Automated Downhole Fluid Contamination Prediction via Iterative Curve Fitting
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Solution Overview
Problem
Conventional methods for predicting fluid contamination in downhole drilling operations are subjective and lack automation, leading to variable results that depend heavily on user experience, and fail to provide real-time updates.
Innovation Solution
An automated system that iteratively generates multiple curves fit to subsets of downhole fluid data, with validation using a remaining subset to determine best fit curves, allowing for real-time contamination prediction and eliminating outliers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional subjective methods are used for contamination prediction, then user experience can guide judgment, but the results become variable and non-repeatable
Solution Approach 1:
The patent replaces the mechanical/manual process of subjective contamination assessment with an automated computational system. The processing device automatically generates multiple curves, performs validations, and determines best-fit curves without human intervention, eliminating the variability inherent in user-dependent manual methods and ensuring consistent, repeatable results.
Solution Approach 2:
The patent changes the parameter of assessment from subjective user judgment to objective computational metrics. By using automated curve fitting and validation processes that operate on defined mathematical parameters, the system transforms contamination prediction into a quantifiable, repeatable measurement process independent of individual user experience levels.
2Measurement precision
If manual contamination assessment is performed, then detailed analysis can be conducted, but real-time updates are not provided
Solution Approach 1:
The patent replaces manual contamination assessment with an automated processing system that can rapidly analyze fluid data and generate contamination predictions in real-time. The computational automation eliminates the time-consuming nature of manual analysis while maintaining or improving assessment accuracy through systematic curve generation and validation.
Solution Approach 2:
The patent enables continuous real-time contamination prediction by automatically processing incoming fluid data without interruption. The system continuously generates curves, performs validations, and updates contamination assessments as new data becomes available, providing uninterrupted real-time monitoring rather than periodic manual assessments.
3Productivity
If automated curve fitting is performed on all fluid data, then processing speed increases, but accuracy decreases due to outliers
Solution Approach 1:
The patent segments the fluid data into multiple subsets and generates curves for each subset individually. This segmentation allows the system to process data in manageable portions while maintaining accuracy by focusing on local patterns in each subset, then combines results to form the overall contamination prediction.
Solution Approach 2:
The patent performs preliminary curve generation on data subsets before final validation. By pre-processing data into subsets and generating initial curves, the system prepares optimized candidate solutions that can be quickly validated against the remaining data, improving overall processing efficiency while maintaining accuracy through the two-stage approach.
Data Source
AI summary
Examples described herein provide a downhole sampling method that includes receiving fluid data from a fluid downhole in a wellbore operation. The method further includes defining a subset of the fluid data and a remaining subset of the fluid data. The method further includes iteratively generating, by a processing device, a plurality of curves fit to the subset of the fluid data. The method further includes performing, by the processing device, a validation on the plurality of curves as applied to the remaining subset of the fluid data to determine one or more best fit curves from the plurality of curves.