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An interpretation for the gravity anomalies is essential to visualize the horizontal and vertical extension of the subsurface intrusion like mud diapirs resembling dike-like geologic bodies. Therefore, the use of simple-geometrical resembling models helps to validate the subsurface targets. A particle optimization algorithm is one of the recently established metaheuristic algorithms, which is utilized in various geophysical applications and allows discovering and explaining the parameters of the buried geologic targets. Here, we have interpreted gravity response profiles for mud diapir, which close an expected two-dimensional (2D) inclined dikes by calculating the following parameters; amplitude coefficient (A), depths to top (h) and bottom (H), width (2b), inclination angle (θ), origin (d), and length of the body (L) that represents the difference between two depths using the particle optimization algorithm. The stability and efficacy of this study were checked on numerical examples without noise and with numerous levels of random noise (10% and 20%). Also, it tested on a gravity response for mud diapir from the south-western (SW) Taiwan and validated by seismic interpretation. The obtained results declared that the suggested algorithm works well even in the existence of noises. Furthermore, the results of the real case model are found in a respectable agreement with available geological and borehole information and other results from the published literature. • Global optimization algorithm for interpreting a mud diapir of an active gas transmission. • Visualizing the application of the particle optimization algorithm. • This method is successively applied to numerical and real datasets. • This method is powerful and robust. [ABSTRACT FROM AUTHOR]

This study focuses on interpreting gravity anomalies caused by fault structures. The faults types are the two-sided inclined fault, which represents mainly the normal and reverse faults, the two-sided vertical fault, the one-sided inclined fault, and the one-sided vertical fault. The study scheme is depends on the combination between the second moving average operator as a tool for separating the residual (desired) and regional (undesired) anomalies and then detecting the fault parameters applying the global particle swarm. The stability and efficiency of the proposed method has been applied to a synthetic example including the effect of regional background and to five real data sets from Iraq, USA, Egypt, and France. Available geologic and geophysical information supports our interpretation for the field examples from Iraq, USA, and Egypt. While, the forward model results from the detected parameters for the last field example (Pyrenees faults, France) was compared and matched well with measured gravity anomaly and found in a good agreement. So, this interpretation is open a sight-view for researchers around the world work in this area to use our results as a priori information for more investigations. • Global particle swarm optimization for interpreting fault-like geologic structure. • The proposed method is depends on second moving average operator to remove the regional effect. • This method is tested on synthetic and fields data for oil and mineral exploration. • This method is powerful and robust. [ABSTRACT FROM AUTHOR]

A global particle swarm algorithm utilized to assess the inverted two-dimensional horizontal thin sheet parameters from the gravity anomaly profile based on applying the second moving average method. The using of the second moving average method has more advantageous than using the Bouguer gravity anomaly because this method has a capability in eliminating the regional field up to third-order impeded in the Bouguer anomaly. This algorithm is applied to interpret the gravity anomaly profile, i.e., estimating the depth, the width, the thickness, the density contrast and the origin location of the buried structure. The efficacy and stability of this method are investigated and exposed for utilizing free-noise and noisy synthetic examples. Real gravity data associated with oil and gas and mineral exploration from three different locations around the world is interpreted. The evaluated time to discovering this appropriate clarification is very short and the estimated parameters contrast the view that the proposed method is applicable for real exploration. It can extract the inverse parameters which have a geologic and economic significance. • A global particle swarm for interpreting gravity data to delineate the parameters of buried geologic structure • This technique relies on second moving average operator to eliminate the impact of the regional and noise in a main field. • This technique applied to synthetic and field examples for oil and mineral exploration. [ABSTRACT FROM AUTHOR]