Optimizing amplitude inversion utilizing statistical comparisons of seismic to well control data

Abstract

A method for obtaining enhanced seismic data and optimized inverted reflectivities includes computing statistical well characterizations based upon band-limited well reflectivities for a subsurface region. Sets of processed seismic data are computed by applying differing processing sequences to seismic data corresponding to the subsurface region. Inverted reflectivities are computed by inverting the sets of processed seismic data. Statistical seismic characterizations are computed based upon the inverted reflectivities. Statistical difference measurements (SDMs) are computed between the statistical well and seismic characterizations. An optimal processing sequence is selected based upon the computed SDMs. Enhanced seismic data is obtained by processing the seismic data corresponding to the subsurface region. An optimal seismic inversion algorithm is obtained based upon the computed SDMs. The seismic data is inverted using the optimal seismic inversion algorithm to produce a set of optimized inverted reflectivities.

Description

technical field [0001] The present invention relates generally to seismic detection of subsurface formations, and more particularly to the use of well control data to improve the quality of seismic processing and amplitude inversion. Background technique [0002] During the last 25 years, the oil and gas industry has sought to derive more information about subsurface properties from seismic data—especially detailed information about subsurface pore flow, porosity, facies, pressure, and geometry. This is accomplished in part by using the seismic data in combination with well log information to improve the accuracy of subsurface properties estimated from the seismic data. These efforts are rewarded by improved exploration success rates and selection of "sweet spots" for development wells. This success is largely based on the recovery of the relative acoustic impedance (the product of the change in density and compression velocity at the interface). [0003] Figure 1 shows a ...

AI Technical Summary

Problems solved by technology

Such post-inversion analysis does not introduce additional uncertainties and errors often cannot compensate for inappropriate processing

[0094] In conclusion, as mentioned above, there are several disadvantages in conventional seismic processing and magnitude inversion

The first disadvantage is that the magnitude processing and inversion sequence may be suboptimal due to poor parameter selection, which results in suboptimal signal-to-noise ratios for the inverted reflectivity at and away from the well control

The second disadvantage is the lack of criteria for QC (Quality Control) in the selection of processing and inversion parameters for the region of interest applicable at well control and away from well control

This poses the problem that the accuracy of the inversion results is far from locations where constraints cannot be applied

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