Quantification of Uncertainty in Field Layout Design of Subsea Production System

Abstract

Abstract The objective of this work is to study the effect of variability in the well flowrate and well target location on layout design of subsea production system. This work introduces an uncertainty quantification approach to assess the variability in subsea production system layout design, utilizing a subsea layout simulation frame-work which incorporates several design considerations such as well target locations in the reservoir, wells per manifold, bathymetry of the seabed, exclusion areas on the seabed, flow assurance, metocean considerations, flowline laying considerations, and pigging of flowlines. This simulation framework encompasses a collection of subsystem-level models, namely drill center clustering, manifold positioning, process host positioning, and flowline design. Algorithmic methodologies adeptly address each individual subproblem. The uncertainty quantification approach incorporates both random and deterministic variables of the field layout design. Random variables stem from the stochastic nature of reservoirs. Latin hypercube sampling serves as the foundation for generating required input samples. Modeling of the well flow rates involves treating them as correlated random variables, leveraging reservoir-specific characteristics. Furthermore, modeling of the well target locations employs uncorrelated random variables. The proposed approach’s effectiveness undergoes rigorous scrutiny via two real-world use cases aimed at studying field layout design variations, including manifold numbers, flowline length, and total cost index. Generated correlated flow rates for wells adhere to a given probability density function, where correlation coefficients consistently exceed 0.9, aligned with reservoir-specific characteristics. Moreover, the proposed simulation model framework achieves the generation of feasible designs that fulfill specified design requirements. Within uncertainty analysis, deterministic inputs of the subsea layout simulation model remain constant, and the number of solutions is varied based on the number of production wells. Use case 1 and 2 involve 19 and 37 production wells, respectively. For each design sample, use case 1 and 2 produce 68 and 132 design alternatives, respectively, and generated results are ranked based on the total cost index to select the top performing design. Finally, each use case presents a statistical summary detailing the flowline length and total cost index. The results show that the proposed uncertainty quantification approach can quantify the variation in the field layout design of subsea production system. The proposed simulation model framework gives different feasible design options by changing the solution parameters. The novelty of the proposed approach is its ability to incorporate stochastic nature of reservoir and geological condition into initial design stages. The current approach takes both the deterministic and random variables into account while designing the field layout. Also, the simulation model framework presented is novel, and it produces different feasible design options by changing the solution parameter while considering all the specified design requirements. This approach is incredibly useful for the field layout design engineer to consider different feasible design alternatives.