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.
The Groningen gas field in the Netherlands is an ideal test bed for in-situ reservoir monitoring techniques because of the availability of both active and passive in-reservoir seismic data. In this study, we use deconvolution interferometry to estimate the reflection and transmission response using active and passive borehole data within the reservoir at ∼3-km depth and separate up- and downgoing P- and S-wave fields by f-k filtering. We validate the results using synthetic data of a 1D elastic model built from sonic logs recorded in the well. The estimated full-waveform reflection response for a virtual source at the top geophone is consistent with the synthetic response. For the virtual source at the bottom geophone, the reflection response appears to be phase delayed, though its arrivals are consistent with the local subsurface geology. Similarly, the first-order estimated local transmission response successfully approximates that of the P-wave velocity in the reservoir. The study shows that reliable subsurface information can be obtained from borehole interferometry without detailed knowledge of the medium parameters. In addition, the method could be used for passive reservoir monitoring to detect velocity, attenuation, and/or interface time-lapse variations.
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