Microseismic Signal Rotation for Source Parameter Accuracy
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Solution Overview
Problem
Current microseismic monitoring methods face challenges in accurately determining source characteristics and location of microseismic events, particularly in hydraulic fracturing operations, due to difficulties in interpreting faint signals and inferring necessary parameters without prior knowledge, which hinders reservoir control and understanding of fracture properties.
Innovation Solution
A method involving multi-component signal recordings from a single monitoring well, rotating these signals to a coordinate system where one component of the moment tensor is independent, allowing for the derivation of remaining components without assumptions, and decomposing the moment tensor into physically distinct subparts to classify and analyze microseismic events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multi-component signals are obtained from a single monitoring well, then the measurement precision of source parameters is improved, but the device complexity increases due to the need for signal rotation and moment tensor decomposition
Solution Approach 1:
The moment tensor is decomposed into physically distinct subparts (isotropic, compensated linear vector dipole, and shear components), allowing independent analysis of different source mechanisms. This segmentation enables precise characterization of microseismic events by separating complex source characteristics into manageable components that can be individually inverted from the multi-component signals.
Solution Approach 2:
The patent transforms the signal data from a single-azimuth recording system into a rotated coordinate system where the signals become independent of one moment tensor component. This dimensional transformation allows the remaining components to be derived without assumptions, effectively adding a mathematical dimension to the analysis that resolves the underdetermined nature of single-well measurements.
2Measurement precision
If signal rotation is applied to make signals independent of one moment tensor component, then the measurement precision improves by eliminating assumptions, but the processing time increases
Solution Approach 1:
The signal rotation transformation is performed as a preliminary step before moment tensor inversion, pre-processing the data into a coordinate system where one component is naturally independent. This preliminary action simplifies the subsequent inversion process by eliminating the need for iterative assumptions about the missing component, thereby reducing overall processing time despite the initial transformation cost.
3Measurement precision
If moment tensor decomposition into physically distinct subparts is performed, then the measurement precision of source characteristics improves, but the device complexity increases due to additional analysis steps
Solution Approach 1:
The moment tensor is segmented into physically distinct subparts including isotropic, compensated linear vector dipole, and shear components. This segmentation allows each subpart to be independently inverted and interpreted, providing precise characterization of different source mechanisms (e.g., volumetric expansion, shear slipping, or compensated linear dipole sources) from the same multi-component signal data.
Solution Approach 2:
Different subparts of the moment tensor are analyzed with different physical interpretations and constraints appropriate to their specific source mechanisms. The isotropic component is analyzed for volumetric changes, the CLVD component for linear dipole sources, and shear components for faulting events. This local quality approach allows precise characterization of specific source types without requiring complex analysis of the entire moment tensor as a single entity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances the accuracy of source parameter determination, enabling precise classification and characterization of microseismic events, improving reservoir control and fracture analysis without relying on assumptions like zero trace or non-volumetric source mechanisms.
Implementation Method 1
rotating the multi-component signals such that the multi-component signals become independent of at least one of the component of a moment tensor representing source characteristics of the microseismic event
Implementation Method 2
decomposing the moment tensor into physically distinct subparts to classify and analyze microseismic events
Data Source
AI summary
A microseismic method of monitoring fracturing operation or other microseismic events in hydrocarbon wells is described using the steps of obtaining multi-component signal recordings from a single monitoring well in the vicinity of a facture or event; and rotating observed signals such that they become independent of at least one component of the moment tensor representing the source mechanism and performing an inversion of the rotated signals to determine the remaining components.