Seismic signature of a permeable, dual-porosity layer

Of the key reservoir properties, permeability seems to be the most elusive. Since the middle of the 90s, various seismic attributes have been proposed to map permeability by using detailed analysis of the frequency content of reflected wavetrains. Some attributes are expected to show a relative increase of high-frequency content with increased permeability; other attributes assume the opposite. Actually, both these trends were observed. A possible explanation of these observations is here derived from an effective model of a permeable dual-porosity layer enclosed by impermeable rocks. For such a model, the reflected wavetrain can be regarded as a sum of three components, one of which is related to acoustic-impedance contrasts, another to extra compliance caused by P-wave-induced fluid flows between fractures and intergranular pores with a high aspect ratio, and a third to the fluid-flow-induced, inelastic attenuation. In layered reservoirs, all the components tend to be frequency dependent, and the well-known dependence of the first component on the reflecting-layer thickness may strongly dominate the effects of permeability. Hence, predicting the behavior of a permeability attribute in a particular environment requires a modeling formalism that can be called permeability substitution by analogy with the widely used fluid-substitution technique.

Guidelines for building a detailed elastic depth model

We developed guidelines for building a detailed elastic depth model by using an elastic synthetic seismogram that matched both prestack and stacked marine seismic data from the Gippsland Basin (Australia). Recomputing this synthetic for systematic variations upon the depth model provided insight into how each part of the model affected the synthetic. This led to the identification of parameters in the depth model that have only a minor influence upon the synthetic and suggested methods for estimating the parameters that are important. The depth coverage of the logging run is of prime importance because highly reflective layering in the overburden can generate noise events that interfere with deeper events. A depth sampling interval of 1 m for the P-wave velocity model is a useful lower limit for modeling the transmission response and thus maintaining accuracy in the tie over a large time interval. The sea‐floor model has a strong influence on mode conversion and surface multiples and can be built using a checkshot survey or by testing different trend curves. When an S-wave velocity log is unavailable, it can be replaced using the P-wave velocity model and estimates of the Poisson ratio for each significant geological formation. Missing densities can be replaced using Gardner’s equation, although separate substitutions are required for layers known to have exceptionally high or low densities. Linear events in the elastic synthetic are sensitive to the choice of inelastic attenuation values in the water layer and sea‐floor sediments, while a simple inelastic attenuation model for the consolidated sediments is often adequate. The usefulness of a 1-D depth model is limited by misties resulting from complex 3-D structures and the validity of the measurements obtained in the logging run. The importance of such mis‐ties can be judged, and allowed for in an interpretation, by recomputing the elastic synthetic after perturbing the depth model to simulate the key uncertainties. Taking the next step beyond using simplistic modeling techniques requires extra effort to achieve a satisfactory tie to each part of a prestack seismic record. This is rewarded by the greater confidence that can then be held in the stacked synthetic tie and applications such as noise identification, data processing benchmarking, AVO analysis, and inversion.

Wave propagation effects on amplitude variation with offset measurements: A modeling study

Wave propagation effects can significantly affect amplitude variation with offset (AVO) measurements. These effects include spreading losses, transmission losses, interbed multiples, surface multiple reflections, P‐SV mode converted waves and inelastic attenuation. Examination of prestack elastic synthetic seismograms suggests that spreading losses and the transmission losses plus compressional interbed multiples are manifest mainly as a time and offset effect on the primary reflections. The surface related multiples and the P‐SV mode‐converted waves interfere with prestack amplitudes inducing distortions in the AVO pattern. Such distortions cause large variances in AVO model fitting. Prestack viscoelastic synthetic seismograms also suggest that inelastic attenuation further complicates the AVO response because of the offset and time variant amplitude decay effects and the phase change due to dispersion. Together, all these effects severely alter AVO behavior and result in serious errors in AVO parameter estimates being made from inadequately corrected seismograms. This modeling study suggests that time and offset dependent data processing prior to AVO analysis would be necessary to correct for the wave propagation effects, via either inverse filtering or model based approaches. Comparisons between acoustic and elastic synthetic seismograms show that corrections for the wave propagation effects derived using acoustic approximations are inadequate. Corrections need to be calculated based on elastic approximations provided that the inelastic attenuation effects have been previously removed.