Mitigating paraffin deposition in production lines has remained a critical issue for the oil industry to control the associated production and transportation cost. Recently, injection of paraffin inhibitors in the transportation pipelines has been widely used along with other strategies to improve production. This study investigates the effect of operating temperatures and geometries on the performance of paraffin inhibitors. Moreover, the experimental temperature differences (i.e. changes in coolant temperature and bulk oil temperature) strongly influence the inhibitor efficacy indicating that these conditions must be optimized prior to field applications. The experiments were conducted with a Caspian Sea (CS) condensate at different temperature conditions using two paraffin inhibitors (Maleic anhydride co-polymers: PI-B and PI-C, where PI-B has a higher carbon chain length than PI-C). The inhibitor concentration of 500PPM and a 24h time duration is maintained for all the experiments. The deposit mass and wax content were analyzed. Wax mass flux increases with the increasing temperature difference in constant bulk oil temperature experiments. In contrast, the mass flux increases first and then decreases with the decrease in the temperature difference in constant coolant temperature experiments. Hence, it is important to consider the influence of operating conditions that may change the oil properties significantly and ultimately the magnitude of the paraffin deposition. Deposit mass (decreased) and wax content (increased) are significantly influenced by the presence of inhibitors. The inhibitor efficacy, that incorporates both deposit mass and wax content, is calculated at different operating temperature differences. It has been observed that the efficacy strongly varies with the operating region. Hence, it is necessary to select proper inhibitors based on the local operating temperature conditions during injection. This study provides a fundamental understanding between operating parameters and inhibitor efficacy. The usage of inhibitors is highly complicated and the knowledge obtained through this investigation disseminates crucial information on selecting proper inhibitor for field applications.
Pooling in directed-evolution experiments will greatly increase the throughput of screening systems, but important parameters such as the number of good mutants created and the activity level increase of the good mutants will depend highly on the protein being engineered. The authors developed and validated a Monte Carlo simulation model of pooling that allows the testing of various scenarios in silico before starting experimentation. Using a simplified test system of 2 enzymes, β-galactosidase (supermutant, or greatly improved enzyme) and β-glucuronidase (dud, or enzyme with ancestral level of activity), the model accurately predicted the number of supermutants detected in experiments within a factor of 2. Additional simulations using more complex activity distributions show the versatility of the model. Pooling is most suited to cases such as the directed evolution of new function in a protein, where the background level of activity is minimized, making it easier to detect small increases in activity level. Pooling is most successful when a sensitive assay is employed. Using the model will increase the throughput of screening procedures for directed-evolution experiments and thus lead to speedier engineering of proteins. Key words: directed evolution, high-throughput screening, Monte Carlo simulation, protein engineering INTRODUCTION POOLING IS THE SIMULTANEOUS ANALYSIS of multiple samples followed by the deconvolution of pools that show promising results. Similar techniques have been used to increase throughput in combinatorial chemistry for drug discovery, 1,2 genome sequencing and chromosome mapping, 3-6 oligonucleotide microarrays, 7,8 and testing of biological samples such as blood for the presence of organisms, contaminants, or characteristics of interest. [9][10][11][12] As noted by Bruno et al,5 "Whenever the objective is to find 'needles in a haystack' a reliable test indicating whether at least one needle occurs in a specific part of the haystack can greatly facilitate the isolation of the needles." In each case, the object is to balance the increase in sample size obtained by pooling with the decrease in ability to detect the analyte of interest. If pools become too large, the signal from the organism in question will be lost in the background of the assay. Directed evolution is an iterative method of protein engineering in which 1 or more genes that code for the protein of interest are subjected to random mutagenesis or recombination.13,14 The resulting variants, or mutant proteins, must then be sorted into good and bad performers. If the activity of interest cannot be tied to host survival (selection), then each mutant must be assayed individually, a process called screening. Because of the time-and resourceintensive nature of screening, laboratories are typically limited to screening 10 5 to 10 7 mutants per round of directed evolution. 15 The capacity limit affects the way error-prone PCR experiments are conducted: because the higher the mutation frequency, the larger the number of inactive muta...
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