Standard, Random and Optimum Array Conversions from Two-pole Resistance Data

Abstract

We present an array evaluation of standard and non-standard arrays over a hydrogeological target. We develop the arrays by linearly combining data from the pole-pole (or 2-pole) array. The first test shows that reconstructed resistances for the standard Schlumberger and dipole-dipole arrays are equivalent or superior to the measured arrays in terms of noise, especially at large geometric factors. The inverse models for the standard arrays also confirm what others have presented in terms of target resolvability, namely the dipole-dipole array has the highest resolution. In the second test, we reconstruct random electrode combinations from the 2-pole data segregated into inner, outer, and overlapping dipoles. The resistance data and inverse models from these randomized arrays show those with inner dipoles to be superior in terms of noise and resolution, and that overlapping dipoles can cause model instability and low resolution. Finally, we use the 2-pole data to create an optimized array that maximizes the model resolution matrix for a given electrode geometry. The optimized array produces the highest resolution and target detail. Thus, the tests demonstrate that high quality data and high model resolution can be achieved by acquiring field data from the pole-pole array.