Fracture Network Characterization Research Articles

Hydraulic characterization and upscaling of fracture networks based on multiple‐scale well test data

Hydraulic properties and upscaling characteristics of low‐permeability fractured rock are analyzed based on systematic well test data from three different measurement scales. First, tests are simulated in a large number of geological fracture network realizations, and the acceptable fracture transmissivity distribution parameters that produce the observed statistics of the two smallest measurement scales, i.e., 2‐m and 10‐m scales, are defined. Instead of a single value, a range of acceptable parameter values can be found to produce the observed result. Second, upscaling simulations are carried out with the calibrated networks. These indicate that the investigated system cannot be properly modeled by means of a continuum tensor presentation but would better be represented by means of “equivalent fracture” statistics. Third, the conductive characteristics of the calibrated 30‐m network blocks are compared to well test results from the same scale. The results from this preliminary analysis indicate that one‐dimensional borehole observations interpreted with standard continuum‐based methods may considerably underestimate the three‐dimensional conductive characteristics of heterogeneous, noncontinuum fractured media.

A three‐dimensional stochastic rock mechanics model of engineered geothermal systems in fractured crystalline rock

A three‐dimensional (3‐D) stochastic network model for simulating a hot dry rock (HDR) or hot wet rock (HWR) engineered geothermal system formed in fractured crystalline rock is presented. The model addresses the problems of fracture network characterization from in situ field data, such as fracture orientation, size, spacing, and other mechanical properties. The model can simulate the changes that occur within the rock mass during stimulation (i.e., large volume fluid injection at pressures sufficient to allow shear slip on natural fractures). It can also be used to simulate steady state circulation of the heat exchange system thus created and includes provision for predicting tracer response curves and heat extraction history. The model has been applied to data gathered during the stimulation and circulation of a 2.2‐km‐deep HDR reservoir at Hijiori, Japan. The predicted shape of the stimulated and shear‐propped fractures closely matched the distribution of seismic source distribution of acoustic emission (AE), regardless of realization of the fracture network, suggesting that the geometry of the stimulated volume can be robustly predicted from knowledge of the fracture population and in situ stresses. However, hydraulic behavior and tracer tests during the circulation could only be satisfactorily simultaneously reproduced by a small subset of realizations. These selected realizations, obtained by matching initial circulation and tracer data, are considered to give the best prospect of satisfactory long‐term thermal modeling. The success in simultaneously modeling diverse data (hydraulic, microseismic, and tracer) lends confidence to the thermal predictions. The results indicate that a large improvement in the long‐term thermal performance of the Hijiori reservoir could result from increasing well spacing from 100 to 150 m without major degradation of the hydraulic performance.

Fractal geometry characterization of geothermal reservoir fracture networks

As a new procedure for modeling geothermal energy extraction systems, a two‐dimensional modeling technique for subsurface fracture networks on the basis of “fractal geometry” is presented. Models of fracture networks are generated by distributing fractures randomly in space and by using the fractal relation between fracture length r and the number of fractures N expressed with a fractal dimension D as N = Cr−D, where C is a constant that signifies the fracture density within the rock mass. This procedure makes it possible to characterize geothermal reservoirs by parameters measured from field data, such as from core sampling. In this characterization the fracture density parameter C of a geothermal reservoir is used as a parameter to model the subsurface fracture network. Using this fracture network model, the connectivities of the water flow paths between wells are calculated by means of a Monte Carlo simulation, and the result is then compared with that derived from a percolation model. We show that many fewer fractures are required to connect two wells for the fracture network model than for the percolation model. The transmissivities between wells for the fracture network model are also obtained as a function of the fracture density parameter C. The results show that the transmissivities in geothermal reservoirs are significantly dependent upon the fracture density of rock mass, and they can be predicted from the fracture density parameter C of the reservoirs.

3D Characterization of Fracture Networks in Chalk Using Electrical Borehole Images, Danish Central Graben, North Sea: ABSTRACT

3D Characterization of Fracture Networks in Chalk Using Electrical Borehole Images, Danish Central Graben, North Sea: ABSTRACT

Fractal Characterization of a Fractured Chalk Reservoir--The Laegerdorf Case

What is the matrix block size distribution of a fractured reservoir In order to answer this question and assess the potential of fractal geometry as a method of characterization of fracture networks, a pilot study has been done of the fractured chalk quarry in Laegerdorf. The fractures seen on the quarry walls were traced in the field for a total area of {approximately}200 {times} 45 m. The digitized pictures have been analyzed by a standard box-counting method. This analysis gave a fractal dimension of similarity varying from 1.33 for fractured areas between faults, to 1.43 for the fault zone, and 1.53 for the highly deformed fault gouge. The amplitude showed a similar trend. The fractal dimension for the whole system of fractures is {approximately}1.55. In other words, fracture networks in chalk have a nonlinear, fractal geometry, and so matrix block size is a scaling property of chalk reservoirs. In terms of rock mechanics, the authors interpret the variation of the fractal dimension as follows: A small fractal dimension and amplitude are associated with brittle deformation in the elastic regime, while a large fractal dimension and amplitude are associated with predominantly ductile, strain softening deformation in the plastic regime. The interactionmore » between the two regimes of deformation in the rock body is a key element of successful characterization and may be approached by seeing the rock as a non-Newtonian viscoelastic medium. The fractal dimension for the whole is close to a material independent limit that constrains the development of fractures.« less