Application of multivariate regression on magnetic data to determine further drilling site for iron exploration

Abstract

In this study, a new approach of the multivariate regression model has been applied to make a precise mathematical model to determine further drilling for the detailed iron exploration in the Koohbaba area, Northwest of Iran. Furthermore, to figure out the additional drilling locations, the ore length to the total core ratio for the drilled boreholes has been used based on the geophysical exploration dataset. Hence, different regression analyses including linear, cubic, and quadratic models have been applied. In this study, the ore length to the total core ratio of the chosen drilled boreholes has been considered as a dependent variable; besides, the outputs of the magnetic data using the UP10 (10m upward-continuation), RTP (reduction to the pole), and A.S. (analytic signal) techniques have been designated as independent variables. Based on probability value (p-value), coefficients of determination (R 2 and R adj 2 {R}_{\text{adj}}^{2} ), and efficiency formula (EF), the fourth regression model has revealed the best results. The accuracy of the model has been confirmed by the defined ratio of boreholes and demonstrated by four additional drilled boreholes in the study area. Therefore, the results of the regression analysis are reasonable and can be used to determine the additional drilling for the detailed exploration.

A Multi-Objective Approach for Optimizing the Layout of Additional Boreholes in Mineral Exploration

“…In particular, lithological, structural, alteration and topographical maps, hyperspectral imaging, as well as ground or airborne magnetic, electrical, gravimetric, and seismic surveys, are often used for mineral potential mapping and are therefore good candidates for the definition of a 'geological potential' parameter relevant to the definition of exploratory boreholes (in addition to KSD, CM, OV, and MC). The reader is referred to [73][74][75][76][77][78] for applications of geophysical surveys to the exploration of volcanogenic massive sulfide, iron oxide copper gold, and porphyry ore deposits and to the sampling design problem.…”

Design of A Three-axis Helmholtz Coil for Magnetic Sensor Calibration

“…In recent years, magnetic exploration technology has been widely used in geological exploration [1][2], medical diagnosis [3], military aviation [4][5] and other fields. The development of magnetic exploration technology has evolved from single total field measurement, single gradient field measurement, magnetic vector field measurement, to the current magnetic gradient tensor field measurement, and its development trend has been transformed from magnetic field scalar detection to the measurement of the three components of the magnetic field.…”

A Framework for Analyzing Individual-Tree and Whole-Stand Growth by Fusing Multilevel Data: Stochastic Differential Equation and Copula Network

“…Bivariate analysis investigates the relationship between a paired dataset of an individual tree or stand variable measurements, for example, the height-diameter relationships [11,12], the height and basal area models [13,14], and others [15,16]. Linear multivariate analysis uses two or more tree or stand variables and analyzes which, if any, are correlated with a specific predictor variable [17,18]. The goal of multivariate analysis is to determine which tree or stand size variables significantly influence or cause a causal relationship with the predictor variable [19][20][21][22].…”