Amplitude preserving AMO from true amplitude DMO and inverse DMO
Starting from the definition of Azimuth Moveout ( AM O) as the cascade of D M O and inverse D M O at different offsets and azimuths, we derive an amplitude-preserving function for the AM O operator. This amplitude function is based on the FK definition of D M O and the definition of its true inverse. Similar to Liner’s formalism of a true inverse for Hale’s D M O, we derive an asymptotically true inverse for Black/Zhang’s D M O and Bleinstein’s Born D M O. A numerical test is given that compares amplitude preservation using kinematically equivalent D M O operators cascaded with their true inverses. We define amplitude-preserved processing as the preservation of the offset-dependent reflectivity after AM O transformation, where the reflectivity is considered to be proportional to the peak amplitude of each event. We found that an AM O operator defined using Zhang’s D M O cascaded with its true inverse best reconstructs data amplitudes after transformation to a new offset and azimuth. The new amplitude function represents an amplitudepreserving azimuth moveout.
Azimuth moveout: the operator parameterization and antialiasing
A practical implementation of azimuth moveout (AMO) must be both computationally efficient and accurate. We achieve computational efficiency by parameterizing the AMO operator with the help of a transformed midpoint coordinate system. To achieve accuracy, the AMO operator needs to be carefully designed for antialiasing. We propose a modified version of Hale’s antialiasing algorithm, which switches between interpolation in time and interpolation in space depending on the operator dips. The method is applicable to a vide variety of integral operators and compares favorably with the triangle filter technique. A simple synthetic example tests the applicability of the method to the AMO case.
Local public health agency performance and community health status.
This study describes the results of an analysis of the relationship between local public health agency performance and health outcomes. Findings support the model that local public health agency performance affects community health status, and depending on the outcome, performance contributions vary. New hypotheses are offered that could help determine how system performance affects health outcomes.