Offshore support vessels (OSVs) play an important role in the smooth operations of various offshore activities. Such activities often require precise station-keeping for OSVs, and either mooring or Dynamic Positioning (DP) is used in this regard. OSVs such as Geotechnical Drilling Vessels generally use spread mooring or DP for station keeping, and most of these vessels are equipped with both systems on-board because of diversity, complexity, and a limited number of vessels in the market. Besides, having both systems on-board helps to cover all ranges of water depths.
However, determining which systems to use for a particular operational scenario depends on many factors and requires significant balancing among them in terms of cost-benefit. Therefore, this research aims to develop a platform that will determine the cost factors involving fuel oil cost and vessel charter rate for both the spread mooring and dynamic positioning based on common operational variables and constraints encountered by geotechnical vessels. Operational information and cost data are collected for several field operations involving both the use of DP and spread mooring, and Artificial Neural networks (ANN) are trained using those collected data samples.
After that, the trained ANN is used to predict the components of cost for any given environmental situation, days of fieldwork and water depth. Later on, the total cost was investigated against water depth for both DP and Spread Morning system to determine the most cost-effective means for station keeping. The results are validated using two operational scenarios for a specific geotechnical vessel. The vessel was operating at two different water depths for different days of fieldwork and using DP for one operation while spread mooring for others.
This decision making algorithm can be further developed by adding up more operational data and scenarios for various vessels. The result gathered from this research can be applied in the development of sustainable decision making business model for geotechnical drilling vessel and other OSVs operators.