Introducing FieldTwin 8.0: See our release video, and sign up to our webinar to see a live demo!

Putting digital into practice with next-generation production modelling

Putting digital into practice with next-generation production modelling blog post illustration image

Jostein Lien

SVP Product

Digital twins promise so much on paper, but what value do they add in reality? Jostein Lien, Senior Vice President of Products at FutureOn, shares one operator’s success story in his latest blog examining the topic of digital integration.

The end goal of digital twin technology can be described in increased efficiencies of time and cost, but ultimately it is about improved results. 

Decisions taken in the earliest stages of subsea development have a particularly large impact on operations, which is what makes the ability to link layouts to accurate production modelling so crucial. 

One operator building cloud-based, multi-application digital twin capability has put FutureOn at the heart of transformational company-wide efforts; the goal is to establish full integration with both third-party and in-house software systems. 

Under the developing concept, subsea scenarios established in FieldTwin will be transferred into a separate digital software package already populated with relevant data necessary to establish a product forecast. 

Workflow inputs, scenario setups, models and configurations are used – in a fully automated process – to produce the forecast, which in addition to being stored in the dedicated software package is also fed back into FieldTwin for access. 

The latter allows for graphics of results across a number of profiles: production, temperature, pressure. 

An initial phase of the project was based on a simplified network of pipelines to illustrate the process of moving straight from FieldTwin to populating the hydraulic network. “You are then able to run export results, where you then can connect up the hydraulic network to the decline curves or a tank model, or to a more complex model using reservoir models”, said the company. 

Going forward, the integration will be expanded to include: reservoir representations, prosper models for wells, and booster options such as pumps, compressors and separators. User interfaces will be optimised, and evaluations are ongoing on some non-metadata elements. Cloud compatibility, the focus of an ongoing shift across oil and gas, is part and parcel of the digital twin approach. 

When complete, the production modelling approach will be able to define all required input metadata, build the relevant models, run calculations on demand, and export results for analysis and reference. 

Well models will be based on template designs stored in a shared library and include a minimum level of data: inflow, equipment, options and PVT. Solutions must be generic enough to cater for a wide variety of installations: oil, condensate, gas, gas-lifted oil, ESP oil, water injector and gas injector. 

The company is providing the FieldTwin concept as part of a longer-term ambition to extend digital twin solutions to operational assets. The technology is already used in topside processing and drilling. Further value will come in time through extension of the integration process into other areas: capex analysis, carbon efficiency calculators, concept reports. 

“This is where we want to get”, said the customer. “A tool that can give us an efficient concept selection and come up with the best concept in respect of value and CO2 footprint”. 

The effectiveness of any digital twin technology, and so its uptake across industry, is only as good as the building blocks behind the model – and FutureOn Recognises that among its client base, metadata is perhaps the most important. Creating an accepted standard for this crucial information, in an aligned and transparent fashion, will facilitate the next steps in the wide-ranging transformation promised by digitalisation. 

Generic metadata is certainly already available but many users and operators have opted to develop their own datasets for their own use cases. So you can of course have pre-set values but you can also modify for a specific field application, for example if you want to add additional data on a value such as maximum pressure.