GEOLOGICAL MODEL EVALUATION THROUGH WELL TEST SIMULATION: A CASE STUDY FROM THE WYTCH FARM OILFIELD, SOUTHERN ENGLAND

This paper presents an approach to the evaluation of reservoir models using transient pressure data. Braided fluvial sandstones exposed in cliffs in SW England were studied as the surface equivalent of the Triassic Sherwood Sandstone, a reservoir unit at the nearby Wytch Farm oilfield. Three reservoir models were built; each used a different modelling approach ranging in complexity from stochastic pixel‐based modelling using commercially available software, to a spreadsheet random number generator. In order to test these models, numerical well test simulations were conducted using sector models extracted from the geological models constructed. The simulation results were then evaluated against the actual well test data in order to find the model which best represented the field geology. Two wells at Wytch Farm field were studied. The results suggested that for one of the sampled wells, the model built using the spreadsheet random number generator gave the best match to the well test data. In the well, the permeability from the test interpretation matched the geometric average permeability. This average is the “correct” upscaled permeability for a random system, and this was consistent with the random nature of the geological model. For the second well investigated, a more complex “channel object” model appeared to fit the dynamic data better. All the models were built with stationary properties. However, the well test data suggested that some parts of the field have different statistical properties and hence show non‐stationarity. These differences would have to be built into the model representing the local geology. This study presents a workflow that is not yet considered standard in the oil industry, and the use of dynamic data to evaluate geological models requires further development. The study highlights the fact that the comparison or matching of results from reservoir models and well‐test analyses is not always straightforward in that different models may match different wells. The study emphasises the need for integrated analyses of geological and engineering data. The methods and procedures presented are intended to form a feedback loop which can be used to evaluate the representivity of a geological model.     

Upscaling hydraulic conductivity: theory and examples from geohydrological studies

This paper presents an overview of the theory of upscaling hydraulic conductivity and describes two case studies in which some of this theory has been applied. The representative hydraulic conductivity of a numerical model block (block conductivity for short) is defined in terms of smaller scale hydraulic conductivities. Also, using elementary examples, some general properties of block conductivities are given. Analytical solutions for the block conductivity are presented that were derived by various authors for uniform flow conditions both in a deterministic and in a stochastic setting. Some results of the hydraulic upscaling theory are illustrated by two case studies from the Netherlands. The first case study deals with deriving the representative hydraulic conductivity tensor of a clay layer. Upscaling results are compared with traditional harmonic averaging. In the second case study the upscaling is used to derive the three-dimensional distribution of block conductivities for a numerical groundwater model of a confining layer of complex deposits. Here stochastic upscaling is used together with a geostatistical simulation approach. The simulated block conductivities are used in a numerical groundwater model and results are compared with pumping tests. When the upscaling is ignored groundwater flow through the deposits is predicted wrongly.     

升尺度在求解等价渗透率中的研究现状及发展趋势

为进一步了解升尺度方法在储层研究中的应用。介绍了单相流中的解析方法、求解压力方法、重正化方法、有效介质方法、流线方法以及两相流中的准静态方法和动态方法等升尺度方法的基本原理及求解思路，结合实际应用分析了不同升尺度方法的适用条件和优缺点。阐述了升尺度研究的发展趋势。综合分析认为，升尺度方法对地质建模和油藏数值模拟具有指导作用。     

Geometric characterization, hydraulic behavior and upscaling of 3D fissured geologic media

In this article, we present numerical modeling and upscaling procedures for highly fissured and discontinuous geologic media, such as ‘karsts’. In particular, we propose a geomorphological generation model, and we address the ‘upscaling’ problem for flow in a highly fissured porous medium (‘what is the macroscale hydraulic behavior of the fissured porous medium?’). The morphological model is partly Boolean, based on statistical distributions of discrete objects (voids), combined with a (random) continuum representation for the underlying porous matrix. Various methods for constraining these two types of media are discussed (self-consistent thresholding; genetic dissolution). Hydraulic simulations are then conducted with the 3D finite volume code BIGFLOW, for the case of 3D composite media with constant matrix and high ‘fissure/matrix’ permeability contrast. The hydrodynamic equations are based on either Darcy’s linear head loss law, or on a linear/quadratic combination of Darcy and Ward–Forchheimer quadratic law (inertial effects). The numerical experiments are conducted for saturated steady flow under permeametric boundary conditions. They are used to analyze the equivalent macroscale behavior of fissured media, as well as quasi-percolation effects, in comparison with analytical results and bounds (Darcian case, low Reynolds). In addition, at moderate to large Reynolds numbers, the macroscale effects of non-Darcian (inertial) head losses are also analyzed.     

Calibration and validation of DEM-FEM model parameters using upscaled particles based on physical experiments and simulations

The real sand is usually idealized by using upscaled particles, due to the large number of particles of tire-sand interaction. This study aims to determine a unique and complete set of DEM-FEM model parameters to improve numerical accuracy of tire-sand interaction after particles idealization. To achieve this aim, a novel method based on experimental design is proposed to calibrate the DEM-FEM model parameters by a series of single-factor numerical calibration tests. Initially, the interaction properties such as equivalent friction coefficients of particle-particle, particle-soil bin and particle-tire are determined successively by comparing experimental test with numerical simulation using the angle of repose as a bulk response. The material parameters of particles are then obtained by modified iteratively to match the stress-strain behavior of the granular assembly in triaxial test. After that, the calibrated parameter set is used to investigate the interaction mechanisms between the off-road tire and the granular terrain. Finally, the simulation results are qualitatively in agreement with the soil bin experiments, which verifies the effectiveness of the calibrated parameter set for the tractive performance analysis of tire-sand interaction.     

Upscaling a simple erosion model from small areas to a large region

Upscaling from a catchment scale to a regional scale is generally rendered difficult by the lack of relevant and precise data at the larger scale. In this case, a winter rill erosion hazard map was produced for the Nord-Pas-de-Calais region using a linear regression erosion model originally designed for the catchment scale. Upscaling entailed adapting and applying the model at the county scale for all of the counties within the region. In upscaling the model, the difficulties associated with the nature of the data were dealt with in three stages: (1) the modification of the model for the county scale as a function of the nature of the data available, (2) an analysis of the influence of the spatial distribution of the data, (3) an analysis of the effect of the loss in precision of the data on the model output. Reference areas were used to verify the accuracy of the upscaling process before applying it to all of the counties in the region. In this case, the most significant limitation was the spatial coverage of the data: the basic administrative unit for which data is collected is the county, and it does not correspond to the erosion process scale which is the catchment. Defining erosion risk in terms of hazard categories rather than estimated erosion rates overcomes this difficulty to some extent. The use of reference areas provides several advantages in an upscaling procedure: these are mainly related to minimizing data collection and obtaining a reliable estimate of the accuracy of the predicted output.     

Some considerations on methods for spatially aggregating and disaggregating soil information

Some possible approaches to the aggregation and disaggregation of soil data and information are presented as an opener to the more detailed discussion. The concepts of hierarchy, grain, extent, scale and variability are discussed. Slight modifications to the Hoosbeek-Bryant scheme to deal with spatial and temporal scales and various types of quantitative models are suggested. Approaches to aggregation or upscaling are reviewed. The contributions of representative elementary volume (REV), variograms, fractal theory, multi-resolution analysis using wavelets, critical point phenomena, renormalisation groups and transfer functions are discussed followed by a brief presentation of some ecological approaches including extrapolation by lumping, extrapolation by increasing model extent and extrapolation by explicit integration. A clear distinction must be made between additive and non-additive variables. The scaling of the former is much less problematic than the latter. Corroboration of any approach by testing against the aggregated values seems problematic. Methods of disaggregation or downscaling including transfer functions, mass-preserving or pycnophylactic methods are also discussed. In order to make quantitative advances, nested sampling or reanalysis of data in land information systems to obtain variance information over a complete range of scales is required. Finally an appeal is made for work to begin on a quantitative scale-explicit theory of soil variation.     

New interdigital design for large area dye solar modules using a lead‐free glass frit sealing

A new interdigital design for large area dye solar modules is developed for an area of 30×30 cm². This design requires fewer holes in the glass substrate for electrolyte filling, than the conventional strip design. A complete manufacturing process of this module—ranging from screen printed layers to semi‐automated colouring and electrolyte filling—in a laboratory‐scale baseline is illustrated. As primary sealing method, a durable glass frit sealing is used. It is shown, that the lead (Pb) content present in many glass frit powders contaminates the catalytic platinum electrode during the sintering process, resulting in a lowering of the fill factor. A screen printable lead‐free glass frit paste is developed, which solves this problem. Long term stability tests are presented on 2·5 cm² dye solar cells, which have been completely sealed with glass frit. In consecutively performed accelerated ageing tests under 85°C in the dark (about 1400 h) and continuous illumination with visible light (1 sun, about 1700 h), a 2·5 cm² dye solar cell with an electrolyte based on propylmethylimidazolium iodide showed an overall degradation of less than 5% in conversion efficiency. In a subsequently performed thermal cycling test (−40°C to +85°C, 50 cycles) a 2·5 cm² dye solar cell with the same electrolyte composition also showed only a slight degradation of less than 5% in conversion efficiency. Copyright © 2006 John Wiley & Sons, Ltd.     

A new approach to evaluate the MODIS annual NPP product (MOD17A3) using forest field data from Turkey

In this study, we present the first evaluation of the MODIS (Moderate Resolution Imaging Spectroradiometer) annual net primary production (NPP) for Turkey’s forest ecosystems using field measurements. Due to lack of country scale field measurements (i.e. flux tower for forest ecosystems), tree DBH (diameter at breast height) data set provided by Ministry of Forest and Water Affairs (MFWA) of Turkey is used to calculate NPP of Turkey’s forest ecosystems. The lack of a reliable NPP data set leads the researchers to use global NPP models such as MODIS annual NPP product. The MODIS MOD17A3 product of vegetation NPP is one of the most highly used data sources for studies of global carbon cycle. However, it is still necessary to test its predictions in multiple biomes, especially for heterogeneous areas in terms of its accuracy and potential bias. Here, we studied a new approach to evaluate coarse scale NPP estimates from the MODIS NPP-MOD17A3 data product, using 2008–2013 field measurements of tree growth throughout Turkey. Three different methods were used to calculate field NPP, including standardized growth coefficients (ministry coefficients [MC]), growth coefficients from North America (Jenkins coefficients [JC]), and annual expected increment (AEI). The average NPP values for all the country is calculated as 2.06 kgC m^–1/5 years (0.412 kgC m^–2 year^–1) (SD = 1.15 kgC m^–1/5 years) from MOD17A3, 0.90 kgC m^–1/5 years (0.18 kgC m^–2 year^–1) (SD = 0.57 kgC m^–1/5 years) with MC, 0.63 kgC m^–1/5 years (0.126 kgC m^–2 year^–1) (SD = 0.37 kgC m^–1/5 years) with JC and 0.58 kgC m^–2 year^–1 (SD = 0.29 kgC m^–1/5 years) with AEI for the studied plots. We found that the MODIS NPP product has a clear relation with both the NPP estimates obtained by using MC (R² = 0.34, root mean square error (RMSE) = 1.51 kgC m^–1/5 years) and JC (R² = 0.32, RMSE = 1.73 kgC m^–1/5 years). In addition to that, the relation between MOD17A3 product and AEI-derived NPP is relatively strong (R² = 0.48, RMSE = 0.26 kgC m^–2 year^–1). We discuss possible reasons for these trade-offs among different methods. This study lays out a new approach to validate coarse scale MODIS product using field data directly, including for highly heterogeneous areas.