ALBERT

Description: The sandy-clayey hydrocarbon reservoirs of the Upper Paleocene and Lower Eocene located to the north of Veracruz State, Mexico, present highly complex geological and petrophysical characteristics. These reservoirs, which consist of sandstone and shale bodies within a depth interval ranging from 500 to 2000 m, were characterized statistically by means of fractal modeling and geostatistical tools. For 14 wells within an area of study of approximately 6 km2, various geophysical well logs were initially edited and further analyzed to establish a correlation between logs and core data. The fractal modeling based on the R/S (rescaled range) methodology and the interpolation method by successive random additions were used to generate pseudo-well logs between observed wells. The application of geostatistical tools, sequential Gaussian simulation and exponential model variograms contributed to estimate the spatial distribution of petrophysical properties such as effective porosity (PHIE), permeability (K) and shale volume (VSH). From the analysis and correlation of the information generated in the present study, it can be said, from a general point of view, that the results not only are correlated with already reported information but also provide significant characterization elements that would be hardly obtained by means of conventional techniques.

Description: In this paper, we develop an estimator for the vertical flux of horizontal momentum with arbitrary beam pointing, applicable to the case of arbitrary but fixed beam pointing with systems such as the Poker Flat Incoherent Scatter Radar (PFISR). This method uses information from all available beams to resolve the variances of the wind field in addition to the vertical flux of both meridional and zonal momentum, targeted for high-frequency wave motions. The estimator utilises the full covariance of the distributed measurements, which provides a significant reduction in errors over the direct extension of previously developed techniques and allows for the calculation of an error covariance matrix of the estimated quantities. We find that for the PFISR experiment, we can construct an unbiased and robust estimator of the momentum flux if sufficient and proper beam orientations are chosen, which can in the future be optimized for the expected frequency distribution of momentum-containing scales. However, there is a potential trade-off between biases and standard errors introduced with the new approach, which must be taken into account when assessing the momentum fluxes. We apply the estimator to PFISR measurements on 23 April 2008 and 21 December 2007, from 60–85 km altitude, and show expected results as compared to mean winds and in relation to the measured vertical velocity variances.

Description: The performance of the Hakamada Akasofu-Fry, version 2 (HAFv.2) numerical model, which provides predictions of solar shock arrival times at Earth, was subjected to a statistical study to investigate those solar/interplanetary circumstances under which the model performed well/poorly during key phases (rise/maximum/decay) of solar cycle 23. In addition to analyzing elements of the overall data set (584 selected events) associated with particular cycle phases, subsets were formed such that those events making up a particular sub-set showed common characteristics. The statistical significance of the results obtained using the various sets/subsets was generally very low and these results were not significant as compared with the hit by chance rate (50%). This implies a low level of confidence in the predictions of the model with no compelling result encouraging its use. However, the data suggested that the success rates of HAFv.2 were higher when the background solar wind speed at the time of shock initiation was relatively fast. Thus, in scenarios where the background solar wind speed is elevated and the calculated success rate significantly exceeds the rate by chance, the forecasts could provide potential value to the customer. With the composite statistics available for solar cycle 23, the calculated success rate at high solar wind speed, although clearly above 50%, was indicative rather than conclusive. The RMS error estimated for shock arrival times for every cycle phase and for the composite sample was in each case significantly better than would be expected for a random data set. Also, the parameter "Probability of Detection, yes" (PODy) which presents the Proportion of Yes observations that were correctly forecast (i.e. the ratio between the shocks correctly predicted and all the shocks observed), yielded values for the rise/maximum/decay phases of the cycle and using the composite sample of 0.85, 0.64, 0.79 and 0.77, respectively. The statistical results obtained through detailed analysis of the available data provided insights into how changing circumstances on the Sun and in interplanetary space can affect the performance of the model. Since shock arrival predictions are widely utilized in making commercially significant decisions re. protecting space assets, the present detailed archival studies can be useful in future operational decision making during solar cycle 24. It would be of added value in this context to use Briggs-Rupert methodology to estimate the cost to an operator of acting on an incorrect forecast.

Description: The Kelvin-Helmholtz Instability (KHI) can drive waves at the magnetopause. These waves can grow to form rolled-up vortices and facilitate transfer of plasma into the magnetosphere. To investigate the persistence and frequency of such waves at the magnetopause we have carried out a survey of all Double Star 1 magnetopause crossings, using a combination of ion and magnetic field measurements. Using criteria originally used in a Geotail study made by Hasegawa et al. (2006) (forthwith referred to as H2006), 17 candidate events were identified from the entire TC-1 mission (covering ~623 orbits where the magnetopause was sampled), a majority of which were on the dayside of the terminator. The relationship between density and shear velocity was then investigated, to identify the predicted signature of a rolled up vortex from H2006 and all 17 events exhibited some level of rolled up behavior. The location of the events had a clear dawn-dusk asymmetry, with 12 (71%) on the post noon, dusk flank suggesting preferential growth in this region.

Description: We investigate the global response of the geospace plasma environment to an interplanetary (IP) shock at ~02:24 UT on 28 May 2008 from multiple THEMIS spacecraft observations in the magnetosheath (THEMIS B and C), the mid-afternoon magnetosphere (THEMIS A), and the dusk magnetosphere (THEMIS D and E). The interaction of the transmitted IP shock with the magnetosphere has global effects. Consequently, it can affect geospace plasma significantly. After interacting with the bow shock, the IP shock transmitted a fast shock and a discontinuity which propagated through the magnetosheath toward the Earth at speeds of 301 km s−1 and 137 km s−1, respectively. THEMIS A observations indicate that the IP shock changed the properties of a plasmaspheric plume significantly. The plasmaspheric plume density increased rapidly from 10 to 100 cm−3 in 4 min and the ion distribution changed from an isotropic to a strongly anisotropic distribution. Electromagnetic ion cyclotron (EMIC) waves observed by THEMIS A are most likely excited by the anisotropic ion distributions caused by the IP shock impact. THEMIS A, but not D or E, observed a plasmaspheric plume in the dayside magnetosphere. Multiple spacecraft observations indicate that the dawn-side edge of the plasmaspheric plume was located between THEMIS A and D (or E).

Description: Fusion welding is common in steel pipeline construction in fossil-fuel power generation plants. Steel pipes in service carry steam at high temperature and pressure, undergoing creep during years of service; their integrity is critical for the safe operation of a plant. The high-grade martensitic P92 steel is suitable for plant pipes for its enhanced creep strength. P92 steel pipes are usually joined together with a similar weld metal. Martensitic pipes are sometimes joined to austenitic steel pipes using nickel based weld consumables. Welding involves severe thermal cycles, inducing residual stresses in the welded structure, which, without post weld heat treatment (PWHT), can be detrimental to the integrity of the pipes. Welding residual stresses can be numerically simulated by applying the finite element (FE) method in Abaqus. The simulation consists of a thermal analysis, determining the temperature history of the FE model, followed by a sequentially-coupled structural analysis, predicting residual stresses from the temperature history. In this paper, the FE thermal analysis of the arc welding of a typical P92 pipe is presented. The two parts of the P92 steel pipe are joined together using a dissimilar material, made of Inconel weld consumables, producing a multi-pass butt weld from 36 circumferential weld beads. Following the generation of the FE model, the FE mesh is controlled using Model Change in Abaqus to activate the weld elements for each bead at a time corresponding to weld deposition. The thermal analysis is simulated by applying a distributed heat flux to the model, the accuracy of which is judged by considering the fusion zones in both the parent pipe as well as the deposited weld metal. For realistic fusion zones, the heat flux must be prescribed in the deposited weld pass and also the adjacent pipe elements. The FE thermal results are validated by comparing experimental temperatures measured by five thermocouples on the pipe outside surface with the FE temperature history at corresponding nodal points.

Description: The multifractal properties of the daily solar X-ray brightness, Xl and Xs, during the period from 1 January 1986 to 31 December 2007 which includes two solar cycles are examined using the universal multifractal approach and multifractal detrended fluctuation analysis. Then we convert these time series into networks using the horizontal visibility graph technique. Multifractal analysis of the resulting networks is performed using an algorithm proposed by us. The results from the multifractal analysis show that multifractality exists in both raw daily time series of X-ray brightness and their horizontal visibility graphs. It is also found that the empirical K(q) curves of raw time series can be fitted by the universal multifractal model. The numerical results on the raw data show that the Solar Cycle 23 is weaker than the Solar Cycle 22 in multifractality. The values of h(2) from multifractal detrended fluctuation analysis for these time series indicate that they are stationary and persistent, and the correlations in the time series of Solar Cycle 23 are stronger than those for Solar Cycle 22. Furthermore, the multifractal scaling for the networks of the time series can reflect some properties which cannot be picked up by using the same analysis on the original time series. This suggests a potentially useful method to explore geophysical data.

Description: Despite the tremendous progress that has been made in data assimilation (DA) methodology, observing systems that reduce observation errors, and model improvements that reduce background errors, the analyses produced by the best available DA systems are still different from the truth. Analysis error and error covariance are important since they describe the accuracy of the analyses, and are directly related to the future forecast errors, i.e., the forecast quality. In addition, analysis error covariance is critically important in building an efficient ensemble forecast system (EFS). Estimating analysis error covariance in an ensemble-based Kalman filter DA is straightforward, but it is challenging in variational DA systems, which have been in operation at most NWP (Numerical Weather Prediction) centers. In this study, we use the Lanczos method in the NCEP (the National Centers for Environmental Prediction) Gridpoint Statistical Interpolation (GSI) DA system to look into other important aspects and properties of this method that were not exploited before. We apply this method to estimate the observation impact signals (OIS), which are directly related to the analysis error variances. It is found that the smallest eigenvalue of the transformed Hessian matrix converges to one as the number of minimization iterations increases. When more observations are assimilated, the convergence becomes slower and more eigenvectors are needed to retrieve the observation impacts. It is also found that the OIS over data-rich regions can be represented by the eigenvectors with dominant eigenvalues. Since only a limited number of eigenvectors can be computed due to computational expense, the OIS is severely underestimated, and the analysis error variance is consequently overestimated. It is found that the mean OIS values for temperature and wind components at typical model levels are increased by about 1.5 times when the number of eigenvectors is doubled. We have proposed four different calibration schemes to compensate for the missing trailing eigenvectors. Results show that the method with calibration for a small number of eigenvectors cannot pick up the observation impacts over the regions with fewer observations as well as a benchmark with a large number of eigenvectors, but proper calibrations do enhance and improve the impact signals over regions with more data. When compared with the observation locations, the method generally captures the OIS over regions with more observation data, including satellite data over the southern oceans. Over the tropics, some observation impacts may be missed due to the smaller background errors specified in the GSI, which is not related to the method. It is found that a large number of eigenvectors are needed to retrieve impact signals that resemble the banded structures from satellite observations, particularly over the tropics. Another benefit from the Lanczos method is that the dominant eigenvectors can be used in preconditioning the conjugate gradient algorithm in the GSI to speed up the convergence.

Description: We investigate the time intermittency of turbulent transport associated with the birth-death of self-organized coherent structures in the atmospheric boundary layer. We apply a threshold analysis on the increments of turbulent fluctuations to extract sequences of rapid acceleration events, which is a marker of the transition between self-organized structures. The inter-event time distributions show a power-law decay ψ(τ) ~ 1/τμ, with a strong dependence of the power-law index μ on the threshold. A recently developed method based on the application of event-driven walking rules to generate different diffusion processes is applied to the experimental event sequences. At variance with the power-law index μ estimated from the inter-event time distributions, the diffusion scaling H, defined by ⟨ X2⟩ ~ t2H, is independent from the threshold. From the analysis of the diffusion scaling it can also be inferred the presence of different kind of events, i.e. genuinely transition events and spurious events, which all contribute to the diffusion process but over different time scales. The great advantage of event-driven diffusion lies in the ability of separating different regimes of the scaling H. In fact, the greatest H, corresponding to the most anomalous diffusion process, emerges in the long time range, whereas the smallest H can be seen in the short time range if the time resolution of the data is sufficiently accurate. The estimated diffusion scaling is also robust under the change of the definition of turbulent fluctuations and, under the assumption of statistically independent events, it corresponds to a self-similar point process with a well-defined power-law index μD ~ 2.1, where D denotes that μD is derived from the diffusion scaling. We argue that this renewal point process can be associated to birth and death of coherent structures and to turbulent transport near the ground, where the contribution of turbulent coherent structures becomes dominant.

Description: Geophysical processes are typically variable over huge ranges of space-time scales. This has lead to the development of many techniques for decomposing series and fields into fluctuations Δv at well-defined scales. Classically, one defines fluctuations as differences: (Δvdiff = v(x+Δx)-v(x) and this is adequate for many applications (Δx is the "lag"). However, if over a range one has scaling Δv ∝ ΔxH, these difference fluctuations are only adequate when 0 〈 H 〈 1. Hence, there is the need for other types of fluctuations. In particular, atmospheric processes in the "macroweather" range ≈10 days to 10–30 yr generally have −1 〈 H 〈 0, so that a definition valid over the range −1 〈 H 〈 1 would be very useful for atmospheric applications. A general framework for defining fluctuations is wavelets. However, the generality of wavelets often leads to fairly arbitrary choices of "mother wavelet" and the resulting wavelet coefficients may be difficult to interpret. In this paper we argue that a good choice is provided by the (historically) first wavelet, the Haar wavelet (Haar, 1910), which is easy to interpret and – if needed – to generalize, yet has rarely been used in geophysics. It is also easy to implement numerically: the Haar fluctuation (ΔvHaar at lag Δx is simply equal to the difference of the mean from x to x+ Δx/2 and from x+Δx/2 to x+Δx. Indeed, we shall see that the interest of the Haar wavelet is this relation to the integrated process rather than its wavelet nature per se. Using numerical multifractal simulations, we show that it is quite accurate, and we compare and contrast it with another similar technique, detrended fluctuation analysis. We find that, for estimating scaling exponents, the two methods are very similar, yet Haar-based methods have the advantage of being numerically faster, theoretically simpler and physically easier to interpret.