应用随机反演改善储层表征的过程

为了适当地完成储层表征的过程,一个有效的方法就是把现场所有可以利用的信息融合成一个一致性的模型。在实际生产中实现这种融合并非简单的任务,所以有必要运用如地震反演等特殊方法。应用地震反演可以使测井数据和地震数据的有效结合成为可能,并且可以得到一个模型,该模型在预测过程中可通过流体数字模拟来验证。地震反演可以通过多种方法进行,主要分为两大类:一类是确定性方法(其代表是回归反演和约束稀疏脉冲反演),另一类是随机方法(其代表是地质统计学反演)。在本次研究中,通过随机反演结果和确定性反演结果的对比展示了随机反演是如何改进储层表征过程的。事实上,随机反演,可以运用较高的采样率(和储层模型的网格大小相接近),来产生一个更可靠的模型。随机反演的另一个好处就是随机方法可产生一些基本的统计测量值来改进解释精度,并且在储层表征过程中能生成大量的实现,从而使储层模型的不确定性研究成为可能。     

Groundwater Quality: Analysis of Its Temporal and Spatial Variability in a Karst Aquifer

This study develops an approach based on hierarchical cluster analysis for investigating the spatial and temporal variation of water quality governing processes. The water quality data used in this study were collected in the karst aquifer of Yucatan, Mexico, the only source of drinking water for a population of nearly two million people. Hierarchical cluster analysis was applied to the quality data of all the sampling periods lumped together. This was motivated by the observation that, if water quality does not vary significantly in time, two samples from the same sampling site will belong to the same cluster. The resulting distribution maps of clusters and box‐plots of the major chemical components reveal the spatial and temporal variability of groundwater quality. Principal component analysis was used to verify the results of cluster analysis and to derive the variables that explained most of the variation of the groundwater quality data. Results of this work increase the knowledge about how precipitation and human contamination impact groundwater quality in Yucatan. Spatial variability of groundwater quality in the study area is caused by: a) seawater intrusion and groundwater rich in sulfates at the west and in the coast, b) water rock interactions and the average annual precipitation at the middle and east zones respectively, and c) human contamination present in two localized zones. Changes in the amount and distribution of precipitation cause temporal variation by diluting groundwater in the aquifer. This approach allows to analyze the variation of groundwater quality controlling processes efficiently and simultaneously.     

Fluorescence as a Tool for Tracing the Organic Contamination from Pulp Mill Effluents in Surface Waters

Three‐dimensional fluorescence spectra of water samples from an eucalyptus bleached kraft pulp mill and from a river, upstream and downstream of the discharge of the effluent, revealed the existence of a peak at δ_exc = 280 nm and δ_em = 340 nm Δδ = 60 nm), characteristic of effluentπs organic matter. Humic substances were isolated from the effluent by sequential adsorption onto resins XAD‐8 and XAD‐4 in series. Their synchronous fluorescence spectra with Δδ = 60 nm do also exhibit an intense signal at δ_exc = 280 nm (≈ 300 nm in the humic acid fraction). The peak is absent in the spectra of humic substances isolated from a non‐polluted site of the river, but it is clearly seen in the spectra of the humic substances from a site downstream of the discharge of the effluent. Synchronous fluorescence spectra (Δδ = 60 nm) of water samples from the river and its lagoon were recorded and revealed to be an easy and fast way of tracing the organic contamination from the effluent.     

Differences between Humic Substances from Riverine,Estuarine, and Marine Environments Observed by Fluorescence Spectroscopy

Sixteen samples of fulvic acids and XAD‐4 fractions of riverine, estuarine, coastal, and open ocean origin have been studied by emission and synchronous molecular fluorescence spectroscopy. Certain features of the molecular fluorescence are related to the nature, the content, and the origin of those aquatic humic substances (HS). Riverine HS appear several times richer in fluorophores than marine HS, which can be well observed by emission fluorescence spectroscopy. Synchronous‐scan spectra of fulvic acids and of XAD‐4 fractions from the aquatic environments studied, emphasized the quality differences of their fluorophores. These features are useful as tracers of humic substances related with their natural environment source or even with their anthropogenic origin.     

Fusing remote sensing with sparse demographic data for synthetic population generation: an algorithm and application to rural Afghanistan

We develop a new algorithm for population synthesis that fuses remote-sensing data with partial and sparse demographic surveys. The algorithm addresses non-binding constraints and complex sampling designs by translating population synthesis into a computationally efficient procedure for constrained network growth. As a case, we synthesize the rural population of Afghanistan, validate the algorithm with in-sample and out-of-sample tests, examine the variability of algorithm outputs over k-nearest neighbor manifolds, and show the responsiveness of our algorithm to additional data as a constraint on marginal population counts.     

From Forests and Fields to Coffee and Back Again: Historic Transformations of a Traditional Coffee Agroecosystem in Oaxaca,Mexico

Studies of coffee agroecosystems have focused on their role in providing habitat for biodiversity across a range of management intensities. These studies have not taken into account the temporal and spatial transformations in coffee landscapes and their impacts on structural heterogeneity and biodiversity, nor systematically linked these transformations to farmer management responses to price and policy shocks. We utilize a coupled natural–human system framework to examine the historical transformations of the coffee landscape in a matrix of community-protected forests in a coffee-growing community in Oaxaca, Mexico, and study how those transformations impact tree biodiversity across a range of management options, including formerly certified organic and conventional coffee, abandonment, and conversion. The coffee landscape has historically transitioned from forests and fields (1950s–1960s) to one dominated by coffee (1970s–1980s) to a richly mosaic and biodiverse landscape (1990–2010) resulting from 43% recent abandonment and conversion of coffee back to forest and fields.     

Global and hemispheric temperatures revisited

To characterize observed global and hemispheric temperatures, previous studies have proposed two types of data-generating processes, namely, random walk and trend-stationary, offering contrasting views regarding how the climate system works. Here we present an analysis of the time series properties of global and hemispheric temperatures using modern econometric techniques. Results show that: The temperature series can be better described as trend-stationary processes with a one-time permanent shock which cannot be interpreted as part of the natural variability; climate change has affected the mean of the processes but not their variability; it has manifested in two stages in global and Northern Hemisphere temperatures during the last century, while a second stage is yet possible in the Southern Hemisphere; in terms of Article 2 of the Framework Convention on Climate Change it can be argued that significant (dangerous) anthropogenic interference with the climate system has already occurred.