Agile Digital Twins: Developing gas fields faster, better and with more certainty

Duncan McLachlan's picture
Duncan McLachlan, Director QHSSE & Digital Innovation, io oil & gas consulting
Himadri Singh's picture
Himadri Singh, Senior Commercial Advisor, io oil & gas consulting
John Ciccarelli's picture
John Ciccarelli, Senior Reservoir Consultant, io oil & gas consulting
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It can take months, perhaps a year or two, to get through the Front End Loading (FEL) stages with current industry approaches to large gas projects. A much faster, lower risk approach should be taken as an alternative that avoids eroding value. The value must be realised sooner i.e in pre-FEED and the best way to do this is with a collaborative multi-disciplinary team working in an agile way to understand and model the technical and commercial aspects of each concept.

Agile project management techniques and best practices are used widely in the automotive, aerospace, construction, software development industries and lean start-up companies. Applying these techniques to field development concept selection means parallel, collaborative sprints where technical and economic models are created. These models are then combined to form a dynamic systems model, or a FEL 0 Digital Twin, which can be optimised around quantifiably defined value drivers. This Digital Twin also allows alternative solutions to be tested in near real time, parallel to the main project path, such that alternative proposals can be quickly ruled in or out without derailing the progressing project.

This approach has been successfully applied to several projects, one example was an offshore compression project where the optimum development concept was multi-dependent and non-obvious. In this example, the subsurface, developments and economics groups worked in parallel to develop models, which were brought together to create a digital representation of the field (a Digital Twin), its challenges and the solution space. The Digital Twin dynamically linked reservoir depletion, facilities sizing (including the installation of new compressors), flow, pressure, power and economic relationships. This led to a concept that gave the optimal size of a new compression platform to maximise the value to the Client. Following this successful concept selection, the project is now in execution phase – detailed engineering. 

In this example, this approach delivered:

  • Clarity of a multidimensional problem with a non-obvious solution;
  • An optimum economic compression solution for a complex group of 350 wells intersecting different reservoirs;
  • An 18month acceleration of the decision process;
  • A 30% cost saving, adding to project value.

This approach not only accelerates the decision-making process in the early stages of a gas development but also brings more certainty. By using decision analysis techniques, such as Analytical Hierarchy Process, it brings greater certainty that the decision taken is the best in terms of the value drivers for a specific development. Further to this, the dynamic nature of the Digital Twin ensures that should there be a major change in the macro techno-economic context of the development; fluctuations in the gas price, new technology coming to market, regulatory changes, then the solution can be re-evaluated, and the new optimal solution developed in a matter of hours.

In conclusion, by working with best practice techniques from other industries, in an agile manner, it is possible to reach solutions to the challenges of developing gas fields faster, better and with more certainty. The approach also demonstrates the ability to provide solutions that drive optimum gas monetization concepts, helping operators maximise the value of their portfolio. Finally, the dynamic nature of the Digital Twin allows an ongoing re-evaluation and optimisation of the solution when the macro techno-economic climate fluctuates through the development phase of a gas development.

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Image courtesy of Wikimedia Commons