Geological resource management of the future: Drilling down the possibilities

Management of geological resources is based, ideally, on information on the quality and quantity of surface and subsurface litho-stratigraphical properties. Increasingly, these data become available for the offshore realm, though the integration into manageable and user-friendly applications is still at its infancy. Building on expertise from on-land data mining, we are now in the phase of creating 3D voxel models allowing for multi criteria resource volume calculations. The underlying data will be subdued to uncertainty modelling, a necessary step to produce data products with confidence limits. Anticipating on the dynamic nature of the marine environment, we aim at coupling the voxel model to environmental impact models to calculate resource depletion and regeneration, based on geological boundary conditions. In combination with anticipated impacts on fauna and flora, mining thresholds will be defined. All of the information is integrated into a decision support system for easy querying and online visualizations . The main aim is to provide long-term predictions on resource quantities to ensure future developments for the benefit of society and our future generations

Motivation for or from bilingual education? A comparative study of learner views in the Netherlands

Teaching and Teacher Learning (ICLON

Ground-penetrating radar profiling on embanked floodplains

Management of the Dutch embanked floodplains is of crucial interest in the light of a likely increase of extreme floods. One of the issues is a gradual decrease of floodwater accommodation space as a result of overbank deposition of mud and sand during floods. To address this issue, sediment deposits of an undisturbed embanked floodplain near Winssen along the river Waal were studied using ground-penetrating radar (GPR). A number of radar facies units were recognized. Boreholes were used to relate radar facies units to sedimentary facies and to determine radar velocity. The GPR groundwave is affected by differences in moisture and texture of the top layer and probably interferes with the first subsurface reflector. The architectural elements recognized in the GPR transects confirm earlier reported insights on human-influenced river behaviour. This is testified in the development of sand bars during flood regimes that are probably more widespread than previously established

Ground-penetrating radar profiling on embanked floodplains

Management of the Dutch embanked floodplains is of crucial interest in the light of a likely increase of extreme floods. One of the issues is a gradual decrease of floodwater accommodation space as a result of overbank deposition of mud and sand during floods. To address this issue, sediment deposits of an undisturbed embanked floodplain near Winssen along the river Waal were studied using ground-penetrating radar (GPR). A number of radar facies units were recognized. Boreholes were used to relate radar facies units to sedimentary facies and to determine radar velocity. The GPR groundwave is affected by differences in moisture and texture of the top layer and probably interferes with the first subsurface reflector. The architectural elements recognized in the GPR transects confirm earlier reported insights on human-influenced river behaviour. This is testified in the development of sand bars during flood regimes that are probably more widespread than previously established

Quantifying uncertainty of geological 3D layer models, constructed with a-priori geological expertise

Uncertainty quantification of geological models that are constructed with additional geological expert-knowledge is not straightforward. To construct sound geological 3D layer models we use a lot of additional knowledge, with an uncertainty that is hard to quantify. Examples of geological expert knowledge are trend surfaces that display a geological plausible basin, additional points that guide the pinching out of geological formations along its depositional extent, etc. All the added geological knowledge, together with the stringent assumptions of normality and second-order stationarity, makes the kriging standard error in our modeling not usable as a measure of uncertainty. We developed a procedure to quantify the uncertainty of our geological 3D layer model that uses cross-validation in a moving window environment to calculate mean deviations and standard errors on a sub-regional scale. Subsequently, we rescaled the x-validation standard error to account for local data configuration and clustering. Summary statistics (Root Mean Squared Prediction Error, Root Mean Error Variance and prediction interval) indicate that there is no bias in the geological model estimation and that the absolute values are trustworthy. An additional check on the above described results was provided by a spatial bootstrapping procedure. Based on 100 bootstrap samples that were "redrilled" in the model, the variance was not comparable to the cross-validated results. To validate the results of the uncertainty quantification we used a sample of (6% randomly selected) drillings as an independent dataset. Results indicate that for datasets with lots of data, the uncertainty quantification provided satisfying results, in terms of RMSE and RMEV. In cases of sparse data, setting aside 6% of the drillings leads to unfavorable statistics, indicating that a minimum of datapoints is needed to obtain a reliable quantification of uncertainty. Organisations: Golder Magyarorszag ZRt.; Mecsekerc Zrt.; MO

The Dutch Rhine-Meuse delta in 3D: A validation of model results

The Geological Survey of the Netherlands aims at building a 3D geological property model of the upper 30 meters of the Dutch subsurface. This model, called GeoTOP, provides a basis for answering subsurface related questions on, amongst others, sand and gravel resources. Modelling is carried out per province using a core-database containing several hundreds of thousands of core-descriptions, the majority of which reach down to around 10 to 15m, and a context of geological maps. This study focuses on the model of the province of Zuid-Holland where major cities like Rotterdam and The Hague are situated and the Rivers Rhine and Meuse enter the North Sea. A stepwise procedure consisting of automated database queries, 2D modelling of stratigraphic surfaces and 3D property modelling, resulted in a model of 50 million volume cells, each measuring 100 by 100 meters in horizontal directions and 0.5 meters in the vertical direction, every cell having estimates of lithology (sand, clay, peat) and sand-grain size class data. Running simulations, using the Sequential Indicator Simulation algorithm, resulted in information on the probabilities of the aforementioned properties. In the study presented here we focussed on two subjects. First we compared the above described GeoTOP model with two "quick and dirty" models constructed several years ago. The most important and visible difference between those models is the geological framework model used, which has more detail in GeoTOP. By comparing the two, we show the effect of detailed modelling on the cumulative exploitable reserves of aggregates. Secondly we show the effect of data density on GeoTOP modelling results. Using GeoTOP of Zuid-Holland gives us a opportunity to study the effect on the results of the amount of data used. We have therefore carried out a validation using subsequently less borehole information to estimate properties on a constant validation set. Organisations: Golder Magyarorszag ZRt.; Mecsekerc Zrt.; MO

Clay resources in the Netherlands

Clay is a common lithology in the Dutch shallow subsurface. It is used in earth constructions such as dikes, and as raw material for the fabricationof bricks, roof tiles etc. We present a new national assessment of Dutch clay resources, as part of a project that provides mineral-occurrenceinformation for land-use planning purposes. The assessment is based on a 3D geological model, which consists of voxel cells with lithologicalcomposition as primary attribute, and has been obtained by interpolating data of more than 380,000 digital borehole descriptions. Theoccurrence of shell material and the extent to which clay is peaty were used as quality attributes, enabling us to tentatively distinguish betweenclay that is potentially suitable as ceramic material, and clay that is not.As clay is extracted using dry (i.e. non-dredging) techniques, the model space has been dimensioned to fully encompass the unsaturatedzone. A high-resolution model (with voxel cells of 250 • 250 • 0.2 m), based mainly on abundant, good-quality hand drillings, was constructeddown to 3 m below the surface. This depth range suffices for clay-resource assessments in the lowlands, which have relatively high groundwaterlevels. Cells from a lower-resolution model (250 • 250 • 1 m, based on fewer data) were added to reach appropriate depths in upland areas.We arrive at about 42.1 km3 of clay occurring in the model space (land areas only). Clay occurs mainly in the coastal domain and below theRhine and Meuse river plains. Geological exploitability has been assessed within the unsaturated zone, taking overburden and intercalations withnon-clay materials (especially peat) into account. The resulting exploitable stock is 12.3 to 18.0 (± 2.0) km3; an estimate in which the mainsource of uncertainty is presented by a lack of proper groundwater-table data. This amount equates to roughly 6000 annual consumptionequivalents. Even when considering that the larger part of the clays is unsuitable for firing, and about one quarter is situated below built-uplands or nature preserves, clay is not a scarce resource in the Netherlands and supplies should present no problem in the near future

Advances in constructing regional geological voxel models, illustrated by their application in aggregate resource assessments

Aggregate resource assessments, derived from three subsequent generations of voxel models, were compared in a qualitative way to illustrate and discuss modelling progress. We compared the models in terms of both methodology and usability. All three models were produced by the Geological Survey of the Netherlands. Aggregate is granular mineral material used in building and construction, and in this case consists of sand and gravel. On each occasion ever-increasing computer power allowed us to model at a higher resolution and use more geological information to constrain interpolations. The two oldest models, built in 2005 and 2007, were created specifically for aggregate resource assessments, the first as proof of concept, the second for an online resource information system. The third model was derived from the ongoing multipurpose systematic 3D modelling programme GeoTOP. We used a study area of 40 × 40 km located in the central Netherlands, which encompasses a section of the Rhine-Meuse delta and adjacent glacial terrains to the north. Aggregate resource assessments rely on the extent to which the occurrence and grain size of sand and gravel are resolved, and on proper representation of clay and peat layers (overburden and intercalations) that affect exploitability. Average model properties (e.g. total aggregate content) are about the same in all three models, except for a difference resulting from converting older lithological classifications to the current one. This difference illustrates that data selection and preparation are paramount, especially when dealing with quality issues. Generally speaking the results of the aggregate resource assessments are consistent and satisfactory for all three models, provided that they are judged at the appropriate scale. However, the assessments based on GeoTOP best approach the desired scale of use for the aggregates industry; in that sense progress was significant and each model was a better fit for the purpose. © 2015 Netherlands Journal of Geosciences Foundation

Mapping Geotechnical Risk for Infrastructural Works in Deltaic Areas

This paper presents method and first results of a study to quantify and communicate geotechnical risk for highway construction on soft soil and large building pits associated with infrastructural works in the Netherlands. A set of easy-to-read maps will inform the end users, geotechnical consultants at the Dutch Ministry of Infrastructure and Environment, in the early stage of projects of the most important subsoil-related geotechnical risks and their spatial distribution. The method involves risk identification, risk assessment, identification of critical geological features contributing to this risk, and development of maps reflecting the magnitude of the geotechnical risk. Geological information is derived from the detailed 3D geological model GeoTOP. GeoTOP allows quick data assessment and creation of maps on a regional to nationwide scale. Close cooperation between geologists, geotechnical engineers and end users is the key success factor in application of the method. Geotechnical consultants will use the maps to identify risks, determine early risk mitigation measures and design site-investigation schemes