Reconstruction of the diagenesis of the fluvial-lacustrine- deltaic sandstones and its influence on the reservoir quality evolution-- Evidence from Jurassic and Triassic sandstones, Yanchang Oil Field, Ordos Basin

The reservoir quality of Jurassic and Triassic fluvial and lacustrine-deltaic sandstones of the Yanchang Oil Field in the Ordos Basin is strongly influenced by the burial history and facies-related diagenetic events. The fluvial sandstones have a higher average porosity (14.8%) and a higher permeability (12.7×10?3 ?m2) than those of the deltaic sandstones (9.8% and 5.8 ×10?3 ?m2, respectively). The burial compaction, which resulted in 15% and 20% porosity loss for Jurassic and Triassic sandstones, respectively, is the main factor causing the loss of porosity both for the Jurassic and Triassic sandstones. Among the cements, carbonate is the main one that reduced the reservoir quality of the sandstones. The organic acidic fluid derived from organic matter in the source rocks, the inorganic fluid from rock-water reaction during the late diagenesis, and meteoric waters during the epidiagenesis resulted in the formation of dissolution porosity, which is the main reason for the enhancement of reservoir-quality.     

Causes of Geochemical Diversity of Carbon Dioxide Water in Crystalline Rock Masses

The problem of the diversity of the geochemical types of carbon dioxide waters (CDW) in petrografically and mineralogically uniform crystalline rock masses is solved with allowance made for the effect of different boundary conditions (physicochemical parameters) on the geochemical effect of interaction in the rock–water system. The formation of the entire geochemical spectrum of CDW in crystalline rock masses is shown to be explicable on the basis of a model of interaction in granite–water systems at different mass ratios of reacting rock (S) and water (L), different temperatures T, and equilibrium concentrations of dissolved CO₂ (P _CO2).     

Snow measurement techniques for land-surface-atmosphere exchange studies in boreal landscapes

Summary  Snow has been studied widely in hydrology for many decades whereas recent meteorological interest in snow is caused by increased emphasis on high latitudes and wintertime in climate-change research as well as by the need to improve weather-forecast models during these conditions. Ground-based measurements of snow properties are needed both to improve understanding of surface-atmosphere exchange processes and to provide ground truth to new remote-sensing algorithms. This justifies a review of techniques to measure snow in combination with establishment of criteria for the suitability of the methods for process studies. This review assesses the state-of-art in ground-based snow-measurement techniques in the end of the 1990s in view of their accuracy, time resolution, possibility to automate, practicality and suitability in different terrain. Methods for snow-pack water equivalent, depth, density, growth, quality, liquid-water content and water leaving the snow pack are reviewed. Synoptic snow measurements in Fennoscandian countries are widely varying and there is no single standard on which process-related studies can build. A long-term, continuous monitoring of mass and energy properties of a snow cover requires a combination of point-measurement techniques. Areally representative values of snow properties can be achieved through a combination of automatically collected point data with repeated manual, areally covering measurements, remote-sensing data and digital elevation models, preferably in a GIS framework. Received August 27, 1999     

Diurnal variation of deep cloud systems over the Indian region using INSAT-1B pixel data

Summary Among the various time scales of deep clouds, diurnal variation is found to be prominent over the tropics. The present study examines the diurnal variation in the number and area cover associated with the cloud systems over the tropical Indian region using INSAT-1B pixel data. Three periods, namely, April–May 1988, July–August 1988, and January–February 1989 are considered. The dependence of diurnal characteristics on the temperature threshold, life duration and size of cloud systems, and land-sea contrast has been explored. The diurnal characteristics of cloud systems living for more than a day have been studied for the first time. It is shown that cloud systems exhibit strong diurnal dependence at the coldest temperature threshold used (201 K). Also, the diurnal variation is more for larger cloud systems and for longer living systems. In general, more deep cloud activity is found from the satellite data during the pre-dawn and early morning hours. Precipitation is enhanced during morning to early noon hours. Further, using data from a recent field experiment, clear evidence of diurnal variation in precipitation over the Bay of Bengal is also presented. Received March 20, 2000/Revised October 3, 2000     

Measures of Parameter Uncertainty in Geostatistical Estimation and Geostatistical Optimal Design

Studies of site exploration, data assimilation, or geostatistical inversion measure parameter uncertainty in order to assess the optimality of a suggested scheme. This study reviews and discusses measures for parameter uncertainty in spatial estimation. Most measures originate from alphabetic criteria in optimal design and were transferred to geostatistical estimation. Further rather intuitive measures can be found in the geostatistical literature, and some new measures will be suggested in this study. It is shown how these measures relate to the optimality alphabet and to relative entropy. Issues of physical and statistical significance are addressed whenever they arise. Computational feasibility and efficient ways to evaluate the above measures are discussed in this paper, and an illustrative synthetic case study is provided. A major conclusion is that the mean estimation variance and the averaged conditional integral scale are a powerful duo for characterizing conditional parameter uncertainty, with direct correspondence to the well-understood optimality alphabet. This study is based on cokriging generalized to uncertain mean and trends because it is the most general representative of linear spatial estimation within the Bayesian framework. Generalization to kriging and quasi-linear schemes is straightforward. Options for application to non-Gaussian and non-linear problems are discussed.