Multiscale transforms are among the most popular techniques in the field of pixel-level image fusion. However, the fusion performance of these methods often deteriorates for images derived from different sensor modalities. In this paper, we demonstrate that for such images, results can be improved using a novel undecimated wavelet transform (UWT)-based fusion scheme, which splits the image decomposition process into two successive filtering operations using spectral factorization of the analysis filters. The actual fusion takes place after convolution with the first filter pair. Its significantly smaller support size leads to the minimization of the unwanted spreading of coefficient values around overlapping image singularities. This usually complicates the feature selection process and may lead to the introduction of reconstruction errors in the fused image. Moreover, we will show that the nonsubsampled nature of the UWT allows the design of nonorthogonal filter banks, which are more robust to artifacts introduced during fusion, additionally improving the obtained results. The combination of these techniques leads to a fusion framework, which provides clear advantages over traditional multiscale fusion approaches, independent of the underlying fusion rule, and reduces unwanted side effects such as ringing artifacts in the fused reconstruction.

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Understanding the strengths and limitations of rapidly advancing distributed acoustic sensing (DAS) technology used for recording vertical seismic profile (VSP) data is achieved by comparing DAS and geophone data sets using both compressional-wave (P-wave) and shear-wave (S-wave) VSP data and their corresponding geophysical answer products. We validate the kinematics (time) and dynamics (amplitude) of DAS VSP data by examining the extracted slowness values, response-to-incident angles, corridor stacks, and common-depth-point (CDP) transforms. For kinematics validation, the slowness values computed from P- and S-wave components of DAS VSP data agree with the geophone slowness values. For dynamics validation, we confirm the cos2 θ response of the fiber to the incident angle of the seismic wavefield for P-waves and sin 2θ for S-waves. The amplitudes of the P-wave corridor stacks are comparable; the S-wave corridor stacks are similar for shallow events and differ for later events due to the limited response of the fiber to S-waves at near-vertical angles of incidence. High-quality CDP transform images are obtained for P- and S-waves. These analyses indicate that properly acquired DAS VSP data sets are reliable for the kinetics and dynamics of both P- and S-waves. Once the fiber-optic cable is installed in the well, VSP acquisition costs are greatly reduced because DAS data may be acquired with no additional well intervention. The extensive spatial coverage obtained using fiber-optic cables, the ease of acquiring time-lapse (4D) VSP data, and the reliability of the resulting DAS VSP data sets are making DAS technology an extremely important VSP acquisition tool.

Great advances have been made in distributed acoustic sensing (DAS) vertical seismic profile (VSP) data acquisition hardware and software. Here, we capture a quantitative assessment of the quality of DAS data at a single point in time. We apply comprehensive testing methods to determine the reliability of the data and its suitability as a supplement to geophone data or to gain access to wells where it would be difficult to deploy geophones. The test measurements are made on DAS and geophone data, which were collected at the same time and in the same well. We analyze the first breaks for waveform consistency, signal-to-noise (S/N) ratio, and slowness. Then, we examine the corridor stacks for waveform consistency and S/N ratio. Finally, we test the properties of the measurement, including linearity, repeatability, reliability, and response, as a function of the angle of incidence of a seismic wave to the fiber. The results show that the DAS VSP data provide accurate formation slowness logs and reliable amplitude information suitable for creating seismic images and corridor stacks.

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