CFD Subterranean Modeling for Wellbore-Formation Interaction
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Solution Overview
Problem
Conventional methods for predicting well performance in the oil and gas industry rely on simplified analytical approaches that neglect the complexities of the wellbore and formation interactions, leading to inaccurate predictions and potential formation damage during testing.
Innovation Solution
A computational fluid dynamics (CFD) modeling method that generates a geometrical model of a subterranean region including a wellbore and surrounding formation, associates physical properties with computational parameters, and inputs these parameters into the model to simulate fluid flow and account for formation damage, permeability, and other geological features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If simplified analytical approaches are used for well performance prediction, then the calculation speed is fast and the method is simple, but the prediction accuracy is poor and formation damage risks are not accounted for
Solution Approach 1:
The patent creates a virtual copy of the wellbore and formation system through computational modeling. Instead of using simplified analytical equations, the invention builds a detailed digital representation that replicates the complex physical interactions between wellbore structures and formation properties, allowing accurate prediction without physical testing
Solution Approach 2:
The patent transforms physical parameters (permeability, viscosity, formation damage factors) into computational parameters that can be processed by numerical models. This allows the system to account for complex formation damage effects and wellbore-formation interactions that simplified analytical approaches cannot capture
2Measurement precision
If detailed appraisal operations are performed within the wellbore to assess well performance, then the prediction accuracy is improved, but the fiscal expenditure and time expenditure increase significantly
Solution Approach 1:
The patent replaces expensive physical appraisal operations with a virtual computational model. The CFD simulation creates a digital twin of the well system that can be tested repeatedly without additional fiscal or time expenditure, eliminating the need for temporary completions and major in-well operations
Solution Approach 2:
The patent performs virtual testing and evaluation before actual well operations. By using CFD modeling to predict well performance and assess formation damage risks in advance, the system enables informed decision-making during the design phase, preventing costly mistakes before they occur
3Ease of manufacture
If conventional analytical approaches are used, then the method is simple to implement, but the ability to account for wellbore-formation interactions and formation damage is limited
Solution Approach 1:
The patent replaces simplified analytical mechanics with computational fluid dynamics. Instead of using analytical equations that assume homogeneity and ignore wellbore features, the invention uses numerical CFD methods that can capture complex fluid flow patterns, pressure distributions, and formation damage effects around the wellbore
Solution Approach 2:
The patent applies different properties and conditions to different regions of the computational domain. The CFD model allows local variation in permeability, viscosity, and formation damage factors around the wellbore, capturing heterogeneous formation properties and localized effects that analytical approaches cannot resolve
Data Source
AI summary
A method of computational fluid dynamic modelling of a subterranean region comprises: defining a computational domain by generating a geometrical model of a subterranean region comprising a wellbore and a surrounding formation; associating knowledge of a physical property of the subterranean region with a computational parameter; and inputting the computational parameter into the computational domain. In one embodiment knowledge of permeability within the subterranean region is defined as a viscous resistance within the computational domain.