In several parts of India, groundwater is the only reliable, year round source for drinking water. Prevention of fluorosis, a chronic disease resulting from excess intake of fluoride, requires the screening of all groundwater sources for fluoride in endemic areas. In this paper, the authors present a field deployable colorimetric analyzer based on an inexpensive smartphone embedded with digital camera for taking photograph of the colored solution as well as an easy-fit, and compact sample chamber (Akvo Caddisfly). Phones marketed by different smartphone makers were used. Commercially available zirconium xylenol orange reagent was used for determining fluoride concentration. A software program was developed to use with the phone for recording and analyzing the RGB color of the picture. Linear range for fluoride estimation was 0-2mgl(-1). Around 200 samples, which consisted of laboratory prepared as well as field samples collected from different locations in Karnataka, India, were tested with Akvo Caddisfly. The results showed a significant positive correlation between Ion Selective Electrode (ISE) method and Akvo Caddisfly (Phones A, B and C), with correlation coefficient ranging between 0.9952 and 1.000. In addition, there was no significant difference in the mean fluoride content values between ISE and Phone B and C except for Phone A. Thus the smartphone method is economical and suited for groundwater fluoride analysis in the field.
History matching large reservoir models under a realistic geological continuity constraint remains an outstanding problem. We propose a new combined geostatistical and streamline-based method potentially capable of history matching large reservoir models, while accounting consistently for geological continuity as provided by a permeability histogram and variogram and by production data. While most existing history-matching techniques somehow rely on the calculation of single-gridblock sensitivity coefficients, the proposed method avoids such calculation entirely by perturbing jointly effective permeabilities along a set of streamlines. Such perturbation results in large changes of the permeability field that reduce significantly error in each iteration of the history-matching procedure. The problem of mapping streamline effective permeability perturbations to single gridblocks is performed under a Gauss-Markov random function constraint. This novel stochastic mapping procedure accounts for the target histogram and variogram while honoring the streamline effective permeability perturbations. Forward flow simulation is achieved by a streamline simulator. The methodology is presented on synthetic cases; it appears to be computationally efficient and robust.
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