.png){kind=icon}
.png){kind=icon}
Return
DFN Modelling Constrained by Source Parameters for SRV Estimation Using Acoustic Emission
.png){kind=icon}
PRE
AI
DOI：10.1111/1365-2478.70152.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
The stimulated reservoir volume (SRV) is a central metric for assessing hydraulic-fracturing effectiveness, yet location-only microseismic methods struggle to capture its correspondence with fracture geometry. We present an SRV estimation workflow that integrates microseismic source parameters to impose physically meaningful constraints on a discrete fracture network (DFN). Specifically, hypocentre locations, equivalent source radii and focal mechanisms are used to construct a disk-based DFN; self-organizing map (SOM)-density-based spatial clustering of applications with noise (DBSCAN) clustering then identifies connected fracture sets; finally, SRV is computed by forming a non-convex envelope over boundary points of the disk elements. Synthetic case studies demonstrate that incorporating source information substantially improves the physical consistency of SRV estimates and strengthens their linkage to fracture structures. SOM-DBSCAN further enhances cluster separability and interpretability while guiding DBSCAN hyperparameter selection. Its application to laboratory acoustic-emission (AE) data demonstrates the practical feasibility of the workflow and highlights its potential transferability to microseismic interpretation. Future work will extend the framework to include additional source and medium parameters to further refine SRV estimation and fracture characterization.
Keywords:
interpretation
inversion
monitoring
passive method
reservoir geophysics
signal processing
Journal
G
IF:
1.8
Papers:
110
Citations:
6.0K