SBIR Phase II: Using microbial genetic data to improve oil production efficiency and reduce environmental impact

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project will be to increase the efficiency of domestic oil production. Using current methods, the oil industry is able to extract only 5% of the known hydrocarbon from shale formation. This represents more than $500B of potential oil and gas that cannot be economically produced for the US economy. The aim is to increase the efficiency of oil production by providing novel subsurface information to improve operational decision making. The resulting value increase for a producer can be up to $1M per well. In addition, it is possible to significantly reduce the environmental impact of the hydraulic fracturing process, which is currently only 50% efficient. By providing novel subsurface data for the industry, this information can reduce environmental impact by saving up to 45B gallons of fresh water and 1M rail cars of mined sand. Furthermore, the analysis of subsurface microbiomes is a rich area for new academic knowledge. Over 80% of the microbial strains identified in Phase I have never been documented in public references. This work not only provides economic and social value, but also expands scientific knowledge. This SBIR Phase II project proposes to use next-generation microbiome analyses to increase the efficiency of domestic oil production. The research objective is to analyze the subsurface hydrocarbon microbiome to characterize hydrocarbon reservoirs and leverage this new data source to increase current efficiency rates. The goal is to analyze 50 producing wells in the Southwestern US, and develop statistical models linking microbial profiles to key reservoir properties that can increase production efficiencies. The analytical method employed will utilize technology stemming from over $20 million in government funding to the University of Colorado used to create bioinformatics software known as "QIIME." The QIIME technology has been extensively tested in analyzing and modeling the human microbiome, but has never been applied to the subsurface hydrocarbon microbiome prior to the Phase I work. By combining advances in cloud computing, DNA sequencing, and novel software analytics, this project will demonstrate that these microbial communities correlate to meaningful production parameters for the oil and gas industry. In so doing, the project will demonstrate at pilot scale that this new information source can be utilized as a novel, non-invasive, low-cost reservoir characterization tool that allows the industry to maximize hydrocarbon production while minimizing environmental impact.