A three-dimensional high-resolution reservoir model of the Eocene Shahejie Formation in Bohai Bay Basin,integrating stratigraphic forward modeling and geostatistics

Reservoir characterization based on geostatistics method requires well constraints (e.g. seismic data with high quality) to predict inter-well reservoir quality that is conformed to geological laws. Nevertheless, the resolution of seismic data in multiple basins or reservoirs is not high enough to recognize the distribution of different types of sand bodies. In this paper, we propose a new method to improve the precision of reservoir characterization: reservoir modeling with the constrains of sedimentary process model and sedimentary microfacies. We employed stratigraphic forward modeling, a process-based method, to constrain the reservoir modeling in one oil-bearing interval of the third member of Eocene Shahejie Formation in J-Oilfield of Liaoxi Sag, Bohai Bay Basin.We divide reservoir modeling into two orders using different types of constrains. In the first order, we use the simulated shale model from stratigraphic forward model that is corrected by wells data as a 3D trend volume to constrain the reservoir sand-shale modeling. In the second order, different types of sedimentary microfacies in the sandy part of the model are further recognized and simulated within the constrains of sedimentary microfacies maps. Consequently, the porosity, permeability and oil saturation are modeled under the control of precise sedimentary microfacies model. The high-resolution reservoir model shows that the porosity, permeability and oil saturation of distributary channel is generally above 20%, 10md and 50%, respectively, which are much higher than that of other types of sedimentary microfacies. It can be concluded that comparing to other types of sedimentary facies, distributary channel has better physical properties and more oil accumulation in the fan-delta front and therefore is the most favorable zones for petroleum development in the research area.     

Kriging in the Presence of Locally Varying Anisotropy Using Non-Euclidean Distances

A stationary specification of anisotropy does not always capture the complexities of a geologic site. In this situation, the anisotropy can be varied locally. Directions of continuity and the range of the variogram can change depending on location within the domain being modeled. Kriging equations have been developed to use a local anisotropy specification within kriging neighborhoods; however, this approach does not account for variation in anisotropy within the kriging neighborhood. This paper presents an algorithm to determine the optimum path between points that results in the highest covariance in the presence of locally varying anisotropy. Using optimum paths increases covariance, results in lower estimation variance and leads to results that reflect important curvilinear structures. Although CPU intensive, the complex curvilinear structures of the kriged maps are important for process evaluation. Examples highlight the ability of this methodology to reproduce complex features that could not be generated with traditional kriging.     

Catchment scale spatial variability of soil salt content in agricultural oasis,Northwest China

Soil salinization is a serious environmental problem in the world, especially in arid and semi-arid regions. Therefore, estimating spatial variability of soil salinity plays an important role in environmental sciences. Aiming at the problem of soil salinization inside an oasis, a case study was carried out at the Sangong River catchment in Xinjiang province, northwest China. Methods of classical statistics, geostatistics, remote sensing (RS) and geographic information system (GIS) were applied to estimate the spatial variability of soil salt content in the topsoil (0–20 cm) and its relationship with landscape structure at catchment scale. The objective of this study was to provide a scientific basis to understand the heterogeneous of spatial distribution of soil salt content at a large scale. The results revealed that (1) elevation of landform was a key factor for soil salt content’s spatial variability, and soil salt content had a strong spatial autocorrelation, which was mainly induced by structural factors. (2) Mapping of soil salt content by Kriging and comparing it with landscape maps showed that area of soil salinization in old oasis was smaller than that in new oasis, and degree of soil salinization in old oasis was also lower than that in the new one. Among all landscapes, cropland was mostly affected by salinity, with 38.8% of the cropland in new oasis moderately affected by soil salinity, and 8.54% in old oasis.     

Use of USLE/GIS technology integrated with geostatistics to assess soil erosion risk in different land uses of Indagi Mountain Pass—Çankırı, Turkey

The universal soil loss equation (USLE) is an erosion model to estimate average soil loss that would generally result from splash, sheet, and rill erosion from agricultural plots. Recently, use of USLE has been extended as a useful tool predicting soil losses and planning control practices by the effective integration of the GIS-based procedures to estimate the factor values on a grid cell basis. This study was performed for five different lands uses of Indağı Mountain Pass, Cankırı to predict the soil erosion risk by the USLE/GIS methodology for planning conservation measures in the site. Of the USLE factors, rainfall-runoff erosivity factor (USLE-R) and topographic factor (USLE-LS) were greatly involved in GIS. These were surfaced by correcting USLE-R site-specifically using DEM and climatic data and by evaluating USLE-LS by the flow accumulation tool using DEM and watershed delineation tool to consider the topographical and hydrological effects on the soil loss. The study assessed the soil erodibility factor (USLE-K) by randomly sampled field properties by geostatistical analysis. Crop management factor for different land-use/land cover type and land use (USLE-C) was assigned to the numerical values from crop and flora type, canopy and density of five different land uses, which are plantation, recreational land, cropland, forest and grassland, by means of reclassifying digital land use map available for the site. Support practice factor (USLE-P) was taken as a unit assuming no erosion control practices. USLE/GIS technology together with the geostatistics combined these major erosion factors to predict average soil loss per unit area per unit time. Resulting soil loss map revealed that spatial average soil loss in terms of the land uses were 1.99, 1.29, 1.21, 1.20, 0.89 t ha⁻¹ year⁻¹ for the cropland, grassland, recreation, plantation and forest, respectively. Since the rate of soil formation was expected to be so slow in Central Anatolia of Turkey and any soil loss of more than 1 ton ha⁻¹ year⁻¹ over 50–100 years was considered as irreversible for this region, soil erosion in the Indağı Mountain Pass, to the great extent, attained the irreversible state, and these findings should be very useful to take mitigation measures in the site.     

Robust estimation of the variogram: I

It is a matter of common experience that ore values often do not follow the normal (or lognormal) distributions assumed for them, but, instead, follow some other heavier-tailed distribution. In this paper we discuss the robust estimation of the variogram when the distribution is normal-like in the central region but heavier than normal in the tails. It is shown that the use of a fourth-root transformation with or without the use of M-estimation yields stable robust estimates of the variogram.Visiting Scientist, NRIMS, during the period in which this work was carried out.     

Geostatistical method to delineate anomalies of multi-scale spatial variation in hydrogeological changes due to the ChiChi earthquake in the ChouShui River alluvial fan in Taiwan

This study uses Ordinary Kriging (OK), Sequential Gaussian Simulation (SGS) and Simulated Annealing Simulation (SAS) to relocate the completely heterotopic dataset from the locations of the Standardized Satellite Oriented Control Point System (SSOCPS) stations to the Groundwater Monitoring Networks (GMNS) stations and factorial kriging to analyze and map relationships among seven variables, including the hydraulic conductivities of three aquifers, the vertical displacements of the ground and groundwater level changes in the wells of three aquifers, and also to delineate the anomalies of multi-scale spatial variation of hydrogeological properties associated with the ChiChi earthquake, measuring 7.3 on the Richter scale, in the ChouShui River alluvial fan in Taiwan. In this study, the anomalies of spatial variation of hydrogeological properties associated with the earthquake are illustrated at micro, local and regional scales of 9, 12 and 36 km, respectively. In the study area, regionalization components associated with variation at local and regional scales are obtained and mapped by factorial kriging. Factorial Kriging Analysis (FKA) also demonstrated that the main effects of the ChiChi earthquake on the spatial variations of groundwater hydrological changes include porous media compression at micro scale, hydrogeological heterogeneousness of the sediments within the aquifer at local scale and the cyclic loading of deviatoric stress at regional scale. Finally, maps of spatial variations of regional components fully depicted all of the anomalies of spatial variation of hydrogeological changes due to the ChiChi earthquake and can be used to identify, confirm and monitor the hydrogeological properties in this study area.     

Application of geostatistics and GIS technique to characterize spatial variabilities of bioavailable micronutrients in paddy soils

To understand the spatial dependency of bioavailable micronutrients in paddy soils, 134 soil samples were taken from Pinghu County, Zhejiang Province, south-east China to characterize the spatial variabilities of bioavailable Cu, Zn, Fe, and Mn. The geostatistics and geographic information system (GIS) techniques were applied. Bioavailable Zn and Mn were fitted to an exponential model with a range of 4.4 km and 2.97 km, respectively. Bioavailable Fe was fitted to the linear model with the longest range of 23.48 km. Bioavailable Cu did not show any spatial correlation with the fitted pure nugget effect model. Bioavailable Zn and Mn had strong spatial dependence due to the effects of intrinsic factors such as parent material, relief and soil types. Bioavailable Fe had moderate spatial dependence over a long distance. The spatial distribution of the four bioavailable micronutrients were significantly correlated to the soil formation factors. Human activity, such as application of fertilizer and pesticide, emission of waste gas and industrial pollution also had significant effects on the spatial distributions of the bioavailable micronutrients.     

A method for the interpolation of nonnegative functions with an application to contaminant load estimation

The objective of this work is to extend kriging, a geostatistical interpolation method, to honor parameter nonnegativity. The new method uses a prior probability distribution based on reflected Brownian motion that enforces this constraint. The work presented in this paper focuses on interpolation problems where the unknown is a function of a single variable (e.g. time), and is developed both for the case with and without measurement error in the available data. The algorithms presented for conditional simulations are computationally efficient, particularly in the case with no measurement error. We present an application to the interpolation of dissolved arsenic concentration data from the North Fork of the Humboldt River, Nevada.     

Stochastic analysis of the effect of heterogeneity and fractures on radionuclide transport in a low-permeability clay layer

Deep low-permeability clay layers are considered as safe environments for disposal of high-level radioactive waste. In Belgium, the Boom Clay is a candidate host rock for deep geological disposal. In this study, we analyze the effects of fractures and spatially variable hydraulic conductivity on radionuclide migration through the clay. Fracture geometry and properties are simulated with Monte Carlo simulation. The heterogeneity of hydraulic conductivity is simulated by direct sequential co-simulation using measurements of hydraulic conductivity and four types of secondary variables. The hydraulic conductivity and fracture simulations are used as input for a transport model. Radionuclide fluxes computed with this heterogeneous model are compared with fluxes obtained with a homogeneous model. The output fluxes of the heterogeneous model differ at most 8% from the homogeneous model. The main safety function of the Boom Clay is thus not affected by the fractures and the spatial variability of hydraulic conductivity.