An-elastic seismic inverse methods for geological monitoring and energy development

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The ability to obtain accurate and highly-resolved maps of subsurface geological structure is critical, both for sustainable exploration/production of Canadian energy resources, and for monitoring of sites of geological sequestration of carbon dioxide. The impact, in economic, environmental, and social arenas, of technological and scientific advances in these areas is significant. Techniques of wave imaging and inversion applied to data collected from active-source seismic surveys are currently the most effective approach to providing these maps. This project will involve a systematic study of (1) mathematical methods that have the potential to provide new, direct, and accurate seismic inverse procedures, and (2) problems of modelling, imaging, parameter determination, and resolution enhancement of seismic data affected by seismic attenuation, a phenomenon observed in seismic data when the subsurface responds an-elastically to seismic stresses. Overlapping aspects of (1) and (2) will be emphasized: an-elastic Earth parameters are a strong link between seismic data and subsurface porosity, permeability, and various indicators of fluid flow under stress. Hence, merging the two lines of research, to provide enhanced and reliable methods for determination of these parameters, would mean a clearer picture of the character and state of stress and flow in a geological volume containing sequestered fluids or hydrocarbon resources. Inverse scattering theory, cast to accommodate an-elasticity, will form the foundation of the project. In progressing this theory, new methods for linear and non-linear direct estimation of an-elastic lithological parameters and absorption compensation, both occuring with reduced requirement for prior information, will be sought. Groundwork has been laid through study of the an-acoustic case: it has been shown that these inverse scattering procedures work through analysis of the dispersive AVA signatures of absorbing targets. This nuanced type of data variability is just beginning to be reported in exploration relevant studies. Connected sub-projects include the application of similar methods for time-lapse monitoring and ground-penetrating radar data.