We have developed and examined a novel seismic acquisition geometry called EcoSeis - a seismic acquisition method designed to lower the surface footprint and reduce green house gas emissions. The goal is to minimize environmental impact while maintaining high quality subsurface imaging. Phase I of the EcoSeis research comprised a rigorous processing, interpretation, and inversion study to understand how acquisition geometry and signal processing interpolation affect image quality and reservoir characterization. Successfully demonstrating that lower impact geometries with sufficiently high trace density can provide adequate subsurface resolution, the focus shifted into the pre-stack space. The quantitative interpretations, using pre-stack analysis and inversion, were conducted on both conventional and EcoSeis datasets. The results from each stage of the analyses were utilized to design and execute a commercial EcoSeis field trial. In this case study we explore how EcoSeis designs performed through inversion and discuss the operational learnings from field implementation of EcoSeis acquisition.
The goal of this case study was to demonstrate that it is possible to acquire high-resolution subsurface images with the proposed EcoSeis methodology while also lowering the surface footprint of the seismic acquisition and reducing greenhouse gas emissions during field operations. In the first phase of the research, a fully sampled dataset was decimated into various conventional and alternative geometries, then reprocessed and evaluated. The evaluation examined both post-stack image quality and pre-stack attributes through detailed qualitative and quantitative interpretation analyses followed by inversion. The results from this study were used to design and execute the first EcoSeis seismic acquisition program.
Seismic surveys provide a cost-effective method for evaluating subsurface oil and gas reservoirs, and recently, they have become a common prospecting method for mineral exploration, geothermal resources, near surface hazard identification, and Carbon Capture Sequestration (CCS). Conventional seismic exploration programs often target deep reservoirs at two-to-three-kilometre depths. For these surveys, it is relatively easy to achieve high trace densities, on the order of millions of traces per square kilometre, enabling accurate subsurface imaging. Achieving similarly high resolution for shallow surveys where the depth may only be 100m to 1000m is more challenging since a higher density of equipment is needed (Crook, 2022).
