismic systems used to collect data, projects include converged systems placed in ISO containers to collect and reformat seismic data potentially up to 10 petabytes of data. Due to the remote locations in which these intelligence systems operate, there is a serious lack of bandwidth to move data from the last mile border to the data center across networks. Therefore, service companies literally send data from the border to the data center on tape, optical, or durable magnetic storage devices.
  • The operators of brownfield factories, where thousands of events and dozens of “red alarms” take place daily, want to work more optimally and stably. However, networks with a low data transfer rate and the almost complete absence of storage facilities for collecting data for analysis in factories suggest that something more fundamental is required before starting a basic analysis of current operations.

This, of course, makes me think that while the providers of public cloud systems are trying to transfer all this data to their platforms, there is a harsh reality that you need to try to cope with. Perhaps the best way to classify this problem is to try to push the elephant through a straw! However, many of the merits of the cloud are essential. So what can we do?

Peripheral Cloud Transition

Of course, the Hitachi market already has (industry-specific) optimized solutions that enrich data at the border, analyze and compress it to the minimum usable amount of data, and also provide business advisory systems that can improve peripheral computing processes. Nevertheless, my conclusion made last week is that the solutions to these complex problems concern not so much the widget that you bring to the table, but the approach to solving the problem. This is truly the spirit of Hitachi Insight Group’s Lumada platform, as it includes methods to attract users, ecosystems and, if necessary, provides discussion tools. I was very happy to return to solving problems (and not selling products) because Matt Hall said: “I was glad to see

So can O&G (oil and gas industry) be a living example showing the need for peripheral computing? It seems that, given the problems discovered during our summit, as well as other industry interactions, the likely answer is yes. Perhaps the reason for this is so clear, because peripheral computing, industry targeting, and a mix of cloud-based design patterns are evident as stacks upgrade. I believe that in this case the question of “how” deserves attention.

Using Matt's quote from the last paragraph, we understand how to push the principle of cloud computing to peripheral computing. In fact, for this industry, we must conduct “old-fashioned” and sometimes personal contacts with people who participate in various parts of the ecosystem of the oil and gas industry, such as geologists, drilling engineers, geophysicists, and so on. Given these interactions that need to be addressed, their scope and depth become more obvious and even convincing. Then, when we draw up implementation plans and bring them to life, we will decide to build peripheral cloud systems.

However, if we sit in the center, just read and present these problems, we will not have enough understanding and sympathy to really do our best. So, once again, yes, oil and gas will generate peripheral cloud systems, but it is the understanding of the real needs of users on the ground that will help us determine what problems are of primary importance.

Also popular now: