Fracture Network Permeability Estimation via Connectivity Index
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Solution Overview
Problem
Current methods for determining the permeability of fracture networks in hydrocarbon deposits are either costly in terms of calculation time or lack precision, particularly for complex and large-sized reservoirs, as they rely on numerical methods that are computationally intensive or analytical methods that make simplifying assumptions.
Innovation Solution
A method that discretizes the deposit into cells, calculates a connectivity index for each cell based on fracture intersections, and assigns permeability values using different estimation methods depending on the connectivity index, optimizing the calculation process by selecting the most precise method for each cell while minimizing computational effort.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If numerical methods are used to determine permeability, then measurement precision is improved, but productivity deteriorates due to computational intensity
Solution Approach 1:
The deposit is divided into multiple cells, and the fracture network is discretized into segments. This segmentation allows the application of different permeability estimation methods to different cells based on their specific characteristics, enabling a balance between accuracy and computational efficiency across the entire reservoir model
Solution Approach 2:
Different permeability estimation methods are assigned to different cells based on local fracture connectivity characteristics. Cells with high connectivity use analytical methods for speed, while cells with complex geometry use numerical methods for accuracy, optimizing the overall calculation process
2Productivity
If analytical methods are used to determine permeability, then productivity is improved, but measurement precision deteriorates due to simplifying assumptions
Solution Approach 1:
The method selectively applies analytical methods only to cells where simplifying assumptions are valid (low connectivity cells), while using more rigorous numerical methods in cells where geometric complexity requires higher precision, thus optimizing the trade-off between speed and accuracy
Solution Approach 2:
The fracture network is segmented into different connectivity zones, allowing the use of computationally efficient analytical methods in simple zones while reserving numerical methods for complex zones, thereby improving overall productivity without sacrificing necessary precision
3Measurement precision
If the deposit is discretized into many cells, then measurement precision is improved, but device complexity increases due to grid construction
Solution Approach 1:
The deposit is discretized into a structured grid of cells, which systematically organizes the complex three-dimensional fracture network into manageable two-dimensional slices. This segmentation reduces the overall complexity by breaking down the problem into smaller, more tractable units that can be processed independently
Data Source
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AI summary
The method involves determining a connectivity index within each of multiple cells depending on number of intersections between fractures by use of a geometrical description. A set of permeability of cells of the fracture network is estimated with the connectivity index above a threshold. A fixed permeability value is assigned within other cells with the connectivity index below the threshold to limit a number of permeability estimations. The development of the reservoir is optimized by simulating fluid flows in the reservoir as a function of permeability of the fracture network of each cell.