Hydrocarbon Facility Layout Planning for Faster Well and Pipeline Siting
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Solution Overview
Problem
Existing automated planning systems for hydrocarbon facilities require significant processing power and time to determine suitable locations for components, often identifying only a limited number of components, leading to delayed operations and increased costs.
Innovation Solution
A modular approach using particle swarm optimization (PSO) and A* algorithms to simultaneously determine well, facility, and pipeline placements, reducing computational requirements and improving efficiency by considering topological complexities and cost factors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional automated planning systems are used to determine suitable locations for hydrocarbon facilities, then comprehensive analysis of geographical and cost considerations is achieved, but processing time increases to days and computational resources are significantly consumed
Solution Approach 1:
The planning system segments the hydrocarbon facility placement problem into distinct modules: well placement optimization, facility location determination, and pipeline routing. Each module is solved independently using specialized algorithms (particle swarm optimization for facilities, A* for pipelines), allowing parallel processing and reducing overall computation time from days to hours while maintaining comprehensive analysis of geographical and cost factors.
Solution Approach 2:
The system implements a multi-scenario approach where multiple planning scenarios are evaluated with varying levels of detail. Users can select from different analysis depths, allowing the system to perform comprehensive analysis when needed but also enabling faster, less detailed analysis for preliminary planning, thus reducing processing time while maintaining the option for thorough evaluation.
2Productivity
If traditional automated planning systems analyze a limited number of components (10-20 wells, drill centers, gathering centers, and central processing centers), then computational requirements are managed, but operational efficiency is reduced due to delayed operations and higher costs
Solution Approach 1:
The system dynamically adjusts the number and type of components analyzed based on user input and computational resource availability. Unlike traditional systems that are limited to 10-20 components, this system can handle hundreds or thousands of wells and facilities by dynamically allocating computational resources and adjusting analysis depth for different component types, thereby improving operational efficiency without being constrained by fixed component limits.
Solution Approach 2:
The system allows dynamic modification of analysis parameters including the number of components to analyze, the level of geographical detail, cost factor weights, and computational resource allocation. These parameter changes enable the system to efficiently handle large-scale projects with hundreds of wells and facilities while maintaining manageable complexity through adaptive parameter adjustment based on project requirements and available resources.
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.