Exploration and production projects, whether for oil and gas, mining, or clean tech applications such as carbon capture and storage, typically begin with the acquisition of seismic data. Generally, these surveys involve optimizing the geometry for surface constraints and operational efficiencies. However, an equally important aspect is to optimize the geometries for reducing environmental impact. Finding the balance between reducing the environmental impact, optimizing costs, and maximizing data quality can be challenging. Sensitive animal habitats can be drastically affected by seismic survey, and the data quality can be negatively impacted by avoiding these areas. In this paper, a variety of data sets were used to understand ecosites, sensitive animal habitats, calving grounds and vegetation to rank the sensitivity of each area. Unique linear geometries were created to reduce the environmental footprint while still maintaining data quality. Results demonstrated that data quality could be maintained with up to a 55% reduction in linear km of seismic cutlines and equivalent reductions in greenhouse gas emissions. These geometries also resulted in cost savings from fewer linear km of cutlines and lower personnel requirements. Implementing linear geometries changes the way that seismic surveys are designed and depending on the scenario, these novel geometries can be applied to a whole survey area, or they can just be used in more sensitive areas to reduce the environmental impact.

Open-Access Online Publication: May 29, 2023