Abstract:
We discuss the problem of proper use of software packages that implement methods for solving ill-posed problems. Most of the problems of processing experimental data belong to ill-posed problems. When using methods for solving ill-posed problems, there is a problem of non-uniqueness of the solution, which is solved by introducing a priori information. Obtaining a priori information is possible in different ways, but quantitative estimates involve the use of additional methods for data analysis. Obviously, additional methods should not be more complicated and labor intensive than the main data processing method. Using the RES3DINV electrical prospecting data analysis software as an example, the role of a priori information for obtaining reliable results is demonstrated. The RES3DINV software is used to build a soil model from the measured values of resistivity using electrical survey’s methods. When using the inversion method implemented in the software package, it is necessary to set the input parameters describing the geometric dimensions of the anomalous resistance object, which are usually unknown a priori. By model objects we demonstrate how the incorrect setting of input parameters affects the result of data interpretation. We show that the vector analysis method can be used as a way to obtain a priori information. This method allows us to obtain estimates of the geometric parameters of an anomalous object, does not involve high time and resource expenses, and can be used directly at the site of field experimental measurements.
Keywords:ill-posed problems, data interpretation, a priori information, geometric parameters, vector analysis.