1. Leading edge halo (high intensity) standard
On the basis of Au out-of-band anomalies, if as, Sb, Ba, B, (Cd) and Hg are abnormal in the middle and inner band of leading edge halo indicator elements, it indicates that there is blind ore in the deep. When the anomalous intensity of Au is low, the anomalous intensities of As, Sb, Ba, B, (Cd) and Hg are only abnormal in the outer zone, indicating that the blind ore is deep. If the abnormal strength of gold is large, and arsenic, antimony, barium, boron, cadmium and mercury are abnormal in the inner zone, it indicates that the blind ore is shallow.
On the contrary, on the basis of weak gold anomaly, if Mn, Bi, Mo and Co are strong anomalies in the middle and inner zones, while As, Sb, Ba, B and Hg are only sporadic or no anomalies, it indicates that there is no ore in the deep zone.
2. Storage standards before and after halo * * *
Under the condition of weak Au anomaly (outer region), if the leading edge halo characteristic indicator elements As, Sb, Ba, B, (Cd) and Hg are all strong anomalies in the middle and inner regions, and the tail halo indicator elements Mn, Bi, Mo and Co are both strong anomalies in the middle and inner regions (* * *), it indicates that there is a second enrichment zone in the deep. If the characteristics of leading edge halo indicate that elements As, Sb, Ba, B, (CD) and Hg are strongly abnormal in the middle and inner zones, it indicates that there is a second enrichment zone in the deep zone.
3. Leading edge halo intensity trend standard
On the structural superimposed halo profile or vertical projection map, the abnormal intensity of the leading edge halo indicator elements As, Sb, Ba, B, (Cd) and Hg, from strong to weak (outer band) to strong, or the anomaly is always strong, especially in the deepest control tunnel or borehole samples, indicating the existence of blind ore in the deep. If there is a strong anomaly in the lower part or tail of the ore body, it shows that the downward extension of the ore body is still very large.
When studying the abnormal changes of indicator elements, we should pay attention to the criteria of superimposed halo intensity (inner band anomaly), middle band anomaly and weak band anomaly (Table 4–19).
4. Parameter conversion criteria
Geochemical parameters As, Ba, Sb and As+Sb of ore body (halo) are calculated. If they rise from top to bottom, from high to low, and from the deepest part in the middle, it means that there are blind mines in the deep, or the ore bodies extend deeply downward.
5. Anti-zoning standard
When calculating the vertical zoning sequence of ore bodies (halos) in various sections, if there is "anti-zoning", that is, As, Sb, B and Hg appear in the middle and lower parts of zoning sequence, it indicates that there are blind mines in the deep, or the ore bodies extend deeply downward.
(2) Quantitative mathematical model of gold deposit (body) location prediction.
1. Research Status
The study of quantitative mathematical model for location prediction of hydrothermal deposits (bodies) has been a subject of concern and tackling key problems for many scholars at home and abroad for many years. Wu Xisheng of Changchun Institute of Geology and Li Hui of Geophysical Research Institute of Ministry of Metallurgy are the most studied. However, few examples have been successfully used in prospecting, which is still a difficult problem in research.
There are two reasons: first, the research idea is wrong, that is, the axial zoning of primary halo of hydrothermal deposit is studied from the viewpoint of one-time mineralization and halo formation, and the mathematical model is established accordingly, but the actual hydrothermal ore body and its primary halo have the characteristics of multi-stage superposition mineralization and halo formation; Secondly, in the process of mineralization and halo formation of gold ore bodies, the formation of leading edge halo and the distance it extends upward from the head of gold ore bodies along the structural zone are not only related to the pressure gradient of hydrothermal solution and the geochemical properties of different leading edge halo elements, but also controlled by multiple factors such as structural properties such as compressibility, compression and torsion and surrounding rock properties. The attenuation form of element concentration in leading edge halo is very complex, which is difficult to be expressed by a mathematical formula of a straight line-a curve. Only when the ore body formed by one mineralization halo or multiple mineralization halos is in the same position or near the same position, halo-ore body, gold content or some geochemical parameters from the front may increase according to a certain curve. Under this condition, regression or other mathematical models can be established to predict blind ore or judge the degree of erosion of ore bodies.
During the period of 1990, we studied the rock geochemical expert prediction series of Jiaodong gold deposit and the mathematical model of gold deposit location prediction. The first step is to identify the gold-bearing property (whether it contains gold or not) of structural belts and chronological veins → the second step is to identify the gold belt to which the gold-bearing body belongs → the third step is to identify the gold mineralization type (chronological vein type? Or altered rock type? The fourth step is to judge the degree of erosion and predict the blind ore. What is the key to blind mine? Although the model realized man-machine dialogue, it initiated a new stage of further quantitative positioning and prediction research by primary halo method, and won the second prize of scientific and technological progress of Ministry of Metallurgy. However, the expert forecasting system is difficult to popularize and apply.
Although the structural superposition halo of similar ore deposits or gold deposits in the same ore belt is very * * *, different ore deposits have their own characteristics. In which mining areas blind ore prediction must be made, it is necessary to establish this deposit model, and use this deposit model and standard to make deep prediction, so as to achieve good prospecting results.
In recent 12 years, China Gold Association organized experts to appraise 12 times the "Deep Blind Ore Prediction Model of Structural Superimposed Halo" of 12 Mine, and the conclusion is that structural superimposed halo has reached the international leading level in blind ore prospecting. But experts always suggest to study the quantitative mathematical model of hydrothermal deposit (body) location prediction. Despite years of efforts, there are no successful examples.
2. Study on the mathematical model of gold deposit (body) location prediction in Qinling Mountains.
The mineralization and halo formation of Qinling gold mine is characterized by multi-stage and multi-stage superposition, and the existence of front tail halo and the turning point of geochemical parameters often appear in the superimposed halo. The author tried to establish a mathematical model to quantitatively predict the deep blind ore and identify the position or erosion degree of the ore body (the head, middle and tail of the ore body), but it was very difficult. This paper only introduces the geochemical parameter index method of location prediction for reference and regression analysis mathematical model research.
(1) geochemical parameter index method: according to the axial variation law of geochemical parameters of deposit-ore body-halo at different elevations, determine the geochemical parameter index that distinguishes the front-head-middle-bottom-tail of ore body.
① Geochemical parameter index: According to the element content of different elevations in Table 4-20, the geochemical parameter index for predicting the degree of ore body erosion is established (Table 4-2 1).
Table 4-2 1 index method of geochemical parameters for orebody prediction of No.60 vein in Yangzhaiyu Gold Mine
② Application method: calculate the average value of the parameters corresponding to the predicted target position of the superimposed halo of the evaluated structure, and then compare with the indexes in the above table, assign values, calculate the assigned average value, and compare with the prediction standard to get the prediction results: pre-mine, mine head, middle section or mine tail.
(2) Regression analysis model for predicting different parts of ore body: The regression analysis model is established based on the axial (vertical) geochemical parameters of No.3 ore body in No.60 vein halo at different elevations (from 1996 to 1794m-200m vertical depth and 283m oblique length) (Table 4-20), and Y is the basic data. The correlation coefficient and regression coefficient of X 1 = Ba, X2 = Pb+Zn and X3 = Co+Ni at different elevations along the ore body axis are calculated respectively, and the y value is1→ 0.8 → 0.6 → 0.4 → 0.2 → 0.1.
Regression analysis model for predicting different parts of ore body: yi = a+bxii is 1, 2,3.
①y 1 = 0.259+0.00 1×(Ba)。
The correlation coefficient between Ba value and Y value of ore bodies with different elevations is r = 0.895.
②y2 = 1.4 1-0.008×(p b+ Zn)。
The correlation coefficient of (Pb+Zn) and Y value assigned by different elevations of ore body is r = 0.9 1.
③y3= 1.49-0.0048×(Co+Ni)。
The correlation coefficient between (Co+Ni) and Y value assigned by different elevations of ore bodies is r = 0.895.
(3) Application method: Calculate the average values of the estimated corresponding parameters in the forecast target of tectonic superimposed halo: x = Ba, x = Pb+Zn, x = Co+Ni, and substitute them into the above three regression equations to get y 1, y2, y3, and then calculate y = (y1+y2+y3). .
The average value of y is about 1, which is the front and head of the mine;
The average value of y is about 0.5, which is medium in mines;
The average value of y ≈0. 1 is about the mine tail.