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Understanding flow behavior in a geothermal reservoir is important for managing sustainable geothermal energy extraction. Fluid flow in geothermal reservoirs generally occurs in complex existing fracture systems in which the reservoirs are situated in highly fractured rocks. To simulate a discrete fracture model, the location and orientation of the fracture were computed using statistical processes and observational data. In many cases, estimating the location and orientation of fractures from 1D borehole logging data is challenging. In this study, we used microseismic data to build the fracture network systems and extract the detailed positions and dimensions of the fractures. We used the microseismic data recorded at the Okuaizu Geothermal Field, Fukushima Prefecture, Japan, from 2019 to 2021. First, we located the hypocenters, removing the effect of uncertainty in the velocity structure of the geothermal fluids. We relocated and clustered the seismic events based on waveform similarity. We analyzed each cluster to define the fracture orientation using principal component analysis (PCA) and focal mechanism (FM) analysis. We used the P polarity with the S/P ratio as a constraint for a better fault-plane solution. With PCA, we can extract the fracture dimension of each cluster. Our cluster analysis showed that the clusters were not always planar fractures, and we interpreted them as fracture zones. Based on the consistency between PCA and FM, each cluster/fracture zone was classified into three conceptual models to characterize the fracture network system in this field. This model showed variations in the orientation of small fractures within the fracture zone. We characterized the spatial variation in fracture distribution and orientations in the reservoir and demonstrated the fracture network system of this field. The fracture zone near the injection well has a N–S strike, and the dip is above 80°; however, the fracture zone in the northeastern part of the injection well has a NW–SE strike with a dip between 60° and 80°. The fracture network system estimated in this study is crucial for robust reservoir modeling because our model is more realistic, observation-orientated, and includes local anomalies of reservoir properties. [ABSTRACT FROM AUTHOR]

In December 2007, an Mw2.2 earthquake occurred in a gabbroic dike at 3.3 km depth in a deep gold mine in South Africa. The fore- and aftershock activity was analyzed in an effort to understand the preparation and generation processes of earthquakes; these findings have already been published. The present paper focuses on the stress state in the source region of the mainshock. A 90-m-long borehole across the mainshock fault was drilled ~ 1.5 years after the mainshock and logged by an optical televiewer. The fault can be identified by severe damage to the borehole wall at the point where the borehole intersected the aftershock cluster. Except for a 10-m section in the hanging wall of the fault, borehole cores were fully recovered. Borehole breakout (BO) and core disking (CD) were found to occur. Two stress measurement techniques [Deformation Rate Analysis (DRA) and Diametrical Core Deformation Analysis (DCDA)] were applied to the borehole cores. By combining their results with occurrence criteria for BO and CD, the principal stress state in the source region of the mainshock was determined. The principal directions in the hanging wall of the fault were nearly identical to the virgin stress state, while it was significantly disturbed in the footwall. The vertical stresses were 106 MPa and 40 MPa in the hanging wall and footwall, respectively. The significant difference in the vertical stress between the two sides of the fault can be explained by the stress redistribution associated with a nonuniform slip on a nonplanar fault. [ABSTRACT FROM AUTHOR]

Topological data analysis is an emerging concept of data analysis for characterizing shapes. A state-of-the-art tool in topological data analysis is persistent homology, which is expected to summarize quantified topological and geometric features. Although persistent homology is useful for revealing the topological and geometric information, it is difficult to interpret the parameters of persistent homology themselves and difficult to directly relate the parameters to physical properties. In this study, we focus on connectivity and apertures of flow channels detected from persistent homology analysis. We propose a method to estimate permeability in fracture networks from parameters of persistent homology. Synthetic 3D fracture network patterns and their direct flow simulations are used for the validation. The results suggest that the persistent homology can estimate fluid flow in fracture network based on the image data. This method can easily derive the flow phenomena based on the information of the structure. [ABSTRACT FROM AUTHOR]