Average reservoir pressure determination for homogeneous and naturally fractured formations from multi-rate testing with the TDS technique

Average reservoir pressure is an important parameter which is utilized in almost all reservoir and production engineering studies. It also plays a relevant role in the majority of well intervention jobs, field appraisal, well sizing and equipment and surface facilities design.The estimation of the average reservoir pressure is normally obtained from buildup tests. However, it has a tremendous economic impact caused by shutting-in the well during the entire test. Since buildup tests are the most particular case of multi-rate tests, these are also used for estimation of the average reservoir pressure. Among them, two-rate tests present drawbacks because it is operationally difficult to keep constant the flow rates. Conventional methods for determination of the average reservoir pressure can be readily extended to multi-rate tests once the rigorous time is converted to equivalent time by time superposition.In this article a new, easy and practical methodology is presented for the determination of the average pressure in both homogeneous and naturally fractured reservoirs from multi-rate tests conducted in vertical oil wells located inside a close drainage region. The methodology which follows the philosophy of the TDS technique uses a normalized pressure and pressure derivative point found on any arbitrary point during the pseudosteady-state flow regime to readily provide the average reservoir pressure value.For verification of the effectiveness of the proposed solution, several field and simulated examples were worked out. We found that the average reservoir pressure results obtained from the proposed methodology match very well with those estimated from either conventional techniques or simulations.     

Spatiotemporal receptive field organization in the lateral geniculate nucleus of cats and kittens

We have studied the spatiotemporal receptive-field organization of 144 neurons recorded from the dorsal lateral geniculate nucleus (dLGN) of adult cats and kittens at 4 and 8 wk postnatal. Receptive-field profiles were obtained with the use of a reverse correlation technique, in which we compute the cross-correlation between the action potential train of a neuron and a randomized sequence of long bright and dark bar stimuli that are flashed throughout the receptive field. Spatiotemporal receptive-field profiles of LGN neurons generally exhibit a biphasic temporal response, as well as the classical center-surround spatial organization. For nonlagged cells, the first temporal phase of the response dominates, whereas for lagged neurons, the second temporal phase of the response is typically the largest. This temporal phase difference between lagged and nonlagged cells accounts for their divergent behavior in response to flashed stimuli. Most LGN cells exhibit some degree of space-time inseparability, which means that the receptive field cannot simply be viewed as the product of a spatial waveform and a temporal waveform. In these cases, the response of the surround is typically delayed relative to that of the center, and there is some blending of center and surround during the time course of the response. We demonstrate that a simple extension of the traditional difference-of-Gaussians (DOG) model, in which the surround response is delayed relative to that of the center, accounts nicely for these findings. With regard to development, our analysis shows that spatial and temporal aspects of receptive field structure mature with markedly different time courses. After 4 wk postnatal, there is little change in the spatial organization of LGN receptive fields, with the exception of a weak, but significant, trend for the surround to become smaller and stronger with age. In contrast, there are substantial changes in temporal receptive-field structure after 4 wk postnatal. From 4 to 8 wk postnatal, the shape of the temporal response profile changes, becoming more biphasic, but the latency and duration of the response remain unchanged. From 8 wk postnatal to adulthood, the shape of the temporal profile remains approximately constant, but there is a dramatic decline in both the latency and duration of the response. Comparison of our results with recent data from cortical (area 17) simple cells reveals that the temporal development of LGN cells accounts for a substantial portion of the temporal maturation of simple cells.     

Parametric system identification on logarithmic frequency responsedata

Gradient search methods that fit the parameters of a user-defined transfer function to experimental logarithmic frequency response data are presented. The methods match a model based on physically significant parameters, including natural frequencies of poles and zeros and damping ratios of complex poles and zeros. The algorithms construct and utilize their own analytical gradient descent functions, based on the desired model. One method attempts to fit both log magnitude and phase, while another identifies a minimum phase transfer function model from only log magnitude frequency response data. The log magnitude algorithm is shown to be superior to traditional methods using nonlogarithmic frequency response data, including those used in commercially available frequency response analyzers. The algorithms are shown to perform well, especially for systems with lightly-damped dynamics     

Phloem sap collection from lettuce (Lactuca sativa L.): Methodology and yield

Three methods to collect phloem sap on different lettuce lines were optimized and are described in detail. The success ratio for stylectomy of aphids was over 80% through the combination of a specially designed setup and electrical penetration graphs to monitor phloem sap ingestion. For unknown reasons on some lettuce lines stylets never showed sustained exudation. There were clear differences in stylet exudation between two aphid species on the same lettuce line. Honeydew collection in hexadecane made accurate quantitative analysis possible; samples were large and clean, but biotransformed. The EDTA chelation method produced large samples, but dilution, oxidation, and impurities from the wound surface reduced the reliability.     

Enhanced Relaxometric Properties of MRI “Positive” Contrast Agents Confined in Three‐Dimensional Cubic Mesoporous Silica Nanoparticles

Mesoporous silica nanoparticles (MSNs) are of growing interest for the development of novel probes enabling efficient tracking of cells in vivo using magnetic resonance imaging (MRI). The incorporation of Gd³⁺ paramagnetic ions into highly porous MSNs is a powerful strategy to synthesize “positive” MRI contrast agents for more quantitative T₁‐weighted MR imaging. Within this context, different strategies have been reported to integrate Gd chelates to 2D pore network MSNs. As an alternative, we report on the modulation of the pore network topology through the preparation of a 3D pore network hybrid GdSi_xO_y MSN system. In this study, 2D GdSi_xO_y‐MSNs with similar porosity and particle size were also prepared and the relaxometric performances of both materials, directly compared. Both syntheses lead to water‐dispersible MSNs suspensions (particle size < 200 nm), which were stable for at least 48h. 3D GdSi_xO_y‐MSNs provided a significant increase in ¹H longitudinal relaxivity (18.5 s^?1mM^?1; 4.6 times higher than Gd‐DTPA) and low r₂/r₁ ratios (1.56) compatible with the requirements of “positive” contrast agents for MRI. These results demonstrate the superiority of a 3D pore network to host paramagnetic atoms for MRI signal enhancement using T₁‐weighted imaging. Such an approach minimizes the total amount of paramagnetic element per particle.     

Sol–gel incorporation of silica nanofillers for tuning the anti-corrosion protection of acrylate-based coatings

The aim of the present work is to synthesize through sol–gel approach new hybrid polymeric nanocomposites to be used as coating materials. An acrylic-based polymer was prepared by free-radical copolymerization of two monomers widely used for coatings, namely 2-ethylhexylacrylate (EHA) and glycidyl methacrylate (GMA) bearing epoxy moieties, in which silica nanoparticles were incorporated by in situ acid hydrolysis and subsequent condensation of tetraethoxysilane (TEOS). Glycidoxypropyl trimethoxysilane (GPTS) was used as coupling agent to fine-tune the compatibility between organic and inorganic phases. The morphology, mechanical properties and corrosion resistance of thin films applied on aluminum alloys were optimized by varying the content of silica nanoparticles whose properties were strongly affected by the TEOS/GPTS ratios. Performances of the obtained hybrid materials were scrutinized by atomic force microscopy (AFM), differential scanning calorimetry (DSC), thermal gravimetric analysis (TGA), and electrochemical impedance spectroscopy (EIS). Thus it was evidenced that an optimum amount of silica nanoparticles with a precise morphology and composition in term of TEOS/GPTS ratio is needed to maintain good coating barrier properties. Outstanding anti-corrosion protection was reached by using optimized hybrid films.     

The role of tissue microstructure and water exchange in biophysical modelling of diffusion in white matter

Biophysical models that describe the outcome of white matter diffusion MRI experiments have various degrees of complexity. While the simplest models assume equal-sized and parallel axons, more elaborate ones may include distributions of axon diameters and axonal orientation dispersions. These microstructural features can be inferred from diffusion-weighted signal attenuation curves by solving an inverse problem, validated in several Monte Carlo simulation studies. Model development has been paralleled by microscopy studies of the microstructure of excised and fixed nerves, confirming that axon diameter estimates from diffusion measurements agree with those from microscopy. However, results obtained in vivo are less conclusive. For example, the amount of slowly diffusing water is lower than expected, and the diffusion-encoded signal is apparently insensitive to diffusion time variations, contrary to what may be expected. Recent understandings of the resolution limit in diffusion MRI, the rate of water exchange, and the presence of microscopic axonal undulation and axonal orientation dispersions may, however, explain such apparent contradictions. Knowledge of the effects of biophysical mechanisms on water diffusion in tissue can be used to predict the outcome of diffusion tensor imaging (DTI) and of diffusion kurtosis imaging (DKI) studies. Alterations of DTI or DKI parameters found in studies of pathologies such as ischemic stroke can thus be compared with those predicted by modelling. Observations in agreement with the predictions strengthen the credibility of biophysical models; those in disagreement could provide clues of how to improve them. DKI is particularly suited for this purpose; it is performed using higher b-values than DTI, and thus carries more information about the tissue microstructure. The purpose of this review is to provide an update on the current understanding of how various properties of the tissue microstructure and the rate of water exchange between microenvironments are reflected in diffusion MRI measurements. We focus on the use of biophysical models for extracting tissue-specific parameters from data obtained with single PGSE sequences on clinical MRI scanners, but results obtained with animal MRI scanners are also considered. While modelling of white matter is the central theme, experiments on model systems that highlight important aspects of the biophysical models are also reviewed.     

Non-destructive Flaw Mapping of Steel Surfaces by the Continuous Magnetic Barkhausen Noise Method: Detection of Plastic Deformation

This paper reports the use of a non-destructive scanning technique to identify plastic deformation defects generated in steel. The technique is based on measurement of continuous magnetic Barkhausen noise (CMBN). In the experiments described here, surfaces with plastic deformations produced by crushing stresses in a 1070 steel are scanned, and the influence of probe configuration, coil type, scanner speed, applied magnetic field and the frequency band used for the analysis on the effectiveness of the technique is studied. A moving smoothing window based on a second order statistical moment is used to analyze the time signal. The results show that the method can detect the position of plastic deformation defects and distinguish between their amplitudes.