Digital Twin Case Study

Deep-Sea Mining Digital Twin

We built a digital twin of an offshore deep-sea mining system, including an integrated physics engine and offshore modelling, helping our client understand and optimize their concept.

Background

Increasing computing power, analytics and use of machine intelligence in engineering work has allowed for the development of "digital twins" of intended or real-world physical systems and processes.

A recent McKinsey article highlighted that 75% of companies in advanced technology industries have already adopted digital twins, and it forecast a $74 billion industry by 2027.

Digital twins can replicate system behaviour in virtual environments that include physics engines, finite-element analysis, and other engineering and data inputs. The results are accurate models of complex systems that can be used to model parameters, test scenarios, and optimise revenue streams.

"75% of companies in advanced technology industries have already adopted digital twins"

McKinsey research

Deep-Sea Mining Digital Twin

Hidden Gem production support vessel

A deep-sea mining client approached us to develop a digital twin for their offshore mining concept. This was to be used for engineering design and optimization purposes, but also as a unique and insightful way to educate investors about their approach.

The result was a comprehensive and accurate digital twin of the entire offshore deep-sea mining production concept. This included various surface vessels, including a production vessel and offshore support vessel; multiple subsea harvesters and analysis of their running and pulling processes; riser and line interactions, including buoyancy and tension calculations; and dynamic modelling of the entire system underway and in various sea-states.

Dynamic Modelling with Physics Engine

Real-world loads, scenarios and reactions with accurate physics

Each major system and sub-component was imported into the digital twin and integrated into a single dynamic model. An accurate physics engine with hydrodynamic properties was applied in order to model offshore operations in various sea-states.

This allowed us to analyze a variety of operations and scenarios in detail. For example, the harvester launch sequence (right) exerts a varying dynamic side load on the offshore support vessel and is further complicated by wave forces exerted at the splash zone. We were able to accurately model launch and recovery in various sea-states.

Operations Analysis

Accurately model complex operations and engineering parameters

Subsea harvesters gather polymetallic nodules and convey them to a riser via buoyant hoses. Loads on the equipment, hoses and riser are a function of multiple complex and interlinked variables, including production rates, harvester speeds, sailing speed and prevailing currents.

We modelled the complete harvesting process, including the use of 4 harvesters in simultaneous operations. This allowed us to calculate these engineering parameters in a variety of different states and operating conditions.

Production Optimization and Economic Analysis

Optimize economics for the entire concept

An integrated model of the entire deep-sea mining system allowed us to explore sensitivities and understand the operational limitations of the concept. As a result we were able to deliver key insights and improvements to the concept.

This level of modelling brought real-world optimizations that have improved our client's concept, project economics, and subsequent ability to successfully fundraise.

Use-Cases

Digital twins can be used throughout a project lifecycle to better understand the concept

Dynamic Modelling

Accurate digital models combined with a physics engine and engineering parameters allow for accurate modelling of real-world loads, scenarios and operations.

Operations Analysis

Complex engineering scenarios and loads can be accurately recreated and modelled, allowing unique and deep understanding of operating parameters and limits.

Production Optimization

Possessing a holistic model of large complex systems allows engineers, operators and managers to optimize production parameters, and consequently improve project economics and financeability.

Applications

Digital twins are best suited to complex concepts with highly variable dynamic parameters and subsystems with coupled performance.

Deep-Sea Mining

Deep-sea mining digital twin

Complex and innovative new production concepts being developed in deep-sea mining lend themselves to digital twins in order to understand operating limits and complexities.

Offshore Wind

Offshore wind farm image

The increasing size of offshore wind turbines results in large structures that undergo huge, complex, dynamic forces. Digital twins allow for accurate modelling of these loads under various scenarios.

Oil & Gas

Digital twin diagram of an offshore oil and gas installation

Digital twins of drilling and completion operations, production processes, and pipeline flows can help you easily monitor assets, optimize production and implement effective predictive maintenance.

Our Services

concept evaluation icon

Concept Evaluation

Concept evaluation for complex and innovative offshore projects, including deep-sea mining and offshore wind manufacture.

Technical Feasibility Study icon

Technical Feasibility Studies

Techno-economic feasibility studies of complex offshore mining systems, floating wind concepts, and new manufacturing techniques

Economic Analysis icon

Economic Analysis

Financial modeling and economic analysis of concepts, including NPV, IRR and project sensitivities.

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Prototype Development & Testing

Construction, development and testing of prototypes for complex offshore projects and challenges.

Finite-element modeling icon

Finite-Element Modeling

Fluid-flow, hydrodynamics, mechanical stresses and other complex marine finite-element modeling challenges.

Mooring load & fatigue analysis icon

Mooring Load & Fatigue Analysis

Analysis of mooring loads and fatigue analysis for moored, tethered and other bottom-secured solutions in offshore wind.

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