Microseismic Data Segmentation for Fracture Network Characterization
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Solution Overview
Problem
Current microseismic processing techniques face challenges in accurately characterizing natural fracture networks and other textural elements in Earth formations, particularly during hydraulic fracturing operations, which affects the efficiency and precision of hydrocarbon production.
Innovation Solution
A method and system that process microseismic data from hydraulic fracturing events to identify and characterize natural fracture networks by determining the presence and location of microseismic events, creating a Voronoi diagram, calculating cell densities, and constructing a connectivity matrix to differentiate between hydraulic and natural fracture-related microseismicity, allowing for enhanced visualization and data storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional microseismic processing techniques are used, then the processing is simple and quick, but the characterization of natural fracture networks is inaccurate
Solution Approach 1:
The patent segments microseismic data into two distinct subsets: one associated with hydraulic fractures and another with natural fractures. This segmentation is achieved by analyzing event locations, densities, and spatial distributions to separate the mixed microseismic signals, thereby improving characterization accuracy of natural fracture networks while managing processing complexity through systematic classification.
Solution Approach 2:
The patent introduces an intermediary processing framework that acts as a mediator between raw microseismic data and final characterization results. This framework includes multiple processing stages (initial processing, subset identification, separation, and characterization) that systematically transform the data, improving accuracy while maintaining manageable complexity through structured intermediate steps.
2Loss of information
If microseismic data from hydraulic fracturing is analyzed, then information about both hydraulic and natural fractures is obtained, but the data is mixed and difficult to interpret
Solution Approach 1:
The patent extracts the signal related to natural fractures from the mixed microseismic data by identifying and removing events associated with hydraulic fractures. This extraction process uses criteria such as event location, density analysis, and spatial distribution patterns to isolate natural fracture events, thereby preserving information about natural fracture networks while reducing the difficulty of interpretation.
Solution Approach 2:
The patent applies partial action by focusing the analysis on specific subsets of microseismic events that are most indicative of natural fracture networks. Rather than attempting to analyze all events equally, the method selectively processes events that meet specific criteria (such as those occurring in particular spatial zones or with certain density patterns), improving interpretability while preserving critical information.
3Measurement precision
If the microseismic event cloud is used directly, then all events are included, but events from hydraulic fractures mask the natural fracture signals
Solution Approach 1:
The patent converts the harmful interference from hydraulic fracture events into a beneficial signal by using the spatial and temporal patterns of these events as reference information. By analyzing the distribution and characteristics of hydraulic fracture events, the method identifies zones and time periods where natural fracture events are most likely to occur, thereby improving detection precision while accounting for the presence of hydraulic fracture signals.
Data Source
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AI summary
This invention provides a method for characterizing natural fracture networks or other textural networks in an Earth formation when using microseismic monitoring of a hydraulic fracturing job. The method comprises receiving (120) microseismic data from a hydraulic fracturing event, identifying a data subset (153) comprising components of the microseismic data associated with the one or more hydraulic fractures; and obtaining a remainder dataset (156) of the microseismic data by removing the subset from the microseismic data. One approach for identifying the data subset, after removing high uncertainty microseismic events, is to create a Voronoi diagram of a plurality of cells each associated with one of the microseismic events, determine a density for each cell, create a connectivity matrix of the high density cells and identify event clusters in the connectivity matrix which are aligned with a main growing direction of the hydraulic fracture.