A B S T R A C TThe link between the stress sensitivity of shaley sandstones and their porosity and clay content is investigated. This is achieved by firstly fitting a compliance-based stress-sensitivity law to laboratory measurements of ultrasonic velocity taken from four sets of reservoir sandstones, extracted from a variety of depositional settings. Correlations are then sought between the independent parameters of this law and the porosity or clay fraction of the rocks, which are then subsequently interpreted in terms of framework or pore-space-related microstructural clay models. The general conclusion drawn from the results is that both of the parameters defining the stresssensitivity law (the asymptotic modulus and the stress-dependent excess compliance) clearly vary with porosity. However, only the asymptotic modulus shows a convincing trend with clay and there is little observed variation of the stress-dependent compliance with clay. There is therefore a resultant variation of stress sensitivity with clay, but it is controlled only by the asymptotic modulus. The analysis also concludes that all four data sets fall into a framework-related category of clay model.
Seawater velocity variations are known to influence the quality of seismic, especially in deepwater areas. Here, this topic is extended to evaluate the effect on reservoir monitoring. A 3D data set from the Gulf of Mexico has been corrected for seawater velocity variations and the corresponding time and amplitude perturbations are measured. From this, a 4D synthetic data set is modeled for realistic reservoir production scenarios. The 4D modeled seismic is perturbed using similar errors to those measured on the real data in order to mimic realistic effects due to seawater velocity variations. Differences between the perturbed and unperturbed 4D volumes are assessed in order to quantify the impact of seawater velocity variations on various reservoir monitoring attributes. Large uncertainties on AVO intercept and gradient are revealed (up to 25 %), highlighting possible ambiguities in the interpretation of time-lapse AVO-derived parameters such as pressure and saturation.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.