Fracture Network Characterization Using Stress‐Based Tomography

Abstract

Information on structural features of a fracture network at early stages of Enhanced Geothermal System development is mostly restricted to borehole images and, if available, outcrop data. However, using this information to image discontinuities in deep reservoirs is difficult. Wellbore failure data provides only some information on components of the in situ stress state and its heterogeneity. Our working hypothesis is that slip on natural fractures primarily controls these stress heterogeneities. Based on this, we introduce stress‐based tomography in a Bayesian framework to characterize the fracture network and its heterogeneity in potential Enhanced Geothermal System reservoirs. In this procedure, first a random initial discrete fracture network (DFN) realization is generated based on prior information about the network. The observations needed to calibrate the DFN are based on local variations of the orientation and magnitude of at least one principal stress component along boreholes. A Markov Chain Monte Carlo sequence is employed to update the DFN iteratively by a fracture translation within the domain. The Markov sequence compares the simulated stress profile with the observed stress profiles in the borehole, evaluates each iteration with Metropolis‐Hastings acceptance criteria, and stores acceptable DFN realizations in an ensemble. Finally, this obtained ensemble is used to visualize the potential occurrence of fractures in a probability map, indicating possible fracture locations and lengths. We test this methodology to reconstruct simple synthetic and more complex outcrop‐based fracture networks and successfully image the significant fractures in the domain.

Comparison of Hydraulic and Tracer Tomography for Discrete Fracture Network Inversion

“…Fractures at the sides of the model (connecting the sources and receivers with the DFN) are fixed, thus they appear with 100% probability. This assumption is acceptable since it is possible to detect the fracture location and orientation in boreholes based on core and image logs (e.g., optical or acoustical televiewer) (see [45,57]). A similar procedure is employed by Fearnhead [52] and Punskaya et al [53] to analyze a speech signal in order to obtain the real speech data without noise.…”

“…The intersection between two or more fractures is considered by mass conservation. These equations are numerically solved by a finite difference approach with first-order accuracy in time and second-order accuracy in space [44,45]. We use an implicit time integration method, which is unconditionally stable.…”

From Fluid Flow to Coupled Processes in Fractured Rock: Recent Advances and New Frontiers

“…Recently, Afshari Moein et al. (2018) developed a stress‐based tomography approach that combines geomechanical modeling of quasi‐static stress variations caused by fractures with an inversion algorithm to reconstruct probable DFN geometries from stress variability profiles obtained from borehole logs. In addition, progress has been made on inversion methods, mainly through the combined inversion of different borehole log data sets (Tian et al., 2021) or by using some borehole data sets to better constrain the inversion of other types of cross‐borehole data sets (Wu et al., 2019).…”

Study on Fracture Characteristics and Controlling Factors of Tight Sandstone Reservoir: A Case Study on the Huagang Formation in the Xihu Depression, East China Sea Shelf Basin, China

“…In reservoirs having low host-rock permeability-dense, natural fractures are one of the key factors that improve reservoir physical properties and increase productivity, as well as the important factors restricting the fracturing effect [3][4][5]. Although scholars have conducted extensive research on fractures [6,7], understanding the origin and attributes of subsurface fractures is still a worldwide concern. One of the main reasons why fracture research has encountered such a bottleneck is that the types of fractures are complex.…”