Downhole Sampling Tool Relative Permeability Prediction
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Solution Overview
Problem
Existing in-situ formation fluid testing techniques often provide inaccurate results due to assumptions of miscibility between drilling fluid and formation fluids, which are immiscible, and require lengthy laboratory core analysis for accurate relative permeability and capillary pressure measurements.
Innovation Solution
A method and system utilizing a downhole sampling tool to perform theoretical and actual sampling operations, predicting and updating models for water-cut and drawdown pressure data based on estimated relative permeability and capillary pressure, iteratively adjusting parameters to match actual data, employing drift-flux or homogenous models to account for fluid immiscibility and tool geometries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If in-situ formation fluid testing techniques are used, then measurement time is reduced, but measurement precision deteriorates due to miscibility assumptions
Solution Approach 1:
The system performs iterative history matching where measured production data (water cut, pressure, rate) is fed back to adjust the numerical model parameters (relative permeability, capillary pressure) until the model predictions match the actual measurements. This feedback loop enables in-situ measurement without sacrificing accuracy despite the immiscible fluid condition
Solution Approach 2:
The invention changes the approach from direct measurement assuming miscibility to indirect measurement through parameter optimization. By treating relative permeability and capillary pressure as adjustable parameters in a numerical model that is optimized to match measured data, the system achieves accurate results under immiscible conditions
2Measurement precision
If laboratory core analysis is performed, then measurement precision is improved, but loss of time increases significantly
Solution Approach 1:
Instead of physically removing and analyzing core samples in the laboratory, the system creates a numerical copy (model) of the formation and performs virtual experiments by adjusting model parameters until they match field measurements. This virtual copying achieves laboratory-quality accuracy without the time delay of physical core analysis
Solution Approach 2:
The invention introduces a numerical model as an intermediary between field measurements and formation properties. The model acts as a mediator that translates production data (water cut, pressure, rate) into accurate relative permeability and capillary pressure values without requiring direct core sample analysis
3Device complexity
If existing in-situ testing algorithms are used, then device complexity is reduced, but measurement precision deteriorates due to incorrect miscibility assumptions
Solution Approach 1:
The system transitions from static algorithms with fixed miscibility assumptions to a dynamic numerical model where parameters are continuously adjusted during iterative history matching. This dynamic approach allows the model to adapt to the actual immiscible conditions in the formation while maintaining computational feasibility
Data Source
AI summary
An apparatus is operated to obtain a model predicting data associated with a theoretical sampling operation to be performed by a downhole sampling tool, including predicted water-cut and pressure data relative to time elapsed during the theoretical sampling operation. The model predicts the water-cut and pressure data based on estimated relative permeability and capillary pressure related to different constituents of fluid theoretically obtained from a subterranean formation by the downhole sampling tool during the theoretical sampling operation. An actual sampling operation is performed with the downhole sampling tool to actually obtain fluid and data associated with the actually obtained fluid, including actual water-cut and drawdown pressure data. The apparatus is then operated to update the model utilizing the actual data water-cut and drawdown pressure data, thus obtaining actual relative permeability and capillary pressure data.