DHI evaluation by combining rock physics simulation and statistical techniques for fluid identification of Cambrian-to-Cretaceous clastic reservoirs in Pakistan

The use of seismic direct hydrocarbon indicators is very common in exploration and reservoir development to minimise exploration risk and to optimise the location of production wells. DHIs can be enhanced using AVO methods to calculate seismic attributes that approximate relative elastic properties. In this study, we analyse the sensitivity to pore fluid changes of a range of elastic properties by combining rock physics studies and statistical techniques and determine which provide the best basis for DHIs. Gassmann fluid substitution is applied to the well log data and various elastic properties are evaluated by measuring the degree of separation that they achieve between gas sands and wet sands. The method has been applied successfully to well log data from proven reservoirs in three different siliciclastic environments of Cambrian, Jurassic, and Cretaceous ages. We have quantified the sensitivity of various elastic properties such as acoustic and extended elastic (EEI) impedances, elastic moduli (K _sat and K _sat–μ), lambda–mu–rho method (λρ and μρ), P-to-S-wave velocity ratio (V _P/V _S), and Poisson’s ratio (σ) at fully gas/water saturation scenarios. The results are strongly dependent on the local geological settings and our modeling demonstrates that for Cambrian and Cretaceous reservoirs, K _sat–μ, EEI, V _P/V _S, and σ are more sensitive to pore fluids (gas/water). For the Jurassic reservoir, the sensitivity of all elastic and seismic properties to pore fluid reduces due to high overburden pressure and the resultant low porosity. Fluid indicators are evaluated using two metrics: a fluid indicator coefficient based on a Gaussian model and an overlap coefficient which makes no assumptions about a distribution model. This study will provide a potential way to identify gas sand zones in future exploration.     

Study of Shallow Low-Enthalpy Geothermal Resources Using Integrated Geophysical Methods

The paper is focused on low enthalpy geothermal exploration performed in south Italy and provides an integrated presentation of geological, hydrogeological, and geophysical surveys carried out in the area of municipality of Lecce. Geological and hydrogeological models were performed using the stratigraphical data from 51 wells. A ground-water flow (direction and velocity) model was obtained. Using the same wells data, the ground-water annual temperature was modeled. Furthermore, the ground surface temperature records from ten meteorological stations were studied. This allowed us to obtain a model related to the variations of the temperature at different depths in the subsoil. Integrated geophysical surveys were carried out in order to explore the low-enthalpy geothermal fluids and to evaluate the results of the model. Electrical resistivity tomography (ERT) and self-potential (SP) methods were used. The results obtained upon integrating the geophysical data with the models show a low-enthalpy geothermal resource constituted by a shallow ground-water system.     

ELF polar chorus and magnetic storms

The data of continuous observations of ELF emissions (polar chorus) at South Pole Antarctic observatory (Φ = ?74.02°) for 1997–1999 and during the superstrong magnetic storms of October and November 2003 are analyzed. It has been established that an increase in polar chorus is as a rule observed during the initial and recovery phases of a magnetic storm at positive values of the IMF vertical component (IMF B _z > 0). Under such conditions, South Pole is located in the region of closed field lines. It has been found that the generation of polar chorus at South Pole abruptly ceases during the storm main phase after the IMF B _z southward turning and beginning of an intense substorm in the nightside auroral zone, probably, because this observatory appears in the region of projection of the open magnetosphere due to the expansion of the polar cap.     

Evaluating relationships between soil chemical properties and vegetation cover at different slope aspects in a reclaimed dump

Conducting research about the relationships between soil chemical properties and vegetation coverage at different slope aspects is especially important in reconstructed ecosystems of vulnerable ecological regions. This study was conducted in the first reclaimed dump within the Pingshuo mining area of Shanxi Province, China, to analyze patterns of soil chemical properties (soil organic matter (SOM), soil total nitrogen (STN), soil available phosphorus (SAP) and soil available potassium (SAp) and vegetation coverage (NDVI) and their correlations at different slope aspects. In the reclaimed dump, 26 quadrats were established along four slope aspects (i.e., shady, semi-shady, sunny and semi-sunny slopes). There was no significant difference in SOM or STN among different slope aspects, while SAP differed between shady slopes compared to semi-shady, sunny and semi-sunny slopes; SAP differed significantly between semi-shady and semi-sunny slopes. The NDVI of semi-sunny slopes differed significantly from that of the other three aspects. There was variation in the relationships between NDVI and soil chemical properties, depending on the slope aspects. The logarithm of SOM and NDVI was related linearly on shady and semi-shady slopes, while NDVI was inversely related to the natural logarithm of the logarithm of SOM on sunny and semi-sunny slopes. STN and NDVI had a first-order function relationship on shady and semi-shady slopes, yet a quadratic function relationship on sunny and semi-sunny slopes. The relationships between SAP and NDVI were inverse on all types of slopes. On shady and semi-shady slopes, NDVI had a quadratic relationship with the logarithm of SAp, but it was well fitted by using a cubic function on sunny and semi-sunny slopes. The sensitivity coefficients of soil chemical properties and NDVI were different, and soil chemical properties changed differently depending on changes in NDVI at different slope aspects.     

Future wave climate over the west-European shelf seas

In this paper, we investigate changes in the wave climate of the west-European shelf seas under global warming scenarios. In particular, climate change wind fields corresponding to the present (control) time-slice 1961–2000 and the future (scenario) time-slice 2061–2100 are used to drive a wave generation model to produce equivalent control and scenario wave climate. Yearly and seasonal statistics of the scenario wave climates are compared individually to the corresponding control wave climate to identify relative changes of statistical significance between present and future extreme and prevailing wave heights. Using global, regional and linked global–regional wind forcing over a set of nested computational domains, this paper further demonstrates the sensitivity of the results to the resolution and coverage of the forcing. It suggests that the use of combined forcing from linked global and regional climate models of typical resolution and coverage is a good option for the investigation of relative wave changes in the region of interest of this study. Coarse resolution global forcing alone leads to very similar results over regions that are highly exposed to the Atlantic Ocean. In contrast, fine resolution regional forcing alone is shown to be insufficient for exploring wave climate changes over the western European waters because of its limited coverage. Results obtained with the combined global–regional wind forcing showed some consistency between scenarios. In general, it was shown that mean and extreme wave heights will increase in the future only in winter and only in the southwest of UK and west of France, north of about 44–45° N. Otherwise, wave heights are projected to decrease, especially in summer. Nevertheless, this decrease is dominated by local wind waves whilst swell is found to increase. Only in spring do both swell and local wind waves decrease in average height.     

Remote Targets Recognition Based on Adaptive Weighting Feature Dictionaries and Joint Sparse Representations

With the improvement in resolution, more and more useful information is contained in the space of remote sensing images, which makes the processing of remote sensing data become more complex, and it is easy to cause the curse of dimensionality and the poor recognition effect. In this paper, a remote target recognition approach named AJRC is proposed, which uses joint feature dictionary for sparse representation based on different feature information for adaptive weighting. Firstly, the features of the images are extracted to calculate the contribution weight of each eigenvalue in sparse representation, and each eigenvalue contribution weight is calculated in sparse representation. Through the adaptive method, the contribution ability of each feature value in sparse representation is strengthened, and new atoms are formed to construct feature dictionary, which makes the dictionary more discriminative. Then, the common features of each category image and the private features of a single image are extracted from the feature vector, and a joint dictionary is formed to represent the test image sparse and recognize the output of the target. Aiming at the problem that the target visual contrast difference, the low resolution and the rotation of the target with different angles, the experiment is carried out by different feature extraction methods. At the same time, we use the PCA method to reduce the feature dictionary in order to avoid dimensionality. Experiments show that compared with the existing SRC method and JSM method, this method has better recognition rate.     

Process-based forward numerical ecological modeling for carbonate sedimentary basins

Nowadays, numerical modeling is a common tool used in the study of sedimentary basins, since it allows to quantify the processes simulated and to determine interactions among them. One of such programs is SIMSAFADIM-CLASTIC, a 3D forward-model process-based code to simulate the sedimentation in a marine basin at a geological time scale. It models the fluid flow, siliciclastic transport and sedimentation, and carbonate production. In this article, we present the last improvements in the carbonate production model, in particular about the usage of Generalized Lotka-Volterra equations that include logistic growth and interaction among species. Logistic growth is constrained by environmental parameters such as water depth, energy of the medium, and depositional profile. The environmental parameters are converted to factors and combined into one single environmental value to model the evolution of species. The interaction among species is quantified using the community matrix that captures the beneficial or detrimental effects of the presence of each species on the other. A theoretical example of a carbonate ramp is computed to show the interaction among carbonate and siliciclastic sediment, the effect of environmental parameters to the modeled species associations, and the interaction among these species associations. The distribution of the modeled species associations in the theoretical example presented is compared with the carbonate Oligocene-Miocene Asmari Formation in Iran and the Miocene Ragusa Platform in Italy.     

Heavy metals in mangrove sediments of the central Arabian Gulf shoreline,Saudi Arabia

To assess heavy metals in mangrove swamps of Sehat and Tarut coastal areas along the Arabian Gulf, 18 sediment samples were collected for Al, V, Cr, Mn, Cu, Zn, Cd, Pb, Hg, Sr, As, Fe, Co, and Ni analysis. The results indicated that the distribution of some metals was largely controlled by anthropogenic inputs, while others were of terrigenous origin and most strongly associated with distribution of aluminum and total organic carbon in sediments. Mangrove sediments were extremely severe enriched with Sr (EF?=?67.59) and very severe enriched with V, Hg, Cd, Cu, As (EF?=?44.28, 37.45, 35.77, 25.97, and 11.53, respectively). Average values of Sr, V, Hg, Cd, Cu, Ni, As, and Cr were mostly higher than the ones recorded from the Mediterranean Sea, the Red Sea, the Gulf of Aqaba, the Caspian Sea, the Arabian and Oman gulfs, coast of Tanzania, sediment quality guidelines, and the background shale and the earth crust. Landfilling due to coastal infrastructure development around mangrove forests, oil spills and petrochemical and desalination effluents from Al-Jubail industrial city to the north were the anthropogenic activities that further enhanced heavy metals in the studied mangrove sediments.     

Contribution of a Dense Population of the Brittle Star <Emphasis Type="Italic">Acrocnida brachiata</Emphasis> (Montagu) to the Biogeochemical Fluxes of CO<Subscript>2</Subscript> in a Temperate Coastal Ecosystem

The production of organic matter and calcium carbonate by a dense population of the brittle star Acrocnida brachiata (Echinodermata) was calculated using demographic structure, population density, and relations between the size (disk diameter) and the ash-free dry weight (AFDW) or the calcimass. During a 2-year survey in the Bay of Seine (Eastern English Channel, France), organic production varied from 29 to 50 g_AFDW m⁻² year⁻¹ and CaCO₃ production from 69 to 104 g_CaCO3 m⁻² year⁻¹. Respiration was estimated between 1.7 and 2.0 mol_CO2 m⁻² year⁻¹. Using the molar ratio (ψ) of CO₂ released: CaCO₃ precipitated, this biogenic precipitation of calcium carbonate would result in an additional release between 0.5 and 0.7 mol_CO2 m⁻² year⁻¹ that represented 23% and 26% of total CO₂ fluxes (sum of calcification and respiration). The results of the present study suggest that calcification in temperate shallow environments should be considered as a significant source of CO₂ to seawater and thus a potential source of CO₂ to the atmosphere, emphasizing the important role of the biomineralization (estimated here) and dissolution (endoskeletons of dead individuals) in the carbon budget of temperate coastal ecosystems.