Assisted history matching in the presence of frequent well intervention using generalize travel time inversion

In this paper we propose an efficient and novel technique that handles production discontinuities through a resampling of the production data, eliminating high frequency production details in a transformed domain. The technique also reduces non-monotonic behavior and results in a response more suitable for the GTTI based misfit calculations. Our proposed approach has been applied to an offshore turbidite reservoir with extensive well intervention resulting in highly detailed production responses. The static model contains more than three-hundred-thousand cells, complex sand depositional distribution combined with fault structures, four pairs of injector-producers, deviated producing wells and more than 8 years of production history. Previous history matching attempts using traditional approaches had difficulties matching production response at the individual well level. With our proposed modifications to the GTTI approach, a significant improvement was obtained on the well level match quality. Most importantly, by visualizing the streamlines and the dynamic adjustment of flow paths during history matching, we could easily identify the areas of inconsistency between the geologic model and the production data. The calibrated geologic model and streamline trajectories provided important insight about communication within sand channels, differences in flow paths and barriers that have not been included in the previous geologic and seismic interpretation.     

Sustainability assessment of bio-ethanol production in Brazil considering land use change,GHG emissions and socio-economic aspects

Three sustainability aspects of bioethanol production in Brazil were considered in this paper. Results show that the recent expansion of sugarcane has mostly occurred at the expense of pasturelands and other temporary crops, and that the hypothesis of induced deforestation is not confirmed. Avoided greenhouse gas emissions due to the use of anhydrous ethanol blended with gasoline in Brazil (E25) were estimated as 78%, while this figure would be 70% in case of its use in Europe (E10). Conversely, considering the direct impacts of land use change, the avoided emissions (e.g., ethanol consumed in Europe) would vary from −2.2% (i.e., emissions slightly higher than gasoline) to 164.8% (a remarkable carbon capture effect) depending on the management practices employed previous to land use change and also along sugarcane cropping. In addition, it was shown that where the bulk of sugarcane production takes place, in state of São Paulo, positive socio-economic aspects are observed. The general conclusion is that a significant share of ethanol production in Brazil can be considered sustainable, in particular regarding the three aspects assessed. However, as production conditions are extremely heterogeneous, a generalization of results is not possible.     

Modeling hourly electricity dynamics for policy making in long-term scenarios

Energy policies are often related to the global effort in reducing greenhouse gas emissions through increased use of renewable energies in electricity production. The impact of these policies is usually calculated by energy planning tools. However, the modeling methodologies most currently used are not adequate to simulate long-term scenarios while considering the hourly dynamics of supply and demand.     

High-temperature hydrogen sulfide corrosion on the heat-affected zone of the AISI 444 stainless steel caused by Venezuelan heavy petroleum

The aim of this study was to evaluate the effect of welding on the corrosion resistance of the heat-affected zone (HAZ) of the AISI 444 ferritic stainless steel in medium containing Venezuelan heavy oil. AISI 444 steel plates were welded through the use of three levels of welding heat input (4, 6 and 8 kJ/cm). Samples were extracted from the welded plates and thermally treated in three different temperatures (200, 300 e 400 °C), while immerged in petroleum for a period of 4 h. Optical microscopy (OM), scanning electronic microscopy (SEM) and energy dispersive X-ray analysis (EDX) techniques were used for the analysis of the surface and transversal section of the joint. Electrochemical trials of cyclic potentiokinetic reactivation of double loop (EPR-DL) were also carried out. It has been concluded that the temperature of treatment has direct influence on the level of material corrosion and that the increase in the welding heat input contributes to a higher level of corrosion.     

Phosphate inhibition on thermophilic acetoclastic methanogens: a warning.

The inhibitory effect of phosphate on acetoclastic-methanogens was investigated for three different thermophilic (55 degrees C) anaerobic consortia. When 70 mM of phosphate was tested, acetoclastic methanogens was completely inhibited in "Eerbeek" sludge which is dominated by Methanosaeta-like methanogens. For the "Hoogezand" sludge the specific methanogenic activity dropped by 79%, indicating that any of the acetate-consuming methanogens present in the sludge was more resistant to the phosphate applied. The results demonstrated that the inhibitory effect of phosphate may affect both methane production rate and final methane concentration and might also be time dependent. This study indicates that the degree of inhibition is species-dependent, and even more resistant species may be affected during long-term experiments. Such inhibition is a matter of concern for researchers since misleading conclusions might be taken from growth and specific methanogenic activity tests when considerable concentrations of phosphate buffer are used and no interference is expected.     

Exhaust emissions and electric energy generation in a stationary engine using blends of diesel and soybean biodiesel

The present work describes an experimental investigation concerning the electric energy generation using blends of diesel and soybean biodiesel. The soybean biodiesel was produced by a transesterification process of the soybean oil using methanol in the presence of a catalyst (KOH). The properties (density, flash point, viscosity, pour point, cetane index, copper strip corrosion, conradson carbon residue and ash content) of the diesel and soybean biodiesel were determined. The exhaust emissions of gases (CO, CO₂,C_xH_y,O₂, NO, NO_x and SO₂) were also measured. The results show that for all the mixtures tested, the electric energy generation was assured without problems. It has also been observed that the emissions of CO, C_xH_y and SO₂ decrease in the case of diesel–soybean biodiesel blends. The temperatures of the exhaust gases and the emissions of NO and NO_x are similar to or less than those of diesel.     

Evaluation of incremental learning algorithms for HMM in the recognition of alphanumeric characters

We present an evaluation of incremental learning algorithms for the estimation of hidden Markov model (HMM) parameters. The main goal is to investigate incremental learning algorithms that can provide as good performances as traditional batch learning techniques, but incorporating the advantages of incremental learning for designing complex pattern recognition systems. Experiments on handwritten characters have shown that a proposed variant of the ensemble training algorithm, employing ensembles of HMMs, can lead to very promising performances. Furthermore, the use of a validation dataset demonstrated that it is possible to reach better performances than the ones presented by batch learning.     

Volatile fraction of DOP “Castelo Branco” cheese: Influence of breed

“Castelo Branco” cheese is a Portuguese DOP cheese made from raw ewe’s milk coagulated with Cynara cardunculus, ripened for at least 40 days. “Merino da Beira Baixa” pure race is frequently used to produce milk for this cheese, however, exotic races such as Assaf and crusade of these two races are also used. The aim of this work has been to compare the volatile profile and sensory characteristics of DOP “Castelo Branco” cheeses manufactured during winter season with milk of breeds from Merino, Assaf and crusade of these two races and identify volatile compounds that can distinguish these cheeses.     

Catalytic performance of silica-aluminas synthesised with the help of chitosan biopolymer

Mesoporous amorphous silica-aluminas were synthesised with standard aluminium and silicon sources by means of the formation of inorganic–organic composites with the addition of chitosan biopolymer, and compared to analogous catalysts synthesised conventionally. Some catalysts were subjected to hydrothermal treatment. The resulting specific surface areas were from 480 to 573 m²/g in the untreated samples and 300–430 m²/g in the hydrotreated catalysts, average pore sizes ranging from 32 to 100 Å with sharp, unimodal distributions. The chitosan materials showed higher specific surface areas and larger pore sizes than those of their non-chitosan counterparts. The most important differences in the acidic properties were in the relationships between tetrahedral and octahedral aluminium atoms, the chitosan materials having higher relative amounts of tetrahedral aluminium than the conventional silica-aluminas. Evidences of stabilization in the physical and chemical properties were observed in the chitosan-containing catalysts. The catalytic performance was evaluated with the conversion of tri-isopropylbenzene at 400 °C, to assess activity and accessibility, and cyclohexene at 300 °C, to assess hydrogen transfer properties. The highest activity and accessibility was observed in the hydrotreated, chitosan-containing catalyst, while hydrogen transfer capabilities were similar to those of medium unit cell sizes, equilibrium commercial FCC catalysts.     

Mixture models for quantitative HIV RNA data

Clinical investigators are increasing their use of quantitative determinations of HIV viral load in their study populations. The distributions of these measures may be highly skewed, left-censored, and with an extra spike below the detection limit of the assay. We recommended use of a mixture model in this situation, with two sets of explanatory covariates. We extend this model to incorporate multiple measures across time, and to employ shared parameters as a way of increasing model efficiency and parsimony. Data from a cohort of HIV-infected men are used to illustrate these features, and simulations are performed to assess the utility of shared parameters.