Multivariate Seismic Fracture Modeling
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Solution Overview
Problem
Current methods for modeling fracture networks in subterranean formations struggle to differentiate between natural and induced fractures, which hampers the effectiveness of hydraulic fracturing treatments and reservoir modeling.
Innovation Solution
The use of multivariate analysis to correlate seismic attributes with petrophysical properties and microseismic data, enabling the identification of fracture origins and improving completion design and reservoir modeling by creating detailed maps of fracture networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional fracture network modeling methods are used, then the modeling process is simple, but the ability to differentiate between natural and induced fractures is poor
Solution Approach 1:
The patent segments the fracture network modeling process by separately characterizing natural fractures and induced fractures using distinct data sources and analysis methods. Natural fractures are identified through seismic attribute analysis, while induced fractures are detected through microseismic event analysis, allowing differentiated modeling of each fracture type
Solution Approach 2:
The patent merges multiple data sources including seismic data, microseismic data, and geomechanical data into an integrated fracture network model. This combination enables simultaneous visualization and analysis of both natural and induced fractures within a unified three-dimensional model
2Measurement precision
If detailed multivariate analysis is performed to correlate seismic attributes with petrophysical properties and microseismic data, then fracture identification accuracy improves, but computational complexity and data processing requirements increase
Solution Approach 1:
The patent introduces an integrated fracture network model as an intermediary that synthesizes information from seismic attributes, petrophysical properties, and microseismic data. This intermediary model correlates multiple data sources through standardized fracture parameters, reducing the direct computational complexity of multivariate analysis while maintaining identification accuracy
Data Source
AI summary
A multivariate analysis may be used to correlate seismic attributes for a subterranean formation with petrophysical properties of the subterranean formation and/or microseismic data associated with treating, creating, and/or extending a fracture network of the subterranean formation. For example, a method may involve modeling petrophysical properties of a subterranean formation, microseismic data associated with treating a complex fracture network in the subterranean formation, or a combination thereof with a mathematical model based on measured data, microseismic data, completion and treatment data, or a combination thereof to produce a petrophysical property map, a microseismic data map, or a combination thereof; and correlating a seismic attribute map with the petrophysical property map, the microseismic data map, or the combination thereof using the mathematical model to produce at least one quantified correlation, wherein the seismic attribute map is a seismic attributed modeled for the complex fracture network.