SBIR Phase I: Paramagnetic Spin-Probes for Corrosion Inhibition

这个小型企业创新研究（SBIR）项目的更广泛的影响/商业潜力解决了一种机制，以优化石油和天然气行业及其他行业项目的腐蚀抑制。据估计，仅美国工业每年就因腐蚀而损失1700亿美元。石油和天然气行业由于其复杂而苛刻的生产技术以及组件故障对环境的威胁而承担了高于平均水平的成本。如今，石油和天然气工业的标准抑制机制是注入化学抑制剂，通常是表面活性剂，其可以涂覆油田管的内部并避免腐蚀。由于故障的高成本，过度注入表面活性剂量导致成本过高和浪费送往炼油厂的不需要的化学品是非常常见的。不幸的是，以前没有一个好的方法来告诉太多的表面活性剂实际上是太多了。这就是这项创新带来的新的方面。它提出了一种机制，通过利用这些表面活性剂在受到非常大的磁场和GHz射频激发时的量子化学性质，实时检测是否有足够的表面活性剂。SBIR第一阶段项目提出从一种特殊设计的试剂中提取化学光谱，该试剂可以添加到采出液样品中，其中化学光谱将根据是否存在足够的表面活性剂来引起腐蚀抑制而改变。更具体地说，它将测量试剂的一些量子化学性质，称为其超精细结构，该结构将在表面活性剂胶束的存在下发生变化。基本上，胶束在该试剂内的自由基电子周围形成封闭屏障，从而改变这些电子在磁体和RF激发的组合中共振的方式。该项目的第一阶段将解决这种方法中的多个挑战，包括选择试剂和开发强大的算法，以将超精细数据转换为临界胶束浓度的量化，其中算法需要能够容忍油田流体中发现的典型杂质。第一阶段还将验证一种光谱方法，该方法可以将超精细数据发送到云端，基于人工智能的算法可以将光谱信息简化为操作员可操作的信息。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) project addresses a mechanism to optimize corrosion inhibition for projects covering the oil and gas industry and beyond. Corrosion costs US industries alone an estimated $170 billion a year. The oil and gas industry takes an above average share of these costs because of its complex and demanding production techniques, and the environmental threat should components fail. Today, the standard inhibition mechanism for the oil and gas industry is to inject a chemical inhibitor, typically a surfactant, that can coat the interior of the oilfield tubular and avoid corrosion. Because of the high cost of failure, it is extremely common to over-inject surfactant quantities resulting in excessive costs and the waste of unwanted chemicals sent to the refinery. Unfortunately, there has not previously been a good way to tell when too much surfactant was in fact too much. That is the specific new aspect brought by this innovation. It proposes a mechanism to detect in real-time that there is sufficient surfactant by taking advantage of quantum chemical properties of those surfactants when they are subject to very large magnetic fields and GHz radio-frequency excitation.This SBIR Phase I project proposes to extract a chemical spectrum from a specially designed reagent that can be added to a sample of produced fluid, where that chemical spectrum will change depending on whether there is sufficient surfactant to cause corrosion inhibition. More specifically it is going to measure some quantum chemical properties of the reagent called its hyperfine structure that will change in the presence of surfactant micelles. Essentially the micelles form a containment barrier around free radical electrons within that reagent and thereby change the way those electrons can resonate in the combination of the magnet and RF excitation. Phase 1 of the project will resolve multiple challenges in this approach, including the choice of reagent and the development of robust algorithms to convert hyperfine data into quantification of critical micelle concentration, where the algorithm needs to be able to tolerate typical impurities found in oilfield fluids. Phase 1 will also validate a spectroscopic approach that can result in the hyperfine data being sent to the cloud where AI-based algorithms can reduce the spectral information to actionable information for the operator.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.