Comparison of three one-dimensional time-domain electromagnetic forward algorithms

Accurate, efficient, and accessible forward modeling of geophysical processes is essential for understanding them and for inversion of geophysical data. Various algorithms are available for predicting data with the time domain electromagnetic method (TDEM). These algorithms differ in their approach and implementation, making some more suitable than others for specific applications. In this study, we compare three different algorithms for calculating the solution to the 1D forward response problem in TDEM, provided by Geoscience Australia, AarhusInv and SimPEG. Our comparison focuses on four main aspects: efficiency, accuracy, generality and convenience. Efficiency is evaluated from the perspective of computational speed. Accuracy is evaluated in two steps. First, we analyse the relative modeling error of each algorithm’s forward calculation for conductive half-space models, compared to an analytic solution. Secondly, we evaluate the accuracy of the algorithms relative to each other in the context of more complex earth models where no analytic solutions exist. This evaluation assumes a realistic TDEM instrument. Generality is the ability to model a variety of real TDEM scenarios. Lastly, we assess the convenience of each algorithm by considering factors such as ease of use, extensibility, code accessibility, and licensing requirements. We find that no single tested forward algorithm is best for all cases. AarhusInv is accurate and fast while it also has the most options for modeling real TDEM systems, but it requires a license, and is the hardest forward algorithm to interface to. SimPEG is open source, fast, easy to install and results may easily be shared, but has accuracy limitations at early times when modeling real systems with gate integration and low-pass filters. Lastly, Geoscience Australia is open source, accurate, and fast, but can only model dipole sources. • Time domain electromagnetic data. • Comparison of Forward Algorithms. • Modeling errors. • Timing of Forward Responses. • modeling capabilities. • Choosing a Forward Algorithm.