Extrapolation of elastic and petrophysical properties from wells using 3D prestack seismic amplitude data

This thesis describes the successful application of a new pre-stack stochastic inversion algorithm to the spatial delineation of thin reservoir units otherwise poorly defined with deterministic inversion procedures. The inversion algorithm effectively combines the high vertical resolution of wireline logs with the relatively dense horizontal coverage of 3D pre-stack seismic amplitude data. Multiple partial-angle stacks of seismic amplitude data provide the degrees of freedom necessary to estimate spatial distributions of lithotype and P- and S-wave velocities in a high-resolution stratigraphic/sedimentary grid. In turn, the estimated volumes of P- and S-wave velocity permit the statistical cosimulation of lithotype-dependent spatial distributions of porosity and permeability. The new stochastic inversion algorithm uses a Bayesian maximization criterion to populate values of lithotype and P- and S-wave velocities in the 3D simulation grid between wells. Property values are accepted by the Bayesian selection criterion only when they increase the statistical correlation between the simulated and recorded seismic amplitudes of all partial-angle stacks. Furthermore, inversion results are conditioned by the predefined measures of spatial correlation (variograms) of the unknown properties, their statistical cross-correlation, and the assumed global lithotype proportions. Using field data acquired in a fluvial-deltaic sedimentary rock sequence, it is shown that deterministic pre-stack seismic inversion techniques fail to delineate thin reservoir units (10-15m) penetrated by wells because of insufficient vertical resolution and low contrast of elastic properties. By comparison, the new stochastic inversion yields spatial distributions of lithotype and elastic properties with a vertical resolution between 10-15m that accurately describe spatial trends of clinoform sedimentary sequences and their associated reservoir units. Blind-well tests and cross-validation of inversion results confirm the reliability of the estimated distributions of lithotype and P- and S-wave velocities. Inversion results provide new insight to the spatial and petrophysical character of existing flow units and enable the efficient planning of primary and secondary hydrocarbon recovery operations.