Direct Trace Element Determination in Oil and Gas Produced Waters with Inductively Coupled Plasma - Optical Emission Spectrometry (ICP-OES): Advantages of High Salinity Tolerance (2019)

Waters co-produced during petroleum extraction are the largest waste stream from oil and gas development. Reuse or disposal of these waters is difficult due both to their high salinities, which can greatly exceed 35 g/L (seawater equivalent), and also the sheer volume of wastewater generated, which is estimated at nearly 900 billion gallons per year across the United States. Beyond disposal concerns, produced water may also represent a possible source of valuable mineral commodities. While an understanding of the trace element composition of produced water is required for evaluating the associated resource and waste potential of these materials, measuring trace elements in high salinity brines is challenging due to the dilution requirements of typical methods. Alternatively, inductively coupled plasma-optical emission spectrometry (ICP-OES) has shown promise as being capable of direct measurements of trace elements within produced waters with minimal dilution. Here we evaluate direct ICP-OES trace element quantification in produced waters through detection and quantification for 17 select trace elements (As, Al, Ba, Be, Cd, Cr, Co, Cu, Hg, Mo, Ni, Pb, Rb, Sb, U, V, and Zn) from 15 produced water samples. The produced waters range in salinity from 17 to 370 g/L and originate from the Eagle Ford, Marcellus, Middle Bakken/Three Forks, Wolfcamp/Cline, and Utica/Point Pleasant reservoirs. The ICP-OES results are compared against trace element levels determined using inductively coupled plasma-mass spectrometry (ICP-MS) from the same samples. Our results demonstrate the potential of an ICP-OES approach for the direct analysis of trace components from high salinity aqueous solutions with minimal dilution and provide additional trace element concentrations for waters from several important U.S. petroleum-generating continuous reservoirs where available data is sparse.