Fault parameters assessment from the gravity data profiles applying the global particle swarm optimization

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.

Automated summary

This study focuses on interpreting gravity anomalies caused by fault structures using the second moving average operator and global particle swarm to detect fault parameters. The proposed method was successfully applied to synthetic and real datasets from Iraq, USA, Egypt, and France, with geological and geophysical information supporting field examples from Iraq, USA, and Egypt. The forward model results for the Pyrenees faults in France showed good agreement with measured gravity anomalies, opening up possibilities for researchers worldwide to use the results as a priori information for further investigations.