Mine seismic prediction of tectonic faults by reflected waves using the method of location

The article presents the case-study of geological anomaly delineation by reflected waves in seismic logs of the common excitation point and the common receipt point using a dedicated software. The proposed data processing flow consists in consistent fulfillment of a sequence of stages. Sorting of seismic logs is followed by band and band-elimination filtering, selection of optimal filter passband and identification of interfering axes of phase synchronization of different-nature waves. The axes of phase synchronization of information-bearing waves are identified by the points of the first arrivals. By these points, ellipses are automatically drawn so that their focuses are at the excitation and receipt points while the value of doubled semi-axes is equal to the product of velocity and first arrival time of a wave. The criterion of reflecting boundaries is the distinctive approach or intersection of the ellipses in a local zone of a supposed reflecting boundary. The data processing algorithm allows revealing tectonic faults within a radius to 200 m around a roadhead. Reflecting boundaries at greater distances from roadheads are located on an estimation basis. The developed algorithm and software can be used by geophysical services and specialized geological exploration agencies for processing and analysis of seismic survey data when predicting structure of coal-and-rock masses.

Remote Monitoring System of Geological Exploration in Lava Area Based on GPS

A remote monitoring system for geological exploration in a lava area based on GPS is designed. The system mainly collects geological exploration data in a lava area by means of multi-S integration through the data acquisition module of geological exploration in a lava area. Then the data collected are transmitted to the data analysis and management module of geological exploration data in a lava area by using a GPS network, and the data analysis and management module of geological exploration data in the lava area is exploited. The monitoring data processing method based on the unascertained filtering method is used to remove gross errors in geological exploration data of lava area, identify abnormal values in geological exploration data of lava area, and transmit the abnormal values to the GPS-based geological anomaly location module. The GPS-based geological anomaly location module locates the geological anomaly according to the abnormal values, thus completing the remote monitoring of the exploration of the lava area based on GPS. The test results show that when the system is applied to remote monitoring of geological exploration in a lava area, the positioning error of small soil caves is small, and the reliability of monitoring data is high, which meets the needs of remote monitoring of geological exploration in a lava area.

Advanced detection and analysis of inclined shaft passing through aquifer in the mine of western China

The thick sandstone aquifer of the Cretaceous Yijun formation is rich in water and poor in predictability. Under this circumstance, the issue of the main inclined shaft of the mine in western China has been studied. Then, the comprehensive geophysical method is used in the field for advanced exploration and prediction. Based on the mine transient electromagnetic method and direct current resistivity method, the comprehensive advanced detection is carried out. Furthermore, the low resistance area in front is determined, the geological anomaly position and characteristics in front of the head are judged, and the water rich area of the detection is qualitatively evaluated, which provides support for the formulation of production technology scheme. The driving construction verification shows that the result of comprehensive geophysical exploration is basically consistent with the actual one of the shaft, and the detection accuracy of the relatively rich water area reaches over 80% which demonstrates that the comprehensive geophysical exploration method can be effectively applied into the construction of inclined shaft driving.

Using EVT for Geological Anomaly Design and Its Application in Identifying Anomalies in Mining Areas

A geological anomaly is the basis of mineral deposit prediction. Through the study of the knowledge and characteristics of geological anomalies, the category of extreme value theory (EVT) to which a geological anomaly belongs can be determined. Associating the principle of the EVT and ensuring the methods of the shape parameter and scale parameter for the generalized Pareto distribution (GPD), the methods to select the threshold of the GPD can be studied. This paper designs a new algorithm called the EVT model of geological anomaly. These study data on Cu and Au originate from 26 exploration lines of the Jiguanzui Cu-Au mining area in Hubei, China. The proposed EVT model of the geological anomaly is applied to identify anomalies in the Jiguanzui Cu-Au mining area. The results show that the model can effectively identify the geological anomaly region of Cu and Au. The anomaly region of Cu and Au is consistent with the range of ore bodies of actual engineering exploration. Therefore, the EVT model of the geological anomaly can effectively identify anomalies, and it has a high indicating function with respect to ore prospecting.

The Calculation of Fractal Model’s Non-Scale Range

Application of fractal method to establish geological data fractal model is an important way to identify geological anomaly. Using derivative identification method, it can divide the fractal model’s non-scale range respectively. It determines the abnormal areas according to the abnormal lower limit value. In this paper, the geological data of Au element is calculated by "C-A" fractal model in Mohe Heilongjiang province. On the same non-scale range the double logarithmic fitting curve has the similar local slope and the second-order derivative of this curve within the same non-scale range could be slightly fluctuate near zero. Using the threshold , the non-scale ranges can be identified by this method. The abnormal lower limit value identified by this method is lesser than the artificial recognition method. On the Matlab software platform to calculate Au abnormal areas’ dimension value is 2.65, and the element abnormal lower limit value is 2.9. The abnormal areas delineated by this abnormal lower limit value contain all the gold ore sites we have known.