1994 Fiscal Year Final Research Report Summary
Fractal Analysis of Fracture in Rocks and its Application to Evaluate of Geothermal Reservoir.
| Project/Area Number |
04452263
|
|---|
| Research Category |
Grant-in-Aid for General Scientific Research (B)
|
| Allocation Type | Single-year Grants |
|---|
| Research Field |
資源開発工学
|
|---|
| Research Institution | TOHOKU UNIVERSITY |
|---|
Principal Investigator |
NAKATSUKA Katsuto Tohoku University, Dept.Resources Engineering, Professor, 工学部, 教授 (60005345)
|
|---|
| Co-Investigator(Kenkyū-buntansha) |
TSUCHIYA Noriyoshi Tohoku University, Dept.Resources Engineering, Research Assistant, 工学部, 助手 (40207410)
|
|---|
| Project Period (FY) |
1992 – 1994
|
| Keywords | FRACTAL / FRACTURE IN ROCKS / STATISTICAL SELF-SIMILARITY / FRACTURE MODEL / GEOTHERMAL RESERVOIR / CLASTER / SPACE FILLING / FRACTURE SHAPE |
|---|
| Research Abstract |
Space filling of natural fracture patterns in sections of the Tamagawa Welded Tuffs shows a statistical self-similarity, and its fractal dimension determined by a box-counting algorithm lied in the range from 1.08 to 1.48. Mean values of fractal dimension in various scales of fracture pattern of the Tamagawa Welded Tuffs were approximately equal. These facts suggest that the fractal dimension of space filling of the zoom sequences had an unique fractal property and the value of the fractal dimension was about 1.28.
Fracture shape in the section which is sliced in random orientation also showed fractal property, and its fractal dimension was in the range between 1.01 and 1.05. The fractal observed in space filling and shape on natural rock suggests that the characteristic fractal dimensions could be estimated by fracture pattern of other scales.
Fractal dimensions of fracture patterns in natural rock sections were determined using box-counting method and geometrical feactures, including l
… More
ength distribution, orientation, connectivity, number of fractures and total length, were formulated to construct fractal fracture network model.
Fracture network was divided into clusters by connectivity. The fractal dimension and visual impression of fracture network was influenced very much by the maximum cluster. Here, the maximum cluster is defined as the cluster with the maximum number of fractures. The number of fractures in the maximum cluster was proportional to fractal dimension, furthermore, connectivity, number and total length of fractures correlated to fractal dimension. The range of selected parameters (such as number of fractures in the maximum cluster, connectivity, number of fractures and total length of fractures in fracture network) could be determined by the relationship thus obtained.
The shape of fractures was first determined and then the maximum cluster, other clusters and single fracture were generated in the above sequence, and are based on input fractal dimension and inter relations among parameters. Computer-generated two-dimensional fracture network patterns and fractal properties were very similar to that of the natural fracture patterns in rock sections. It was confirmed by the box-counting analysis that the same fractal dimension of the obtained model fracture patterns coincided with that of input data. Less
|
