SBIR Phase I: Using microbes as a cost effective sensor network to improve oil and gas production

这个小企业创新研究（SBIR）项目的更广泛的影响/商业潜力是提高石油生产的效率，并减少目前无法使用生物信息学软件预测基于地下微生物的油井特征的石油的百分比。 目前，超过50%的国内油藏无法经济地开采，缺乏地下信息是提高效率的关键障碍。 其目标是帮助释放目前技术无法实现的国内能源潜力中的1万亿美元经济价值。该项目旨在利用地下微生物作为传感器网络，为石油和天然气公司提供新的信息。这些信息将用于为增加产量的关键决策提供信息，这些决策将采用更有针对性的方法，从而提高美国的能源独立性，同时减少石油钻探和生产对环境的影响。通过这样做，该项目将为120亿美元的油藏数据和测井行业提供颠覆性价值。该SBIR第一阶段项目建议使用地下原生的微生物群落作为描述油藏关键特性的先进且具有成本效益的传感器网络。在地下深处，原生微生物与其生态系统之间存在着数万亿种独特的相互作用。 通过结合云计算、DNA测序和新型软件分析的进步，该项目将证明这些微生物群落与石油和天然气行业有意义的生产参数相关。在这样做的过程中，该项目将在试点规模上证明，这种新的信息源可以作为一种新型的、非侵入性的、低成本的储层表征工具，使该行业能够最大限度地提高油气产量，同时最大限度地减少对环境的影响。

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project is to increase the efficiency of oil production and to decrease the percentage of oil that is currently inaccessible using bioinformatics software to predict oil well features based on subsurface microbes. Over 50% of domestic oil reservoirs cannot be economically produced today, and a lack of information about the subsurface is a key roadblock to increasing this efficiency. The goal is to help unlock $1 trillion of economic value in domestic energy potential currently inaccessible with current technology. This project seeks to utilize the subsurface microbes as a network of sensors that provide novel information for oil and gas companies. This information will be used to inform key decisions that increase production with more targeted approaches that result in greater U.S. energy independence while reducing the environmental impact of oil drilling and production. In so doing, the project will provide disruptive value in the $12B reservoir data and well logging industry. This SBIR Phase I project proposes to use microbial communities that are native to the subsurface as an advanced and cost effective sensor network that describe key properties of the oil reservoirs. Deep within the subsurface, there are trillions of unique interactions of the native microbes to their ecosystem. 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.