Nonlinear porodynamic analysis by adaptive semi-explicit/explicit time marching formulations

Acta Geotechnica - In this paper, we propose two adaptive semi-explicit/explicit numerical approaches to analyse nonlinear porodynamic models. In this context, simple, stabilised, non-iterative,...     

Biomass allometric equation and expansion factor for a mountain moist evergreen forest in Mozambique

Background

Worldwide, forests are an important carbon sink and thus are key to mitigate the effects of climate change. Mountain moist evergreen forests in Mozambique are threatened by agricultural expansion, uncontrolled logging, and firewood collection, thus compromising their role in carbon sequestration. There is lack of local tools for above-ground biomass (AGB) estimation of mountain moist evergreen forest, hence carbon emissions from deforestation and forest degradation are not adequately known. This study aimed to develop biomass allometric equations (BAE) and biomass expansion factor (BEF) for the estimation of total above-ground carbon stock in mountain moist evergreen forest.

Methods

The destructive method was used, whereby 39 trees were felled and measured for diameter at breast height (DBH), total height and the commercial height. We determined the wood basic density, the total dry weight and merchantable timber volume by Smalian’s formula. Six biomass allometric models were fitted using non-linear least square regression. The BEF was determined based on the relationship between bole stem dry weight and total dry weight of the tree. To estimate the mean AGB of the forest, a forest inventory was conducted using 27 temporary square plots. The applicability of Marzoli’s volume equation was compared with Smalian’s volume equation in order to check whether Marzoli’s volume from national forest inventory can be used to predict AGB using BEF.

Results

The best model was the power model with only DBH as predictor variable, which provided an estimated mean AGB of 291?±?141 Mg ha^?1 (mean?±?95% confidence level). The mean wood basic density of sampled trees was 0.715?±?0.182 g cm^?3. The average BEF was of 2.05?±?0.15 and the estimated mean AGB of 387?±?126 Mg ha^?1. The BAE from miombo woodland within the vicinity of the study area underestimates the AGB for all sampled trees. Chave et al.’s pantropical equation of moist forest did not fit to the Moribane Forest Reserve, while Brown’s equation of moist forest had a good fit to the Moribane Forest Reserve, having generated 1.2% of bias, very close to that generated by the selected model of this study. BEF showed to be reliable when combined with stand mean volume from Marzoli’s National Forestry Inventory equation.

Conclusion

The BAE and the BEF function developed in this study can be used to estimate the AGB of the mountain moist evergreen forests at Moribane Forest Reserve in Mozambique. However, the use of the biomass allometric model should be preferable when DBH information is available.

     

Stochastic Simulation Model for the Spatial Characterization of Lung Cancer Mortality Risk and Study of Environmental Factors

This paper presents a study in which the lung cancer risk in males was characterized based on a simulation model of mortality rates. Block sequential simulation of mortality rates, measured in counties of different sizes, was implemented and applied to a normal grid of continental Portugal with high spatial resolution. The uncertainty in the mortality rate measurements, directly related to differences in the population size of each county, was integrated in a block direct sequential simulation through Poisson kriging of local means and variances. Three age groups were examined: 50–59, 60–69, and 70–79 years. After the continuous geographic patterns of lung cancer risk were obtained, factors potentially associated with the main areas of risk were analyzed for southern Portugal. Thus, a defined class of land use and dry weather events, related to airborne particulate matter, were found to be associated with high-risk areas, resulting in high local spatial correlation patterns in all three age groups.     

Steepness and asymmetry of the largest waves in storm sea states

Several steepness coefficients are proposed to describe the steepness and asymmetry of the largest individual waves in measured records of storm sea states. These coefficients are calculated for data collected in the North Sea and the Atlantic Ocean. Several statistical relationships between the new parameters are identified.     

Geostatistical Seismic Inversion with Direct Sequential Simulation and Co-simulation with Multi-local Distribution Functions

Stochastic sequential simulation is a common modelling technique used in Earth sciences and an integral part of iterative geostatistical seismic inversion methodologies. Traditional stochastic sequential simulation techniques based on bi-point statistics assume, for the entire study area, stationarity of the spatial continuity pattern and a single probability distribution function, as revealed by a single variogram model and inferred from the available experimental data, respectively. In this paper, the traditional direct sequential simulation algorithm is extended to handle non-stationary natural phenomena. The proposed stochastic sequential simulation algorithm can take into consideration multiple regionalized spatial continuity patterns and probability distribution functions, depending on the spatial location of the grid node to be simulated. This work shows the application and discusses the benefits of the proposed stochastic sequential simulation as part of an iterative geostatistical seismic inversion methodology in two distinct geological environments in which non-stationarity behaviour can be assessed by the simultaneous interpretation of the available well-log and seismic reflection data. The results show that the elastic models generated by the proposed stochastic sequential simulation are able to reproduce simultaneously the regional and global variogram models and target distribution functions relative to the average volume of each sub-region. When used as part of a geostatistical seismic inversion procedure, the retrieved inverse models are more geologically realistic, since they incorporate the knowledge of the subsurface geology as provided, for example, by seismic and well-log data interpretation.     

On the focal mechanism of the 26.05.1975 North Atlantic event contribution from tsunami modeling

The 1975 May 26 earthquake, of magnitude Ms = 7.9, occurred in the North Atlantic close to the Azores Archipelago. Its epicentre, as given by US Geological Survey, was 17.5° W, 35.9° N, 200 km south of the Gloria Fault. Several authors determined the focal mechanism as a dextral strike-slip event with no significant dip-slip component, compatible with the relative motion between Eurasia and Nubia plates but away from the presumed plate boundary. The 1975 earthquake generated a tsunami of small amplitude, recorded at the Portuguese tide-gauge network, in Spain and Northern Africa. The peculiar location of the earthquake and tsunami source and the generation of a noticeable tsunami were already discussed by several authors, but up to now, no direct modelling of the tsunami generation and propagation was made to judge the set of source solutions obtained by seismological analysis. In this paper, we present tsunami simulations, backward ray tracing and forward non-linear shallow water simulations using data from Iberia and Azores and Northern Africa. We show that a good fit between observed data and synthetic waveforms can be obtained with a focal mechanism with no significant dip-slip component, favouring its interpretation as almost pure dextral strike-slip event located in an old fracture zone south of Gloria Fault.     

Experimental evidence of the transition between power law models in the high frequency range of the gravity wave spectrum

The existence of a transition in the slope of the wind-generated gravity wave spectrum from a f⁻⁴ to a f⁻⁵ power law, at a given frequency in the high frequency range, is examined. Evidence of its existence and of the non-uniqueness of the wave spectrum slope in the equilibrium range is presented. Furthermore, it is demonstrated that the statistical variability of the spectral estimates makes it difficult to obtain reliable results from limited sets of finite length wave records.     

Geostatistical seismic Amplitude‐versus‐angle inversion

Seismic inversion plays an important role in reservoir modelling and characterisation due to its potential for assessing the spatial distribution of the sub‐surface petro‐elastic properties. Seismic amplitude‐versus‐angle inversion methodologies allow to retrieve P‐wave and S‐wave velocities and density individually allowing a better characterisation of existing litho‐fluid facies. We present an iterative geostatistical seismic amplitude‐versus‐angle inversion algorithm that inverts pre‐stack seismic data, sorted by angle gather, directly for: density; P‐wave; and S‐wave velocity models. The proposed iterative geostatistical inverse procedure is based on the use of stochastic sequential simulation and co‐simulation algorithms as the perturbation technique of the model parametre space; and the use of a genetic algorithm as a global optimiser to make the simulated elastic models converge from iteration to iteration. All the elastic models simulated during the iterative procedure honour the marginal prior distributions of P‐wave velocity, S‐wave velocity and density estimated from the available well‐log data, and the corresponding joint distributions between density versus P‐wave velocity and P‐wave versus S‐wave velocity. We successfully tested and implemented the proposed inversion procedure on a pre‐stack synthetic dataset, built from a real reservoir, and on a real pre‐stack seismic dataset acquired over a deep‐water gas reservoir. In both cases the results show a good convergence between real and synthetic seismic and reliable high‐resolution elastic sub‐surface Earth models.