Next Generation Oilfield on-Site Trace Chemicals Analysis by SERS

Accurate and precise monitoring of chemical additives in oilfield brine is an important aspect of oil and gas operations towards corrosion control and flow assurance. Many operators are required to monitor the residual concentrations of chemical additives in production systems at specific locations to monitor and troubleshoot factors affecting chemical deliverability and performance. However, residual measurements are extremely problematic due to many factors, including the surface active nature of the chemicals and high ionic strength of the brine. The error on residual measurements can often be over 100%. Residual measurement typically requires the collection of a water sample, which often needs to be transported to a centralized analytical laboratory. Analytical techniques used to measure residuals are based on several combinations of separation (e.g. chromatography, liquid-liquid extraction, etc.) and detection (e.g. various forms of spectroscopy). However, most of these methods lack portability and require tedious laboratory procedures located off-site. The current paper describes a nanotechnology-enabled Raman spectroscopy method developed and tested for monitoring chemical inhibitor residuals. Development of this technology with handheld instrumentation provides better detection and quantification of chemical additives in the field and reduces time and cost compared to sending samples to off-site laboratories for data collection.

A Fast Approximation for Adaptive Wavelength Selection for Infrared Chemical Sensors

<p>Active mid-infrared spectroscopy with tunable lasers is a leading technology for standoff detection and identification of trace chemicals. Information-theoretic optimal selection of the laser wavelength offers the promise of increased detection confidence at lower abundances and with fewer wavelengths. Reducing the number of wavelengths required enables faster detections and lowers sensor power consumption while keeping the optical power under eye safety limits. This paper presents an approximation to the mutual information which operates ~40000x faster than traditional techniques, thereby making near-optimal real-time sensor control computationally feasible. Application of this technique to synthetic data suggests it can reduce the number of wavelengths needed by a factor of two relative to an evenly-spaced grid, with even higher gains for chemicals with weak signatures.</p>

A Fast Approximation for Adaptive Wavelength Selection for Infrared Chemical Sensors

<p>Active mid-infrared spectroscopy with tunable lasers is a leading technology for standoff detection and identification of trace chemicals. Information-theoretic optimal selection of the laser wavelength offers the promise of increased detection confidence at lower abundances and with fewer wavelengths. Reducing the number of wavelengths required enables faster detections and lowers sensor power consumption while keeping the optical power under eye safety limits. This paper presents an approximation to the mutual information which operates ~40000x faster than traditional techniques, thereby making near-optimal real-time sensor control computationally feasible. Application of this technique to synthetic data suggests it can reduce the number of wavelengths needed by a factor of two relative to an evenly-spaced grid, with even higher gains for chemicals with weak signatures.</p>

POLUTAN LOGAM BERAT DALAM EKOSISTEM MANGROVE

HEAVY METAL POLLUTANTS IN MANGROVE ECOSYSTEM. Mangrove is an unique tropical ecosystem with the marine, riverine, terrestrial and atmosphericcomponents influencing the occurrence, speciation, bioavailability and fate of trace chemicals. Mangrove ecosystem are one of the most threatened tropical environment due to habitat loss, aquaculture expansion, overharvesting and increase of pollution load. In this paper, the role of mangrove to act as a sink of pollutants, accumulation and biomagnifications of heavy metals is discussed.