Barycentric Interpolation for Wellbore Fluid Property Prediction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for designing well bore treatment fluids are labor-intensive and require extensive testing to predict properties like rheology, leading to increased costs and reduced efficiency in subterranean operations.
Innovation Solution
The use of Barycentric interpolation to develop models that predict properties of well bore treatment fluids, allowing for the design of fluids with optimized rheology and reduced laboratory testing, thereby saving time and costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If extensive laboratory testing is used to predict fluid properties, then measurement precision is improved, but loss of time and productivity deteriorate
Solution Approach 1:
The patent applies preliminary action by developing prediction models using historical fluid formulation data and laboratory test results before actual fluid design. The system pre-processes and stores relationships between fluid compositions and their properties (rheology, fluid loss, gel strength, etc.) in a database, enabling rapid prediction without repeating extensive laboratory testing for each new fluid formulation.
Solution Approach 2:
The patent uses copying by creating virtual representations of fluid formulations and their properties through computational models. Instead of physically testing each fluid formulation, the system copies existing formulation-data relationships from the database to predict properties of new formulations, significantly reducing the need for physical laboratory testing while maintaining prediction accuracy.
2Manufacturing precision
If extensive laboratory testing is conducted to determine fluid properties, then manufacturing precision is improved, but productivity deteriorates
Solution Approach 1:
The patent replaces the mechanical system of physical laboratory testing with an information-based computational system. The prediction model uses computer algorithms to calculate fluid properties based on composition data, substituting physical experimentation with computational analysis. This substitution maintains formulation accuracy while dramatically improving design productivity and reducing laboratory resource requirements.
Solution Approach 2:
The patent applies parameter changes by transforming the fluid design process from physical experimentation to computational parameter analysis. The system varies composition parameters (chemical additives, concentrations, ratios) in the prediction model to optimize fluid properties, replacing physical formulation adjustments with computational parameter optimization. This enables rapid evaluation of multiple formulations without proportional increases in laboratory testing.
3Reliability
If traditional fluid design methods are used, then reliability is maintained, but loss of time increases
Solution Approach 1:
The patent implements feedback by using actual laboratory test results and field performance data to continuously refine and update the prediction model. The system incorporates feedback loops where new formulation-test data pairs are added to the database, improving the accuracy and reliability of predictions over time. This feedback mechanism ensures that the computational model remains aligned with actual fluid behavior while reducing overall testing time through more accurate initial predictions.
Data Source
AI summary
Methods and systems for predicting properties of well bore treatment fluids are disclosed. An embodiment includes a method of predicting fluid properties comprising: determining an operational window for a well bore fluid system; collecting data at vertices of the operational window; and developing a model comprising predicted properties for a plurality of data points within the operational window, wherein developing the model uses Barycentric interpolation.


