Non-Newtonian Fluid Modeling in Subterranean Reservoirs
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Solution Overview
Problem
Current methods for predicting fluid flow in subterranean reservoirs fail to accurately capture the behavior of non-Newtonian fluids due to their complex rheological properties, particularly near wells, due to inadequate integration of shear-thinning effects, permeability reduction, and adsorption, leading to inaccurate predictions.
Innovation Solution
A system and method that models non-Newtonian fluids by calculating 'effective' viscosity and incorporating shear-thinning effects, permeability reduction, and adsorption into numerical simulators, characterizing the skin zone with two parameters, and applying these parameters to Peaceman's well model for improved well modeling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional fluid flow models are used, then the modeling process is simple, but the prediction accuracy for non-Newtonian fluids is insufficient
Solution Approach 1:
The patent changes the rheological parameters from constant (Newtonian) to variable (non-Newtonian) by implementing shear-dependent viscosity models. The fluid viscosity is no longer a constant but varies with shear rate according to power-law or Carreau models, allowing accurate representation of shear-thinning behavior in heterogeneous porous media.
Solution Approach 2:
The model transitions from static viscosity assumptions to dynamic viscosity calculations that adapt to local flow conditions. The viscosity field becomes dynamic, changing continuously with the shear rate distribution throughout the reservoir, which is calculated based on the velocity gradients in the porous medium.
2Reliability
If shear-thinning effects are integrated into the well model, then the rheological behavior is captured more accurately, but the integration process becomes inadequate and requires additional validation steps
Solution Approach 1:
The patent merges the shear-thinning rheological model directly with the wellbore flow model and reservoir simulator. The non-Newtonian fluid equations are integrated into the governing flow equations, creating a unified model that simultaneously solves for pressure, velocity, and viscosity fields without requiring separate validation steps.
Solution Approach 2:
The patent introduces an intermediary computational framework that bridges the gap between conventional reservoir simulators and non-Newtonian fluid mechanics. This framework uses iterative solution methods to couple the shear-dependent viscosity calculations with the pressure-driven flow equations, enabling seamless integration of complex rheological behavior.
3Measurement precision
If conventional models are used for heterogeneous porous media, then the computational process is straightforward, but the flow behavior of non-Newtonian fluids near wells cannot be accurately captured
Solution Approach 1:
The patent segments the reservoir into regions with different flow regime characteristics, particularly distinguishing between the wellbore region (high shear rates) and the bulk reservoir (lower shear rates). This segmentation allows the model to apply appropriate rheological formulations in each zone, capturing the transition of non-Newtonian behavior from the well vicinity outward.
Solution Approach 2:
The model implements local quality by allowing different rheological parameters and flow regime assumptions in different spatial locations. Near the wellbore where shear rates are high, the full non-Newtonian behavior is captured, while in the bulk reservoir, simplified formulations may be used, optimizing computational resources while maintaining accuracy where it matters most.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach provides more accurate predictions of fluid flow for non-Newtonian fluids in heterogeneous porous media, particularly near wells, by accounting for complex rheological behaviors, leading to enhanced optimization of field operations and performance prediction.
Implementation Method 1
the integration of physical phenomena such as shear-thinning effect, permeability reduction, and adsorption
Implementation Method 2
the integration of physical phenomena such as shear-thinning effect, permeability reduction, and adsorption
Data Source
AI summary
A computer-implemented reservoir prediction system, method, and software are provided for modeling the behavior of non-Newtonian fluids in subterranean reservoirs while accounting for shear-rate dependent viscosity and permeability reduction with a skin zone characterized by a traditional skin factor and an apparent skin factor. A non-Newtonian fluid injection pressure or a non-Newtonian fluid injection rate is computed at steady-state responsive to reservoir data associated with a subterranean reservoir, injection data for a non-Newtonian fluid, and fluid data for the non-Newtonian fluid. The shear-rate dependent viscosity can further be applied to a well model in numerical reservoir simulation to improve the well model.