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Brazilian pre-salt reservoirs are mainly carbonate formations and they represent a great opportunity for research development. There is an increasing need of synthetic simulation models that reproduce these Pre-salt flow features for research development in reservoir simulation. This work presents a simulation benchmark model available as public domain data that represents Brazilian pre-salt trends and add a great opportunity to test new methodologies for reservoir development and management using numerical simulation. The work structure is divided in three steps: development of a reference model with known properties, development of a simulation model under uncertainties considering a specific date that represents the field development phase, and, elaboration of a benchmark proposal for studies related to the oil field development and production strategy selection. The reference model, treated as the real field, is a fine grid model in order to guarantee a high level of geologic details. The simulation model under uncertainties is a large scale model, a result of a development project considering an initial stage of field management. The benchmark model is based in a combination of Pre-salt characteristics and Ghawar field information given its diagenetic events and flow features close to Pre-salt. Based on the available information, several uncertainty attributes were considered in structural framework, facies, petrophysical properties, discrete fracture network. Economic and technical uncertainties were also considered. There is an increasing need of synthetic simulation models that reproduce these Pre-salt flow features for research development in reservoir simulation. This work presents a simulation benchmark model available as public domain data that represents Brazilian pre-salt trends and add a great opportunity to test new methodologies for reservoir development and management using numerical simulation. The main result of this project is achieved: the construction of a reference model and the construction of a simulation model under uncertainties assuming the well log information from three wells. This work provides a great contribution for further research development in reservoirs with geologic and dynamic pre-salt trends.

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<b><i>Introduction:</i></b> A critical point for using blood purification during sepsis may be the potential interaction with antimicrobial therapy, the mainstay of sepsis treatment. The aim of our study was to investigate the vancomycin removal during hemoperfusion (HP) using HA380 cartridge. <b><i>Methods:</i></b> This is an experimental study, in which 500 mL of solution was circulated in a closed-circuit (blood flow of 250 mL/min) simulating HP ran using HA380. Vancomycin was added to reach a through concentration or a very high concentration to evaluate the removal ratio (RR) during 120 min of HP. Comparison between blood-crystalloid solution and balanced solution was performed by using Kruskal-Wallis test. The kinetics of vancomycin removal and the adsorption isotherm were evaluated. <b><i>Results:</i></b> We found a complete removal of vancomycin at baseline through concentration of 23.0 ± 7.4 mg/L. Using extremely high concentration (baseline 777.0 ± 62.2 mg/L), RR was 90.1 ± 0.6% at 5 min and 99.2 ± 0.6% at 120 min. No difference in terms of RR was found between blood-crystalloid mixture and balanced solution. The kinetics of the vancomycin reduction followed an exponential decay. Repeated boluses (total amount of 2,000 mg) resulted in cumulative adsorption of 1,919.4 mg with RR of 96.6 ± 1.4%, regardless of the amount injected (100 vs. 500 mg). Vancomycin adsorption onto HA380 followed the Langmuir isotherm model. <b><i>Conclusions:</i></b> A considerable amount of vancomycin was rapidly removed during in vitro HP with HA380. Clinical studies are needed to determine whether this may lead to underdosing. Drug therapeutic monitoring is highly recommended when using HA380 for blood purification in patients receiving vancomycin.

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8In this study, we consider robustness as a risk management method in the development of 9 complex petroleum fields, complementing the well-known techniques of acquiring new 10 information and adding flexibility to the production system. To create a robust production 11 strategy we aim to reduce sensitivity to uncertainty. Our methodology is based on the analyzed 12 performance of an optimized production strategy, covering all possible scenarios. We use 13 technical and economic indicators to objectively identify and quantify refinements in this 14 strategy to assure good performance across possible scenarios. We focus on the robust number 15 and placement of wells, and robust platform processing capacities. We consider the robustness 16 of net present value and of the recovery factor, computed using Multi-Attribute Utility Theory. 17We quantify the risk through semi-deviation, instead of standard deviation, to focus on the 18 downside volatility. Refining an optimized production strategy significantly improved the 19 optimization process by increasing the expected value of each objective and, dramatically 20 reduced the downside risk. 21 22 Keywords: field development; uncertainty management; robustness; production strategy; semi-23 deviation; reservoir simulation. 24 25 The upstream sector, particularly in offshore fields, is considered high-risk, comprising 29 considerable investment in complex, uncertain scenarios. Various sources of uncertainties may 30 coexist during the development phase, the focus of this study: (1) geological uncertainties, 31 associated with recoverable reserves and flow characteristics; (2) operational uncertainties, 32 related to system availability; and (3) economic uncertainties, such as oil price, capital 33 expenditures (CAPEX) and operational expenditures (OPEX). Thus, uncertainty and risk 34 analyses are fundamental to decide whether and how to develop a field. 35

Decision-making processes for selecting an oil exploitation strategy can be complex due to the high number of variables to be optimized. Many times, it can be unfeasible to search an optimal solution by evaluating a high quantity of variables simultaneously. In this case, assisted methods that involve engineering analyses and mathematical optimization algorithms are an alternative to obtain a good solution. This paper shows the application of an assisted method to optimize a large number of variables of an oil exploitation strategy. The proposed methodology is to order and combine different optimization procedures with practical engineering analysis. The optimization variables include number and position of wells, platform capacities, wells opening schedule and wells shut-in time. The methodology is applied to a reservoir model based on a Brazilian offshore oil field to discuss the results obtained. Results indicate an efficient procedure for evaluating deterministic scenarios, suggesting optimization procedures for each decision variable and enabling the achievement of good quality solutions with a reasonable number of simulation runs. This is useful in many practical cases, mainly those, which require runs with long simulation time.