A high-resolution weighted AB semblance for dealing with amplitude-variation-with-offset phenomenon

Abstract

Velocity analysis is an essential step in seismic reflection data processing. The conventional and fastest method to estimate how velocity changes with increasing depth is to calculate semblance coefficients. Traditional semblance has two problems: low time and velocity resolution and an inability to handle amplitude variation-with-offset (AVO) phenomenon. Although a method known as the AB semblance can arrive at peak velocities in the areas with an AVO anomaly, it has a lower velocity resolution than conventional semblance. We have developed a weighted AB semblance method that can handle both problems simultaneously. We have developed two new weighting functions to weight the AB semblance to enhance the resolution of velocity spectra in the time and velocity directions. In this way, we increase the time and velocity resolution while eliminating the AVO problem. The first weighting function is defined based on the ratio between the first and the second singular values of the time window to improve the resolution of velocity spectra in velocity direction. The second weighting function is based on the position of the seismic wavelet in the time window, thus enhancing the resolution of velocity spectra in time direction. We use synthetic and field data examples to show the superior performance of our approach over the traditional one.

Seismic noise attenuation using an online subspace tracking algorithm

“…Even in post-stack seismic data, the existence of noise will affect interpretation result which directly links the seismic images with subsurface oil & gas reservoirs (Wang et al 2011;Chen 2015bChen , 2016Gan et al 2016e;Ren & Tian 2016;Zhang et al 2016e). A successful separation between useful reflection signals and unwanted noise is a long standing problem in the area of seismic data processing and greatly affects the fidelity of subsequent seismic imaging and geophysical inversion, like amplitude-variation-with-offset (AVO) inversion, full waveform inversion, attenuation estimation and geological interpretation (He & Wu 2015;Li et al 2016a;Lines et al 2016;Liu et al 2016a;Mousavi & Langston 2016a,b;Mousavi et al 2016;Qu & Verschuur 2016;Qu et al 2016a;Zhang et al 2016f;Jin et al 2017;Li et al 2017;Ebrahimi et al 2017;Mousavi & Langston 2017). Effectively rejecting the cross-talk interference caused in the simultaneous-source seismic acquisition also plays a significant role in tremendously saving the data recording cost (Berkhout 2008;Qu et al 2014Qu et al , 2015Qu et al , 2016bAbma et al 2015;Chen 2015a;Zu et al 2015Zu et al , 2017aZhou 2017).…”

A general framework for anisotropic and wavefront moveout parameter analysis

“…The major limitation of this technique was added overhead associated with the calculation of the local similarity. Ebrahimi et al (2017) extended the work of Kahoo et al (2016) by applying their proposed weighting functions to the AB-semblance (Fomel 2009). The issue of resolution and dynamic range being heavily dependent on user-defined weighting constants in the weighting functions is still apparent in this approach.…”

“…W (r i , τ ) can be replaced by an offset or offset-azimuth dependent trend function to account for AVO anomaly particularly of the class IIP variety (Chen et al 2015, Ebrahimi et al 2017, Fomel 2009, Yan and Tsvankin 2008. Class IIP anomalies are associated with a polarity offset in the amplitude distribution (Rutherford and Williams 1989).…”

“…The explicit expressions for A(τ ) and B(τ ) are given by Equation 3.33 and Equation 3.34 respectively (Ebrahimi et al 2017, Fomel 2009, Wilson and Gross 2016. Its important to note that expressions for A(τ ) and B(τ ) are given in Chapter 2.…”

“…Many approaches have been proposed to alleviate these issues. The accuracy problem associated with AVO/AZ polarity reversals has been remedied by many different modifications of the semblance operator and similar type operators (Abbad and Ursin 2012, Abbad et al 2009, Ebrahimi et al 2017, Fomel 2009, Sarkar et al 20022001, Wilson andGross 2016). With regards to resolution, a plethora of; correlation, weighted semblance, eigenstructure and singular value decomposition (SVD) based methods, and differential semblance based methods have been proposed.…”