Correcting Relative Permeability for Accurate Water Breakthrough Prediction
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Solution Overview
Problem
Current geo-model simulations for predicting water break-through time in the petroleum industry often use large grid-block sizes to reduce computational time, but this leads to inaccurate predictions due to numerical dispersion, resulting in earlier water production and underestimation of water handling capacity, especially when using larger grid sizes.
Innovation Solution
The method involves obtaining initial relative permeability data, determining viscosity data, and generating corrected relative permeability data based on the flood-front saturation point to simulate water break-through time, allowing for more accurate predictions using larger grid sizes while reducing simulation runtime.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If large grid-block sizes are used in geo-model simulations, then simulation runtime is reduced, but prediction accuracy deteriorates due to numerical dispersion
Solution Approach 1:
The patent applies parameter changes by modifying the relative permeability data through a correction process that adjusts the flood-front saturation point. This transformation of the permeability parameters enables large grid-block simulations to produce accurate water break-through time predictions without suffering from numerical dispersion errors, thus resolving the contradiction between simulation efficiency and prediction accuracy
2Productivity
If large grid-block sizes are used in geo-model simulations, then computational efficiency is improved, but water handling capacity estimation deteriorates due to underestimation
Solution Approach 1:
The patent transforms the relative permeability parameters to correct the flood-front saturation point, which eliminates the underestimation of water handling capacity that occurs with large grid-block sizes. This parameter transformation maintains computational efficiency while improving the reliability of water handling capacity predictions
3Speed
If traditional relative permeability data is used with large grid sizes, then simulation speed is increased, but water production prediction deteriorates due to earlier breakthrough
Solution Approach 1:
The patent applies a correction transformation to the relative permeability data that adjusts the flood-front saturation point. This parameter change corrects the numerical dispersion effect that causes premature water breakthrough predictions, enabling fast simulations with large grid sizes to accurately predict water production timing
Data Source
AI summary
The present disclosure describes methods and systems, including computer-implemented methods, computer program products, and computer systems, for improving water break-though time predictions. One computer-implemented method includes obtaining, by a hardware data processing apparatus, a plurality of initial relative permeability data; determining, by the hardware data processing apparatus, viscosity data; determining, by the hardware data processing apparatus, a flood-front saturation point based on the viscosity data and the initial relative permeability data; and generating, by the hardware data processing apparatus, a plurality of corrected relative permeability data based on the plurality of initial relative permeability data and the critical fractional flow point, wherein the plurality of the corrected relative permeability data are used to simulate water break-through time.