Automatable High Sensitivity Tracer Detection: Toward Tracer Data Enriched Production Management of Hydrocarbon Reservoirs

The development of automatable high sensitivity analytical methods for tracer detection has been one of the most central challenges to realize ubiquitous full-field tracer deployment to study reservoirs with many cross-communicating injector and producer wells. Herein we report a tracer analysis approach, inspired by strategies commonly utilized in the biotechnology industry, that directly addresses key limitations in process throughput, detection sensitivity and automation potential of state-of-the-art technologies. A two-dimensional high performance liquid chromatography (2D-HPLC) method was developed for the rapid fluorescence detection and simultaneous identification of a class of novel barcoded tracers in produced water down to ultra-trace concentration ranges (<1ppb), matching the sensitivity of tracer technologies currently used in the oil industry. The sample preparation process throughput was significantly intensified by judicious adaptations of off-the-shelf biopharma automation solutions. The optical detection sensitivity was further improved by the time-resolved luminescence of the novel tracer materials that allows the negation of residual background signals from the produced water. To showcase the potential, we applied this powerful separation and detection methodology to analyze field samples from two recent field validations of a novel class of optically detectable tracers, in which two novel tracers were injected along with a benchmarking conventional fluorobenzoic acid (FBA)-based tracer. The enhanced resolving power of the 2D chromatographic separation drastically suppressed the background signal, enabling the optical detection of a tracer species injected at 10x lower concentration. Further, we orthogonally confirmed the detection of this tracer species by the industry standard high-resolution accurate mass spectrometry (HRAM) technique, demonstrating comparable limits of detection. Tracer detection profile indicated that the transport behavior of the novel optical tracers through highly saline and retentive reservoir was similar to that of FBAs, validating the performance of this new class of tracers. Promising steps toward complete automation of the tracer separation and detection procedure have drastically reduced manual interventions and decreased the analysis cycle time, laying solid foundation to full-field deployment of tracers for better reservoir characterizations to inform decisions on production optimization. This paper outlines the automatable tracer detection methodology that has been developed for robustness and simplicity, so that efficient utilization of the resultant high-resolution tracer data can be applied toward improving production strategy via intelligent and active rate adjustments.