Abstract

We have studied using traveltimes of P- and S-waves and initial seismic-pulse rise-time measurements from natural microearthquakes to derive 3D P-wave velocity VP information (mostly structural) as well as P- and S-wave velocity VP/VS and P-wave quality factor QP information (mostly lithologic) in a known hydrocarbon field in southern Albania. During a 12-month monitoring period, 1860 microearthquakes were located at a 50-station seismic network and were used to obtain the above parameters. The data set included earthquakes with magnitudes ranging from –0.1 to 3.0 R (Richter scale) and focal depths typically occurring between 2 and 10 km. Kohonen neural networks were implemented to facilitate the lithological classification of the passive seismic tomography (PST) results. The obtained results, which agreed with data from nearby wells, helped delineate the structure of the reservoir. Two subregions of the investigated area, one corresponding to an oil field and one to a gas field, were correlated with the PST results. This experiment showed that PST is a powerful new geophysical technique for exploring regions that present seismic penetration problems, difficult topographies, and complicated geologies, such as thrust-belt regions. The method is economical and environmentally friendly, and it can be used to investigate very large regions for the optimal design of planned 2D or 3D conventional geophysical surveys.

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