Optimized routing of interconnected subsea pipelines using geospatial cost-surface modelling

This study presents an innovative, fully automated pipeline routing model that integrates multilayer geophysical and regulatory datasets into a single cost surface model. Unlike conventional techniques that rely on manual route selection or simplified cost estimates, the proposed method allows for a systematic assessment of tradeoffs among cost, length, safety, and environmental impact. The proposed method leverages Geospatial analysis tools to convert geophysical data, environmental restrictions, and platform locations into a detailed cell-based geophysical model. This model is used to generate a composite cost surface that reflects real-world challenges such as seabed topography, geohazards, and protected marine areas. Using graph-based optimization algorithms, the system computes the least-cost main and lateral pipeline routes that interconnect source and destination nodes. The approach was tested on actual offshore field scenarios, where it successfully identified optimal pipeline alignments that cut overall project cost by up to 15% compared to conventional routing methods. The system demonstrated a significant reduction in pipeline crossings and length and ensured full compliance with environmental and safety regulations. These results confirm the effectiveness of the geospatial cost surface approach in delivering robust, efficient, and sustainable subsea pipeline designs.