Alexander Klokov

Seismic diffraction interpretation at Piceance Creek

AbstractWe applied time-domain seismic diffraction imaging to a 3D data set from the Piceance Creek Field, Piceance Basin, northwest Colorado. The work was motivated by the need for insight into natural fracture distribution, thought to influence production. We used a novel chain of two previously developed processing steps to separate diffractions from the recorded wavefield — One step is applied to the conventional stack volume, and the other was applied to migrated dip-angle gathers. The diffractions were then imaged independently for interpretation. Comparison of seismic attributes, commonly used for fracture characterization, found that the resulting diffraction image had lateral resolution comparable to or greater than the discontinuity-type attributes and provided information complementary to azimuthal anisotropy measurements. The diffraction image from Piceance Creek had advantages over attributes in interpretation confidence because diffractions were a direct seismic response to subsurface featur...

Diffraction imaging of polygonal faults within a submarine volcanic terrain, Maverick Basin, south Texas

AbstractPolygonal fault systems are common structural features of intracratonic continental margins. The map-view geometry of these faults became apparent with the use of powerful fault-imaging seismic attributes, such as coherence and curvature. However, these attributes lack the amplitude information necessary for lithological evaluation. We developed a 3D diffraction volume that not only imaged faults but also contained amplitude information. From the unmigrated stack volume, we extracted diffractions that were transformed into amplitude envelope and root-mean-square amplitude volumes. These attributes, together with clay volume (Vclay) data, were extracted along interpreted horizons and fault planes. Crossplots between seismic attributes and Vclay enabled linear relationships between the attributes and Vclay, which were used to infer lithological composition within fault zones. Our results found that, although the fault zones were clay filled, some subvertically inclined clay-poor zones that could ser...

Correlation between seismic diffractions extracted from vertical seismic profiling data and borehole logging in a carbonate environment

AbstractSeismic diffractions may play an important role in seismic interpretation because they characterize geologic objects that might not be visible for conventional seismic attribute analysis. Diffractivity may be caused by, and consequently may define, tectonic dislocations (faults and fractures), lithologic variations, and fluid saturation within rocks. We have tied seismic diffractions extracted from vertical seismic profiling (VSP) data and borehole logging, from which we recognized the reasons that were responsible for diffractivity of the strata. First, we processed a multisource multicomponent VSP data set to extract seismic diffractions and constructed diffraction images of the strata for all three of the VSP data components. Then, we performed joint analysis of well logs and diffractions to obtain petrophysical attributes associated with diffraction images. We divided the rock succession into several units, which have different diffraction properties. We identified compacted rock, alternating ...

Diffraction Imaging in the Dip-angle Domain - Viking Graben Case Study

“DEDICATED - Case Studies in Diffraction Imaging and Interpretation” We apply a diffraction imaging technique based on the Hybrid Radon Transform in the dip-angle domain to the 2D North Viking Graben seismic data set. Diffractions in this case correspond to seismic response from a fault system and rough reflection boundaries. The constructed diffraction image allows us to locate faults which are not clearly visible in the conventional reflection seismic image.

Introduction to special section: Skeletonized/sparse/multiscale geophysical inversion for the interpreter

Seismic inversion methods are mostly based on gradient-based optimization techniques that minimize the data residual between the observed and the predicted data, which is usually computed from a given estimate of the model. This conventional optimization problem can be reformulated as inversion of