Modeling of Hijiori HDR Reservoir by Using Deterministic and Stochastic Fracture Information

New Concept Fracture Network Simulator [D/SC]

Abstract

D/SC (Deterministic and Stochastic Crack network simulator) has been developed with an objective to make reliable fracture network models by integrating various kinds of fracture information such as core analysis, borehole measurements, microseismic observations and geological surveys. The basic concept of D/SC is to put fractures into the model directly if their features have been determined and to interpolate the space in between by stochastic fractures, which follow the statistical properties of the reservoir. The model with a number of discrete fractures is then converted to a continuum model whose elements have equivalent permeability to the discrete fracture network. Finally, the pressure, flow vector and temperature at every element is calculated. The advantage of this approach is that the various kinds of data obtained from the reservoir can be utilized in describing the characteristics of the reservoir and that the created model can be used for predictions not only for reservoir performances in time but also for special potentials for new production wells. This paper describes a procedure of creating a fracture network model by applying D/SC to the Hijiori Hot Dry Rock reservoir. The Hijiori fracture model created includes several deterministic fractures, which are inferred from PTS logging data and BHTV images, in filling stochastic fractures, that follow statistical information derived from core analysis and BHTV images, and two permeable faults that represent both the caldera faults and the boundary of the microseismic distribution. The simulated thermal performance shows a significant difference in temperature draw down of production fluid from the two production wells (HDR-2a and HDR-3). The model was also used for the evaluation of pseudo-new wells in the Hijiori site. The results provided us with a guideline of preferable locations for an additional well.