Prediction method for three-dimensional statistical distribution of rock fracture network occurrence

Abstract

The invention provides a prediction method for three-dimensional statistical distribution of rock fracture network occurrence. The method comprises the steps that a measuring line for observing rock in the field is arranged, fractures intersecting with the measuring line are collected, inclining directions, inclining angles and sizes of the fractures are measured, a mean value of the sizes of the fractures is calculated, and the number of samples of the inclining directions and the inclining angles is counted; the pitch direction, pitch angle and width of the measuring line are measured; whether the inclining directions and the inclining angles of the fractures are randomly distributed in probability space is judged; whether the order of magnitudes of the width of the measuring line is smaller than the order of magnitudes of the mean value of the sizes of the fractures is judged; the inclining directions and the inclining angles of the fractures are converted into polar points through stereographic projection, and observation frequency of all the polar points is acquired; sine values of intersection angles are calculated; a deviation compensation coefficient of the observation frequency of the polar points is calculated; and initial prediction frequency of the polar points is calculated, and prediction frequency of the polar points is obtained through a round-off integer method according to the initial prediction frequency. Through the method, three-dimensional statistical distribution of fracture occurrence can be accurately predicted.

Description

technical field [0001] The invention relates to the technical fields of rock mechanics and geology, in particular to a method for predicting the three-dimensional statistical distribution of rock fracture network occurrences. Background technique [0002] Rock fractures include joint planes, bedding planes, and other significant fracture planes with negligible tensile strength. It is a kind of medium interface commonly found in the crust. It is a network composed of various fracture units, especially the geometric properties of the network. Controlling the kinematics, mechanics, and hydraulic behavior of rock media, the geometric properties of fracture networks can be quantitatively described by the statistical distribution of a set of three-dimensional physical quantities such as size, position, and occurrence. [0003] Surveying line technology is a commonly used technique for field observation of geometric properties. This technology only collects fractures that intersect...

AI Technical Summary

Problems solved by technology

[0004] (1) These prediction methods require other investigation information such as the measurement of permeability coefficient, which increases the workload of actual measurement, and some parameters need to be set during the prediction process. The prediction results may be sensitive to these additional investigation information and settings, resulting in inaccurate prediction results. Certainty and Inaccuracy

[0005] (2) One or more theoretical occurrence distribution types must be defined, but they may not conform to the real three-dimensional distribution, and at the same time, there is no practical method to identify the optimal distribution type

[0006] (3) Some samples do not conform to the theoretical distribution in nature, so it seems unreasonable to impose a definition of the theoretical distribution type

But at the same time, it has some deficiencies. For example, it does not completely eliminate observation errors. For approximately parallel fractures such as bedding surfaces, the gap between the predicted results and the three-dimensional real distribution is small, and it can reflect the three-dimensional statistical distribution. However, for non-parallel situations such as joint surfaces , the residual error after prediction is relatively obvious, and there is still a certain gap between the prediction results and the three-dimensional real distribution, which cannot effectively represent the three-dimensional statistical distribution

Images