Applying a new synchronous inversion of seismograms using maximum likelihood method and stochastic refinements to study ultra-thin oil-saturated reservoirs

Abstract

Seismic inversion makes use of single or multi-dimensional seismic trace data to derive elastic properties from seismic amplitude data. These elastic properties are subsequently used to make inferences about seismic lithology, lithologic properties, and the presence of fluids. Most implementations of seismic inversions operate on limited stacked subsets of the seismic data. Common inputs to inversion methods include angle stacks, offset stacks, or multiple stacks of time-lapsed data. The implementation in this paper makes use of a synchronous pre-stack inversion based on the maximum likelihood algorithm (Anat Canning and Alex Malkin, 2009). The PMLI inversion is applicable to time and depth angle or offset seismograms. It is a full pre-stack inversion, which inverts each and every trace of an offset or angle gather and returns elastic properties. The PMLI inversion can also invert partial angular or offset sums, which can be created in any processing system. As a complete pre-stack inversion, PMLI provides higher accuracy and noise immunity as observed in the output results of Pw and Sw impedances, density, Vp/Vs, Poisson’s ratio, Lambda Rho (LR) and Mu Rho (MR). PMLI also incorporates a necessary and effective preprocessing step, which is performed on-the-fly as part of the inversion process. Because the PMLI method operates on gathers, it is easily and efficiently parallelized for multi-core and multi-node clusters and for shared memory architectures.