Celtic Sea Floating Offshore Wind – Site Intelligence & Spatial Characterization

Executive Summary

This study establishes the site intelligence layer of Morie Analytics by transforming publicly available marine geospatial datasets into engineering-ready inputs for floating offshore wind development.

Using Celtic Sea lease areas, GEBCO 2025 bathymetry and EMODnet seabed classification, the workflow converts raw regional data into structured spatial products that support early-stage engineering decisions.

The result is a reproducible Python-based pipeline that replaces fragmented GIS workflows with a scalable and transparent offshore data-processing framework.

This module represents the entry point of the workflow, where raw geospatial data is converted into structured engineering inputs.

This article is the first study case within the Morie Analytics portfolio, a sequential engineering workflow for floating offshore wind development:

Site intelligence → Layout generation → Soil reconstruction → Mooring physics → Anchor verification → Cable optimization

Each module transforms upstream engineering information into progressively more detailed design constraints for downstream analysis.

Project Scope

• Screening of 5 Celtic Sea lease areas
• Processing of GEBCO 2025 bathymetry
• Integration of EMODnet Folk 7 seabed classification
• Generation of lease-scale bathymetry and soil maps
• Validation of local results against regional datasets

This study converts regional marine data into engineering-ready spatial constraints.

Engineering Context

Early-stage floating offshore wind design requires rapid and consistent evaluation of:

• Water depth and seabed slope distribution
• Seabed conditions
• Anchor feasibility constraints
• Mooring footprint implications
• Installation constraints

These assessments are often performed manually in GIS environments, leading to inconsistencies across projects.

This workflow introduces a structured computational approach, where public datasets are transformed into standardized engineering inputs suitable for downstream design modules.

Inputs and Data Sources

This study integrates publicly available marine geospatial datasets:

• Celtic Sea lease area boundaries
• GEBCO 2025 global bathymetry grid
• EMODnet Folk 7 seabed classification

The EMODnet classification is used here as a regional sediment screening dataset and not as a substitute for site-specific geotechnical investigation.

All datasets are:

• Harmonized into a projected coordinate system
• Spatially aligned
• Processed into engineering-ready formats

This provides the spatial data foundation for downstream modules.

System Flow

Raw Geospatial Data → Spatial Processing → Engineering Inputs

This modular structure ensures reproducibility, clarity and scalability.

Processing Workflow

For each lease area:

1. Import lease boundary
2. Transform coordinates to projected system
3. Load GEBCO bathymetry
4. Mask bathymetry within lease polygon
5. Load EMODnet seabed data
6. Intersect seabed classification with lease
7. Generate plots and structured outputs

This converts regional datasets into engineering-ready spatial constraints.

Regional Lease Context

Figure 1 – Regional lease areas used as the screening context for floating offshore wind development.

Engineering Significance

Offshore design begins at regional scale, where:

• Lease areas compete for feasible conditions
• Bathymetry and soils vary spatially
• Design assumptions must remain consistent

Bathymetry Characterization

Figure 2 – Lease-scale bathymetry used to constrain feasible layout regions.

The bathymetric dataset reveals water depths across the selected Celtic Sea lease areas typically ranging between:

• ~85 m to 100 m approx.
• Gentle slopes with gradual depth transitions

This results in a bathymetrically smooth environment, well-suited for floating offshore wind deployment.

Engineering Significance

Bathymetry directly informs:

• Floater type feasibility
• Mooring line configurations and geometry
• Anchor radius and footprint
• Cable routing constraints

From an engineering perspective, the observed depth range implies:

• Floating wind is prefered (fixed-bottom solutions are not economically viable at this depth scale)
• Mooring systems will operate in an intermediate-depth floating wind regime, where line compliance and footprint expansion remain dominant design considerations.
• Anchor locations must be designed considering relevant horizontal offsets and footprint expansion

The relatively mild seabed slopes enable:

• Stable and predictable mooring layouts
• Reduced risk of localized load amplification due to terrain effects
• Simplified cable routing with fewer constraints related to steep gradients

However, depth variability across the site still requires:

• Consistent normalization of mooring configurations (addressed in morie_mooring)
• Alignment of anchor design with local water depth conditions (addressed in morie_anchor)
• Consideration of cable touchdown zones under varying depth profiles (addessed in morie_cable)

This bathymetric characterization defines the geometric boundary conditions for all downstream engineering modules.

Seafloor Slope Characterization

Figure 3 – Seafloor slope map derived from GEBCO bathymetry.

The slope map was computed directly from the processed bathymetric grid in order to evaluate local seabed gradients across the lease area.

The results indicate a relatively smooth seabed morphology, with gentle regional gradients and limited occurrence of localized steep terrain.

Engineering Significance

Seafloor slope directly affects several downstream engineering processes:

• Mooring line touchdown behavior
• Anchor mudline load angle
• Cable touchdown and routing
• Installation accessibility and vessel operations

Even in relatively smooth environments, localized slope variations can influence:

• Horizontal and vertical load transfer at the seabed
• Mooring line equilibrium geometry
• Cable free-span risk
• Spatial variability of installation conditions

This additional spatial layer therefore complements bathymetry by introducing a first-order terrain constraint into the workflow.

Seabed Characterization

Initial Mapping

Figure 4 – Initial soil classification used for validation of processing steps.

EMODnet Classification Alignment

Figure 5 – EMODnet Folk 7 classification legend.

The EMODnet seabed dataset provides sediment classification at multiple levels of resolution:

• Folk-16 → highly detailed classification including mixed sediment types
• Folk-7 → intermediate engineering-relevant grouping
• Folk-5 → simplified classification for large-scale screening

In this workflow, the Folk-7 classification is selected as a balance between:

• Spatial resolution (soil horizontal variability)
• Engineering interpretability
• Compatibility with anchor and cable design models

This level preserves key distinctions (e.g., sand vs mud vs coarse material) while avoiding excessive fragmentation of sediment classes.

Engineering Mapping

Figure 6 – Soil classification aligned with EMODnet standards.

The processed map shows a predominance of sandy sediments across the selected Celtic Sea region, with localized variations including:

• Finer materials (mud-dominated zones)
• Coarser sediments and transitional layers

Engineering Significance

Seabed classification supports:

• Anchor concept screening (e.g., suction piles vs driven solutions)
• Soil-structure interaction assumptions (strength, stiffness, friction)
• Cable burial feasibility and protection requirements

From an engineering perspective, the predominance of sandy sediments suggests potentially favorable conditions for suction-assisted or driven anchor concepts, subject to confirmation through site-specific geotechnical investigation.

At this stage, the Folk-7 classification should be interpreted as a regional sediment screening layer rather than a direct indicator of geotechnical strength, relative density, installation feasibility or anchor capacity.

At the same time, localized heterogeneity highlights the need for:

• Site-specific soil reconstruction (addressed in morie_soil)
• Robust anchor design envelopes for mixed conditions (addresed in morie_anchor for a suction pile solution)

Regional Context Verification

Figure 7 – Regional seabed conditions across the Celtic Sea.

Local-to-Regional Validation

Figure 8 – Verification of lease-scale results within regional context.

Engineering Significance

Ensures:

• Spatial accuracy
• Classification consistency
• Traceability to source datasets

Outputs Generated

For each lease area:

• Bathymetry and soil classification grids
• Spatial plots
• Structured CSV summaries

These outputs are directly usable in downstream engineering workflows.

Engineering Applications

The outputs support:

• Lease-to-lease comparison
• Mooring system feasibility
• Anchor concept screening
• Cable routing strategy
• Installation feasibility and planning

This transforms raw geospatial data into engineering decision inputs.

Relationship to Other Morie Study Cases

This study is the entry point of the Morie Analytics workflow.

Feeds into:

• morie_layout → spatial layout optimization
• morie_soil → localized soil modeling
• morie_mooring → depth-informed system geometry
• morie_anchor → preliminary anchor feasibility
• morie_cable → seabed-aware routing constraints

It provides the baseline environmental context for all downstream modules.

Why It Matters Commercially

• Reduces reliance on manual GIS workflows
• Enables rapid multi-site screening
• Improves consistency across projects
• Accelerates early-stage decision making
• Provides scalable data infrastructure for developers

This is where data becomes engineering leverage.

Aspects to Improve

• Incorporation of higher-resolution bathymetry datasets
• Integration of geotechnical CPT data
• Inclusion of metocean conditions
• Automated constraint mapping (exclusion zones, cables, shipping)
• Incorporation of slope-based constraint filtering

These extensions would move the workflow closer to FEED-level site characterization.

Design Philosophy

Design Philosophy

The objective of this study is not to replace detailed site investigation, but to establish a transparent and reproducible regional screening workflow capable of transforming public marine datasets into structured engineering constraints for early-stage floating offshore wind assessment.

The study reflects the Morie Analytics approach:

• Physics-informed
• Modular
• Traceable
• Engineering-focused
• Scalable