Abstract
The Manta-Ray Foraging Optimization has been adapted and implemented in computing model parameters from potential field anomalies originating from two-dimensional dipping faults. The inversion technique was originally demonstrated on magnetic anomalies from uncorrupted-then, corrupted synthetic datasets. Thereafter, it was experimented on profiles taken from mining fields in the United States, and Australia. The results obtained showed that the design procedure is admirably stable and flexible, especially when dealing with noisy data. It is also notably efficient in the quantitative resolution of geophysical inverse problems. The consistency in results obtained from analysis of deep-seated and shallow field examples, even when compared against background results, is also impressive. The new technique has also exhibited notable superiorities over other well-known and conventional techniques, especially on the grounds of convergence rate, cost, and quality of resolved anomaly parameters. Consequently, it is recommended for interpretation of other structures and modeling of other geophysical data like self-potential and resistivity data.