Proppant Distribution in Discrete Fracture Network Simulation
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Solution Overview
Problem
The oil and gas industry faces challenges in accurately simulating hydraulic fracturing operations due to limited computational resources, making it difficult to optimize the efficiency and accuracy of proppant and proppant fluid phenomena in unconventional reservoirs with low-permeability rock matrices.
Innovation Solution
The implementation of a time-dependent spatial distribution of proppant effects within a discrete fracture network, which involves analyzing and predicting proppant behavior to optimize fracturing jobs in real-time, using a treatment control system that processes data from sensors and adjusts proppant types and sizes to enhance fluid flow and fracture propagation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If detailed simulation of proppant and fluid phenomena is performed to improve accuracy, then simulation accuracy is improved, but computational resource requirements increase
Solution Approach 1:
The patent segments the fracture network into discrete elements and divides the simulation domain into regions based on proppant transport behavior (e.g., proppant-filled regions vs. fluid-only regions). This segmentation allows detailed simulation only where necessary while using simplified models elsewhere, thereby improving accuracy in critical areas without proportionally increasing overall computational resources.
Solution Approach 2:
The patent applies partial action by performing detailed proppant-fluid interaction simulations only in specific regions where proppant is present and transport phenomena are critical, rather than throughout the entire fracture network. In regions where proppant effects are negligible, simplified fluid flow models are used, reducing unnecessary computational effort while maintaining sufficient accuracy.
2Adaptability or versatility
If multiple proppant types and sizes are used to optimize fracture properties, then fracture effectiveness is improved, but simulation complexity increases
Solution Approach 1:
The patent implements local quality by assigning different proppant properties (size, density, shape) to different regions of the fracture network based on local conditions such as stress state, fluid velocity, and fracture geometry. This allows the simulation to capture the nuanced effects of multiple proppant types in different locations without requiring a uniformly complex model throughout the entire system.
Solution Approach 2:
The patent employs dynamic adaptation of proppant characteristics during the simulation process, where proppant properties and distributions are updated based on evolving fracture conditions, fluid flow patterns, and stress fields. This dynamic approach enables the simulation to capture time-dependent proppant transport and deposition behavior, improving fracture effectiveness predictions while using efficient algorithms that adapt to changing conditions rather than requiring static complex models.
Data Source
AI summary
A hydraulic fracturing flow simulation method includes identifying a discrete fracture network that partitions a reservoir into porous rock blocks. The method further includes determining a current network state that includes flow parameter values at discrete points arranged one-dimensionally along the fractures in said network. The method further includes constructing a set of linear equations for deriving a subsequent network state from the current state. The method further includes repeatedly solving the set of linear equations to obtain a sequence of subsequent network states, the sequence embodying a time-dependent spatial distribution of at least one flow parameter, said flow parameter comprising a proppant volume fraction. The method further includes displaying the time-dependent spatial distribution.


