Identification of New Hydrocarbon Prospect Area Using Multi-Attribute Analysis of Hydrocarbon Microtremor Data

A growing number of low-frequency passive seismic surveys over proven oil and gas fields throughout the world have shown the presence of anomaly spectra (between 2–4 Hz). These signals are known as hydrocarbon microtremors, and the HyMAS (Hydrocarbon Microtremor Analysis) method has been widely used and developed by Spectraseis as a complement method for direct hydrocarbon indicators (DHI). This method, which is completely passive and does not require seismic artificial excitation sources, is useful for optimizing well placement during exploration, appraisal, and development for the oil and gas fields. We conducted several signal attributes provided for low-frequency passive seismic data that resulted in a better correlation between the presence of hydrocarbons in the subsurface and the observed spectral anomalies. In this study, we measured the attributes for 121 stations with two proven hydrocarbon production stations among them. We mapped each attribute value and interpreted the results based on spectral and polarization attributes from the proven hydrocarbon production stations. We also included the analysis of noise identification from the investigation site. Using the results, we combined each mapped attribute and made a spatial scoring map that provided the consistency level of each attribute for the DHI. This map provides a quick look to find an area of interest for further exploration which could be used for new optimized well placement during exploration.