Step 1: Understanding apparent resistivity in a double-dipole system.
In a double-dipole system, apparent resistivity is calculated using the voltage measured between the potential electrodes, the current injected, and the geometric factor (dependent on electrode spacing and array configuration). The formula is: \[ \rho_a = K \cdot \frac{V}{I} \] where \(K\) is the geometric factor, \(V\) is the measured potential difference, and \(I\) is the injected current.
Step 2: Analyzing each factor:
(A) Electrode spacing affects the geometric factor \(K\), so it affects apparent resistivity.
(B) The true subsurface resistivity influences the voltage measured, affecting apparent resistivity.
(C) The distance between the dipole centers changes the sensitivity and geometry of the measurement, affecting \(K\).
(D) Telluric currents are naturally occurring geoelectric currents in the Earth, but in controlled source resistivity measurements, their influence is negligible or eliminated through signal processing.
Hence, the apparent resistivity is not affected by the telluric current.
Suppose a mountain at location A is in isostatic equilibrium with a column at location B, which is at sea-level, as shown in the figure. The height of the mountain is 4 km and the thickness of the crust at B is 1 km. Given that the densities of crust and mantle are 2700 kg/m\(^3\) and 3300 kg/m\(^3\), respectively, the thickness of the mountain root (r1) is km. (Answer in integer)
For a half space composed of 3 layers with resistivities \( \rho_1 \), \( \rho_2 \) and \( \rho_3 \), as shown in the figure, which of the following statements is/are correct about the variation of apparent resistivity with electrode spacing?
A color model is shown in the figure with color codes: Yellow (Y), Magenta (M), Cyan (Cy), Red (R), Blue (Bl), Green (G), and Black (K). Which one of the following options displays the color codes that are consistent with the color model?
While doing Bayesian inference, consider estimating the posterior distribution of the model parameter (m), given data (d). Assume that Prior and Likelihood are proportional to Gaussian functions given by \[ {Prior} \propto \exp(-0.5(m - 1)^2) \] \[ {Likelihood} \propto \exp(-0.5(m - 3)^2) \]
The mean of the posterior distribution is (Answer in integer)