Modular Hydrocarbon Facility Layout for Faster Placement Planning
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Solution Overview
Problem
Current automated planning systems for hydrocarbon production sites are inefficient due to high computational requirements and limited ability to process geographical complexities, leading to delayed operations and increased costs in determining optimal component placements for hydrocarbon extraction and processing.
Innovation Solution
A method using particle swarm optimization and A* algorithms to simultaneously determine well placements, facility placements, and pipeline placements based on geological and cost data, allowing for modular analysis and reduced processing power while accounting for topological complexities and prohibited areas.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional automated planning systems are used to determine component placements, then comprehensive analysis of geographical and cost considerations can be performed, but processing time increases to days and computational resources are excessively consumed
Solution Approach 1:
The planning system divides the analysis into discrete modular components including well placement modules, facility placement modules, pipeline routing modules, and trajectory design modules. Each module processes specific aspects of the planning problem independently, allowing parallel computation and reducing overall processing time while maintaining comprehensive analysis capabilities
Solution Approach 2:
The system transforms continuous geographical and cost parameters into discrete optimized variables that can be processed efficiently by computational algorithms. By parameterizing the problem in terms of optimizable variables with defined constraints, the system achieves both comprehensive analysis and computational efficiency
2Measurement precision
If traditional automated planning systems analyze component placements, then geographical and cost considerations are evaluated, but the number of components that can be analyzed is limited to 10-20 elements
Solution Approach 1:
The system segments the hydrocarbon operation into distinct component categories (wells, facilities, pipelines, trajectories) that can be analyzed simultaneously through modular computational processes. This segmentation enables the system to handle large numbers of components across multiple categories without being limited to analyzing only 10-20 total elements
Solution Approach 2:
The system performs comprehensive analysis on all components exceeding the traditional 10-20 component limit by implementing efficient algorithms that can process excessive quantities of data. The modular architecture allows the system to analyze entire fields with hundreds of components rather than being constrained to small subsets
3Measurement precision
If comprehensive component placement analysis is performed, then optimal locations can be identified, but computational power and hardware requirements increase significantly
Solution Approach 1:
The computational workload is segmented into independent modular tasks that can be distributed across multiple processors or computing nodes. Each module (well placement, facility placement, pipeline routing) consumes computational resources independently, allowing efficient parallel processing and reducing the peak computational power required compared to monolithic analysis approaches
Solution Approach 2:
The system uses simplified representative models and algorithms that can be replicated and executed efficiently across multiple computational units. By copying and adapting proven optimization algorithms for each modular component, the system achieves comprehensive analysis without requiring excessively powerful single-point computational hardware
4Measurement precision
If detailed pipeline routing and trajectory design are included in the analysis, then comprehensive placement optimization is achieved, but system complexity and processing requirements increase
Solution Approach 1:
The system segments the complex planning problem into distinct functional modules: well placement optimization, facility placement optimization, pipeline routing analysis, and trajectory design. Each module handles specific complexity independently with specialized algorithms, making the overall system more manageable and efficient than attempting to solve all aspects simultaneously in a single complex model
Data Source
AI summary
A method for identifying locations for components of a hydrocarbon production facility may involve receiving, via a processor, input data having one or more maps representative of an area, a plurality of sets of coordinates for a plurality of wells, and cost data associated with at least one of the plurality of components. The method may also involve determining a set of candidate components that corresponds to the plurality of locations based on the input data and an optimization algorithm and determining additional sets of candidate components that correspond to the plurality of locations based on the input data, the set of candidate locations, and the optimization algorithm. The method may then include generating one or more additional maps indicative of the plurality of locations for the plurality of components based on at least one of the one or more additional sets of candidate components.