High‐resolution Radon transforms for improved dipole acoustic imaging

Abstract

Imaging using dipole acoustic logging reflections has become a research topic of increasing interest in recent years. Extracting reflections from the whole waveform is both important and extremely difficult because the reflections are obscured by large‐amplitude direct waves. A method of wavefield separation based on high‐resolution Radon transforms has been applied to separate the reflected waves. First, an analysis of the common offset gathers shows that the linear Radon transform can be used to separate the direct and reflected wave fields. However, traditional linear Radon transforms cannot focus the wave event using the least squares method. An improved high‐resolution linear Radon transform is achieved using the principles of maximum entropy and Bayesian methods based on previous studies. The separation method is tested using synthetic data for hard and soft formations, a void model, and a fault model. The high‐resolution Radon transform method is used to process a field dataset and exhibits improved results compared with those of the standard method.

A High-Precision Method for Extracting Polarization Angle Under the Condition of Subsurface Wavefield Aliasing

“…Firstly, the three-component aliased signal is integrated from the time domain data along the parabola path to the Radon domain, to get the projection of the aliased waveforms on the Radon domain [15], [16]. The formula is as follows [17]:…”

“…16) I km (k, m = x, y, z) represents the covariance obtained from the data of the k and m axes. The mean value of the k-th component in the time window is µ k .…”