Enhancing Reservoir Visualization with Spectral Decomposition
Author: subsurfaceAI

Spectral decomposition adds value to visualization and interpretation workflows by revealing details normally overlooked in full bandwidth seismic displays.

In Alberta’s Blackfoot field, the oil- and gas-producing Lower Cretaceous Glauconite Member contains shales and quartz sands of lacustrian and channel origin. The hydrocarbon reservoirs typically occur where the porous sands pinch out against impermeable sands or shales. Three channel phases have deposited sands with up to 18% porosity. However, the channel sands can be difficult to differentiate from the adjacent low-permeability strata because the lithotypes share similar P-wave impedances. To better visualize the channel facies in the Blackfoot data, we implemented a workflow combining VisualVoxAt’s strata-grid module with the software’s spectral decomposition capabilities.

In imaging the Glauconite channel sands, running multiple spectral decomposition methods helped to resolve the channel morphology and bed thickness relationships within the channel facies. While TFCWT spectral decomposition provided the best resolution of all the methods, it also took the longest time to calculate. The S-Transform maps provided similar results to TFCWT and were faster to generate, making the S-Transform method the most efficient technique for resolving the channels in this particular study. Spectral decomposition can greatly improve visualization and interpretation workflows by revealing thin beds, lateral discontinuities and subtle anomalies not readily identified in poststack data. By correlating the spectral maps back to well logs and attribute relationships, the technique can help the interpreter to better understand complex reservoir plays and plan drilling strategies with greater confidence.

Janice Liwanag, Dr. Rongfeng Zhang, Karl Mirotchnik, Geomodeling Technology Corp

Published in the Drilling and Exploration World Journal July 2006