MODELING THE COST OF CONSTRUCTING AN OFFSHORE DRILLING RIG USING RANDOM FOREST
Keywords:
Random Forest, Offshore Drilling Rig, Cost DriversAbstract
Offshore drilling rigs are vital equipment for oilfield exploration and development; therefore, accurate estimates of their construction costs are crucial for planning rig construction projects. This paper explores the development of a random forest model to forecast offshore drilling rig construction costs. The model aims to provide accurate and reliable estimates of cost drivers based on a robust dataset that includes historical construction costs and rig design characteristics. The prediction-based ensemble learning approach used in the random forest algorithm effectively captures complex relationships and interactions in the data, improving forecast accuracy compared to traditional regression methods. The model's construction, validation, and significant findings will be detailed, highlighting its ability to minimize estimation errors and support decision-making in project budgeting. The objectives of this research encompass resource management, cost control, and strategic planning in rig construction projects.
