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Doing more with data for offshore structures

Wednesday, January 30, 2019

We could do more with data for offshore structures if it was in standard formats, integrated into a 'digital asset', convenient to collect, consistent and collected, says Steven Coull of DNV GL.

How do we best leverage the power of data to facilitate more measured decisions about the safe operation of offshore structures?

The job of a structural engineer is to make informed decisions about the condition of the structure and decide if it is it still safe to operate.
These decisions require information about the current condition of the structure.

The structure will be installed in pristine condition, with everything exactly as it was designed, but much like your new car, fresh from the dealer, it does not stay that way. Offshore, environments are harsh and the structure will corrode, it will be damaged, new parts will be added and old parts taken away.

Working with data

To do this, a lot of data will be collected and assessed. The data comes from a diverse range of sources and includes weight management data, inspection findings, structural integrity models, and data from motion sensors.

All of this data contributes to the decision-making process in different ways. The only common thing about the data is that it is all different.

Data is a term that is frequently used, but not always understood. It can be considered as just one part of an overall model that captures how knowledge is collected, processed and acted upon. A common name for this is the Data, Information, Knowledge, Wisdom pyramid. The model describes the ability to make a wise decision.

Data is the first step in the process. It is the raw unrefined product, collected at source. Much like iron ore, it is of no use by itself.
You can't build a bridge with iron ore, and you can't do anything useful with data.

Data must be refined and organised, set in context, and connected to other data. The process yields information. Information is useful. Information is the carbon steel structural beam. It has purpose, but has yet to fulfil that purpose.

To make decisions with information, you need to assess it and understand it.

You build the knowledge based on the information you are presented with, or in the case of our steel beam, you build your bridge. Knowledge is the basis for 'wisdom', or the choices you make.

Connected, consistent, convenient

To achieve the maximum value from data, and generate high quality information, Data must be connected, consistent and convenient.

Connected data means being able to describe its relationship to other things in clear and unambiguous terms.

The singularly most challenging aspect of data is the lack of consistent formats. There are standard formats for some data, but a lot of data is supplied inconsistently. Different suppliers use different formats and some data lacks internal consistency.

A lot of these problems stem from the collection method. It is collected by humans with no thought to the wider application. Data also needs to be convenient. Too often the value of data is reduced to zero when we can't access it when we need it, which is unfortunate considering there is usually a cost to collect it.

The digital asset

The concept of a digital asset, or digital twin, has been around for some time.

These digital assets are usually presented as a 3D model of the structure, but that itself is not the digital asset, it is merely an interface.

The digital asset is the infrastructure underneath the 3D model, and is a simple concept. It is simply a list of things, but with a structure and a consistent way of describing things.

This is like your home address, a simple common way of describing where you live that allows different companies to deliver your mail.

What if each company used a different system to identify your location, or if different systems were used for different parts of the country? This is where we currently stand, with several different ways of describing the same thing.

Interoperability

This exposes another problem. How do you share data effectively between different systems, providers and consumers?

Different organisations invariably develop their own products and ways of supplying data.

This is a frustration to consumers of data who must adapt their systems to deal with different formats. Converting data is sometimes simple, but fidelity can be lost by the limitation of various formats.

The data we deal with today is mostly unstructured and disconnected. This significantly reduces the value of it as it cannot be used immediately.

What is needed are standards for data interoperability. This is a common ground that allows all data providers and consumers to speak in the same language without having to translate or interpret it. These standards must be developed outside of commercial enterprises. They must be open and adopted by all. The oil and gas industry must come together to achieve this, to agree the standards and to promote their use.

Data is there, we have been collecting it, but we have not been harnessing the power of it.

Instead we lock it away behind inconsistent formats, poor access and incomparable frames of reference. To unlock this data, we need a digital asset model that gives us a common frame of reference and standard data formats to allow the development of tools that will work together seamlessly. Most of all, it must be easy, and it can be if we build the correct foundations before we start.



Associated Companies
» DNV GL
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