Flow Detection Using Well Seismic Data

Abstract

The aquifer studied, 20 to 130 m in depth, consists of tight karstic carbonates. 3D seismic survey revealed three high-porosity, presumably-water-productive, layers. Ambient seismic noise and VSP data have been recorded in 11 wells in order to evaluate the potential of the well seismic method to detect karstic bodies and flows, the results being compared with full waveform acoustic data, BHTV logs and flow measurements. The paper describes the methodology developed to detect flow using both ambient noise measurement and conversion of P-wave into Stoneley waves, observed on VSP data recorded with hydrophone sensor. An attribute, named VSP flow index, has been calculated to detect both karstic levels and flows. Concerning the karstic level detection, the results obtained on 11 wells are compared with full waveform acoustic data and confirmed by BHTV logging data and at a large scale by seismic data (3D seismic). The results obtained are consistent. The VSP data have also been compared with PLT data. An attempt to obtain a VSP flow detector has been done. The conclusions of the study show that ambient noise analysis and conversion of P- body waves into Stoneley waves can be fruitfully used to detect productive levels and flow circulation.