Seismic on floating ice: data acquisition versus flexural wave noise

Geophysical surveying of the Arctic will become increasingly important in future prospecting and monitoring of the terrestrial and adjacent areas in this hemisphere. Seismic data acquired on floating ice are hampered with extensive noise due to ice vibrations related to highly dispersive ice flexural waves generated by the seismic source. Several experiments have been conducted on floating ice in van Mijenfjorden in Svalbard in the Norwegian Arctic to specifically analyse the extent of flexural waves recorded with various seismic receivers and sources deployed both on top of ice and in the water below. The data show that flexural waves are severely damped at 5 m or deeper below the ice and hydrophone data suffer less from these vibrations compared with data recorded on the ice. Aliasing of single receiver hydrophone data can to some extent be suppressed using an in-line line source of detonating cord. Experiments on ice on shallow water show prominent guided wave modes often referred to as Scholte waves propagating along the seabed. In this case, both flexural and Scholte waves interfere and make a complicated pattern of coherent noise. On shallow water, the positioning and type of the seismic source must be evaluated with respect to the coherent noise generated by these waves. Geophone strings of 25 m effectively suppress both flexural and Scholte waves due to their relative short wavelengths. An airgun generates relative more low-frequency energy than a surface source of detonating cord. Accordingly, seismic mapping of deep seismic horizons seem to be best achieved using geophone strings of such length and an airgun source. For shallow targets, the use of hydrophones in combination with detonating cord is an appropriate solution. Seismic surveying in the Arctic always have to follow environmental restrictions of not disturbing or harming wildlife and not causing permanent footprints into the vulnerable tundra, which implies that the choice of seismic acquisition strategy might occur as a trade-off between optimum data quality and environmental constraints.     

Entropy analysis of in situ particle size spectra

Entropy analysis has been used to classify in situ particle (floc) size spectra of suspended particles into groups based on similar distribution characteristics. Results revealed that the in situ spectra sorted into groups that reflected different forcing conditions (e.g. variations in turbulence). The different forcing conditions were not necessarily reflected in other commonly used distribution measures such as median floc diameter. This suggests that entropy analysis may be an effective approach for investigating the effect of changes in forcing conditions on floc size. It is hypothesized that it may be possible to derive the average shape of floc size spectra from measurement of the forcing conditions alone and subsequently derive parameters such as floc fraction, floc density, floc settling velocity and the optical properties of the water column from the average spectra.     

High-resolution vertical profiles of groundwater electrical conductivity (EC) and chloride from direct-push EC logs

Elevated groundwater salinity associated with produced water, leaching from landfills or secondary salinity can degrade arable soils and potable water resources. Direct-push electrical conductivity (EC) profiling enables rapid, relatively inexpensive, high-resolution in-situ measurements of subsurface salinity, without requiring core collection or installation of groundwater wells. However, because the direct-push tool measures the bulk EC of both solid and liquid phases (EC_a), incorporation of EC_a data into regional or historical groundwater data sets requires the prediction of pore water EC (EC_w) or chloride (Cl^?) concentrations from measured EC_a. Statistical linear regression and physically based models for predicting EC_w and Cl^? from EC_a profiles were tested on a brine plume in central Saskatchewan, Canada. A linear relationship between EC_a/EC_w and porosity was more accurate for predicting EC_w and Cl^? concentrations than a power-law relationship (Archie’s Law). Despite clay contents of up to 96%, the addition of terms to account for electrical conductance in the solid phase did not improve model predictions. In the absence of porosity data, statistical linear regression models adequately predicted EC_w and Cl^? concentrations from direct-push EC_a profiles (EC_w = 5.48 EC_a + 0.78, R ² = 0.87; Cl^? = 1,978 EC_a – 1,398, R ² = 0.73). These statistical models can be used to predict EC_w in the absence of lithologic data and will be particularly useful for initial site assessments. The more accurate linear physically based model can be used to predict EC_w and Cl^? as porosity data become available and the site-specific EC_w–Cl^? relationship is determined.     

Marine conditions in central Sweden during the early Preboreal as inferred from a stable oxygen isotope gradient

The marine benthic fauna and the δ¹⁸O_c of foraminifers and ostracods from six sites situated on a west–east transect through central Sweden have been analysed in order to estimate the palaeosalinity and palaeocirculation in this shallow‐marine environment. The measurements have been undertaken on material from the early Preboreal, when the Baltic Basin was in contact with the North Sea through straits in central Sweden. The δ¹⁸O_c values have a more negative value towards the east, indicating decreasing salinity. This was the result of limited possibilities for marine water to penetrate into the Baltic Basin and the mixing with freshwater from the melting Fennoscandian ice‐sheet. Four water masses existed in the area: a surface layer of freshwater, marine water from the North Sea, brackish–marine intermediate water on the Swedish west coast and brackish Yoldia Sea water in the Baltic Basin. The chronology is based on radiocarbon dates of marine fossils and, at one site, on the occurrence of the Vedde Ash (10 400–10 300 ¹⁴C yr BP). This is the first record from marine settings in Sweden. Copyright © 2001 John Wiley & Sons, Ltd.     

Assimilating spatially dense data for subsurface applications—balancing information and degrees of freedom

The degrees of freedom (DOF) in standard ensemble-based data assimilation is limited by the ensemble size. Successful assimilation of a data set with large information content (IC) therefore requires that the DOF is sufficiently large. A too small number of DOF with respect to the IC may result in ensemble collapse, or at least in unwarranted uncertainty reduction in the estimation results. In this situation, one has two options to restore a proper balance between the DOF and the IC: to increase the DOF or to decrease the IC. Spatially dense data sets typically have a large IC. Within subsurface applications, inverted time-lapse seismic data used for reservoir history matching is an example of a spatially dense data set. Such data are considered to have great potential due to their large IC, but they also contain errors that are challenging to characterize properly. The computational cost of running the forward simulations for reservoir history matching with any kind of data is large for field cases, such that a moderately large ensemble size is standard. Realization of the potential in seismic data for ensemble-based reservoir history matching is therefore not straightforward, not only because of the unknown character of the associated data errors, but also due to the imbalance between a large IC and a too small number of DOF. Distance-based localization is often applied to increase the DOF but is example specific and involves cumbersome implementation work. We consider methods to obtain a proper balance between the IC and the DOF when assimilating inverted seismic data for reservoir history matching. To decrease the IC, we consider three ways to reduce the influence of the data space; subspace pseudo inversion, data coarsening, and a novel way of performing front extraction. To increase the DOF, we consider coarse-scale simulation, which allows for an increase in the DOF by increasing the ensemble size without increasing the total computational cost. We also consider a combination of decreasing the IC and increasing the DOF by proposing a novel method consisting of a combination of data coarsening and coarse-scale simulation. The methods were compared on one small and one moderately large example with seismic bulk-velocity fields at four assimilation times as data. The size of the examples allows for calculation of a reference solution obtained with standard ensemble-based data assimilation methodology and an unrealistically large ensemble size. With the reference solution as the yardstick with which the quality of other methods are measured, we find that the novel method combining data coarsening and coarse-scale simulations gave the best results. With very restricted computational resources available, this was the only method that gave satisfactory results.     

Evolution of sea-level trends along the Norwegian coast from 1960 to 2100

Ocean Dynamics - A first national analysis of the evolution of sea-level rates along the Norwegian coast for the period 1960–2100 has been accomplished by exploring tide-gauge records,...