Inversion of 1-D Resistivity Data using RR-PSO algorithm to identify Shallow Gas in Balikpapan

Abstract

In recent years shallow gas blowouts have occurred several times in Balikpapan residential areas due to drilling activities for groundwater exploration and geological structures that play as a gas trap. It is necessary to identify structures containing shallow gas by implementing geophysical methods namely Vertical Electrical Sounding (VES). VES is an electrical resistivity method which involves the rapid measurement of variations of the ground resistivity with increasing electrode spaces. The output of this method is a 1-D resistivity model used to identify shallow gas. The 1-D resistivity model can be obtained by the inversion technique. In general, the inversion of VES data is conducted using local optimization method. However, this method has several limitations hence we need to implement a global optimization method in VES data inversion. In this work, the RRPSO algorithm was implemented, which is a global optimization method, in VES data inversion to obtain 1-D resistivity model. First, the RR-PSO algorithm is built and tested to invert synthetic data to evaluate the algorithm's performance. In this stage, the similarity index and several statistical parameters of the inversion results were calculated. After the synthetic test, the algorithm is implemented on field data inversion. The result shows that the RR-PSO algorithm has successfully inverted both the synthetic and field data. In the synthetic test, the similarity index obtained is more than 95%. The 1-D resistivity model from field data inversion indicates at the depth of 20 – 55 m a high resistivity anomaly that is identified as shallow gas. For further study, the RR-PSO algorithm could be implemented for other VES data to construct 2-D resistivity model in the study area (Palm Hills Resident area, south Balikpapan) for imaging the shallow gas presence as a mitigation measure.