Point-bar deposits exhibiting fining-upward grain-size trends are widely documented from both modern rivers and ancient preserved successions. However, in some mud-dominated sedimentary systems this common pattern may not occur; rather, alternative coarsening-upward trends can develop. We investigated point-bar deposits in the mud-dominated river terminus (median value (D₅₀) < 55 μm) of the meandering Río Colorado in Bolivia's southern Altiplano, a semi-arid endorheic basin. Grain-size trends were investigated using double random grain-size distribution (GSD) measurements and end-member modelling analyses (EMMA), as well as detailed mineralogical analyses (XRD and LOI). These methods revealed an upward-coarsening trend of point-bar deposits in terms of D₅₀ of GSD and in proportions of coarse sediment for two (C2 and C0) of three chronologically different meandering channels in the river terminus. Those of another abandoned channel (C1) were, by contrast, dominated by a fining-upward trend. The deposits in channel C2 were characterised by a lower content of organic matter and carbonate compared with those of the other two channels. A novel conceptual model for the formation of coarsening-upward point-bar deposits is proposed. The model implies the action of low-frequency, high-magnitude floods during an overall hyper-arid period when sediment supply to the river terminus is dominated by clay and fine silt. A temporal trend toward higher magnitude and longer duration flood events allows for the transport coarser-grained sediments further down system toward the river terminus where deposition occurs on the inner bend of meandering channels. Successive accretion layers within the point-bar deposits record a coarsening upward trend. Results demonstrate how a coarsening-upward succession of point-bar deposits in the muddy river terminus of a semi-arid endorheic basin can contribute to improved understanding of mechanisms of deposition in fine-grained fluvial systems. Our results contribute to an improved understanding of the varied processes and sedimentology of very fine-grained meandering river terminus systems in semi-arid or arid endorheic basins; the results additionally provide insight to enable improved interpretations of rock record examples of pre-vegetation rivers on Earth and other planetary bodies.

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A new viscoelastic constitutive model for subaqueous clay-rich gravity flows is presented. It is explained that for the materials which exhibit a minimum in their strain controlled flow curves the structure parameter must be a symmetric function of the strain rate and the stress. Therefore, the destruction of structure within the material is modeled using the dissipation energy. An expression for the elastic strain of the flowing structure is derived. The final set of equations can reproduce the viscosity bifurcation that clay suspensions may exhibit under a given load. This is explained to be important for the prediction of the run-out distance of clay-rich gravity flows. The ability of the model to reproduce the general response of pasty materials to step stress and step shear rate tests is examined. The model requires four empirical parameters. A methodology is presented for obtaining these parameters and power law functions are given for their calculations for a limited rest time of 3000 s. The ability of the model to reproduce the rheological behavior that clay-rich suspensions exhibit under both stress and strain controlled conditions is examined using rheometry tests.

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In this paper, geological prior information is incorporated in the classification of reservoir lithologies after the adoption of Markov random fields (MRFs). The prediction of hidden lithologies is based on measured observations, such as seismic inversion results, which are associated with the latent categorical variables, based on the assumption of Gaussian distributions. Compared with other statistical methods, such as the Gaussian mixture model or k-Means, which do not take spatial relationships into account, the hidden MRFs approach can connect the same or similar lithologies horizontally while ensuring a geologically reasonable vertical ordering. It is, therefore, able to exclude randomly appearing lithologies caused by errors in the inversion. The prior information consists of a Gibbs distribution function and transition probability matrices. The Gibbs distribution connects the same or similar lithologies internally, which does not need a geological definition from the outside. The transition matrices provide preferential transitions between different lithologies, and an estimation of them implicitly depends on the depositional environments and juxtaposition rules between different lithologies. Analog cross sections from the subsurface or outcrop studies can contribute to the construction of these matrices by a simple counting procedure.

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Hidden Markov Models (HMMs) have been applied to predict reservoir lithologies using seismic inversion results as inputs. This approach takes into account the conditional probabilities between different lithologies, i.e. the vertical transitions in sedimentary sequences. These properties are used as prior geological information. In order to relate the seismic inversion results to the true well-log data, HMMs need to be trained based on the Expectation-Maximization theory. Application of the resulting model on a synthetic example from the Book Cliffs (Utah, USA) showed that most lithologies are classified correctly, even for some thin layers. A comparison with point-wise methods in which data samples are treated independently from each other, such as k-means and fuzzy logic classifiers, leads to the conclusion that the spatial correlation in HMMs allows better lithological predictions because the prior information accounts for the geological depositional processes. A real case study with data from the Vienna Basin (Austria) is performed, in which lithologies in a 3D cube are obtained based on properties from seismic inversions, via trained HMMs. While the vertical sequences are shown to be reasonably well predicted, the horizontal continuities are not. This indicates that the future research should focus on the lateral geological relationships.

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This study presents a classification for subaqueous clay-laden sediment gravity flows. A series of laboratory flume experiments were performed using 9%, 15%, and 21% sediment mixture concentrations composed of sand, silt, clay, and tap water, on varying bed slopes of 6°, 8°, and 9.5°, and with discharge rates of 10 and 15 m³/hr. In addition to the characteristics of the boundary and plug layers, which have been previously used for the classification of open-channel clay-laden flows, the newly presented classification also incorporates the treatment of the free shear layer. The flow states within the boundary and free shear layers were established using calculation of the inner variable, self-similarity considerations, and the magnitude of the apparent viscosity. Based on the experimental observations four flow types were recognized: (1) a clay-rich plug flow with a laminar free shear layer, a plug layer, and a laminar boundary layer, (2) a top transitional plug flow containing a turbulent free shear layer, a plug layer, and a laminar boundary layer, (3) a transitional turbidity current with a turbulent free shear layer, no plug layer, and a laminar boundary layer, and (4) a fully turbulent turbidity current. A connection between the emplaced deposits and the relevant flow types is drawn and it is shown that a Froude number, two Reynolds numbers, and a dimensionless yield stress parameter are sufficient to associate an experimental flow type with a natural large-scale density flow.

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The coupled Markov chain model can be used to simulate reservoir lithologies between wells, by conditioning them on the observed data in the cored wells. However, with this method, only the state at the same depth as the current cell is going to be used for conditioning, which may be a problem if the geological layers are dipping. This will cause the simulated lithological layers to be broken or to become discontinuous across the reservoir. In order to address this problem, an actively conditioned process is proposed here, in which a tolerance angle is predefined. The states contained in the region constrained by the tolerance angle will be employed for conditioning in the horizontal chain first, after which a coupling concept with the vertical chain is implemented. In order to use the same horizontal transition matrix for different future states, the tolerance angle has to be small. This allows the method to work in reservoirs without complex structures caused by depositional processes or tectonic deformations. Directional artefacts in the modeling process are avoided through a careful choice of the simulation path. The tolerance angle and dipping direction of the strata can be obtained from a correlation between wells, or from seismic data, which are available in most hydrocarbon reservoirs, either by interpretation or by inversion that can also assist the construction of a horizontal probability matrix.

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In this study, geological prior information is incorporated in the classification of reservoir lithologies using the Markov Random Field (MRF) technique. The prediction of hidden lithologies in seismic data is based on measured observations such as seismic inversion results, which are associated with the latent categorical variables derived from the distribution of Gaussian assumptions. The Hidden Markov Random Field (HMRF) approach can connect similar lithologies laterally (horizontally) while ensure a geologically reasonable stratigraphic (vertical) ordering. It is, therefore, able to exclude randomly appearing lithologies caused by errors in the inversion. In HMRF, the prior information consists of a Gibbs distribution function and transition probability matrices. The Gibbs distribution connects similar lithologies and does not need a geological definition derived from non-case-related information. The transition matrices provide preferential transitions between different lithologies and an estimation of these matrices implicitly depends on the depositional environments and juxtaposition rules between different lithologies.@en

Reservoir characterisation is a data driven process which involves the integration of different datasets to describe the subsurface. One of the difficulties of integrating geological data with the wave-equation based seismic inversion is that geological information is invariably interpreted as a layer-based model, whereas the wave-equation is defined and solved on a grid. Mapping a layer-based model space onto a grid-based space leads to highly non-Gaussian, multi-modal distribution functions, even when the layer-based properties have simple Gaussian distributions. In this paper an analytic method is presented that translates the prior layer-model based distributions to grid-based prior distributions. From the unconstrained seismic inversion result a Gaussian likelihood function is constructed and the method to find the maximum a posterior estimate (MAP) and its uncertainty is described. As geological prior information we use well data, a geological concept of the environment of deposition and structural seismic interpretation in the form of some horizons to guide the prior model in between wells. Given the prior model, a measure for the probability of the data is formulated. When this process is repeated for various prior scenarios, the probability of the scenario, given the data, can be calculated for every location.@en

The sea floor of intraslope minibasins on passive continental margins plays a significant role in controlling turbidity current pathways and the resulting sediment distribution. To address this, laboratory analogue modelling of intraslope minibasin formation is combined with numerical flow simulations of multi-event turbidity currents. This approach permits an improved understanding of evolving flow–bathymetry–deposit interactions and the resulting internal stacking patterns of the infills of such minibasins. The bathymetry includes a shelf to slope channel followed by an upper minibasin, which are separated by a confining ridge from two lower minibasins that compares well with analogous bathymetries reported from natural settings. From a wider range of numerical flow experiments, a series of 100 consecutive flows is reported in detail. The turbidity currents are released into the channel and upon reaching the upper minibasin follow a series of stages from short initial ponding, ‘filling and spilling’ and an extended transition to long retrogradational ponding. Upon reaching the upper minibasin floor, the currents undergo a hydraulic jump and therefore much sediment is deposited in the central part of the minibasin and the counterslope. This modifies the bathymetry such that in the fill and spill stage, flow stripping and grain-size partitioning cause some finer sediment to be transported across the confining ridge into the lower minibasins. Throughout the basin infill process, the sequences retrograde upstream, accompanied by lateral switching into locally formed depressions in the upper minibasin. After the fill and spill stage, significant deposition occurs in the channel where retrograding cyclic steps with wavelengths of 1 to 2 km develop as a function of pulsating flow criticality. These results are at variance with conventional schemes that emphasize sequential downstream minibasin filling through ponding dominated by vertical aggradation. Comparison of these results with published field and experimental examples provides support for the main conclusions.

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A method is presented to link prior geological information, from wells and interpretation, to full waveform inversion at reservoir scale. The method converts the layer-based prior information to grid-based property probability density distributions that are highly non-Gaussian and is based on Bayes' Rule. The likelihood function for the unconstrained inversion is based on the Hessian of the inversion kernel and the minimum residual energy in the objective function. Good results have been obtained from a synthetic case study based on a very realistic outcrop model (Book Cliffs,Utah). Also results from a real data case study will be shown. @en

Hidden Markov Model has been applied to predict the reservoir lithologies by using seismic inversion results as inputs. This method can take the conditional probability between different states or lithologies into account which is the vertical correlation in geology. In order to consider the misfit between the inversion results and the true well-logging data, the model needs to be trained. The application on a field example is quite successful in which most of lithologies have been predicted correctly even for some thin layers. However, this method is only 1D which means that the lateral continuity has not been considered yet. @en

A previous geological and petrophysical model of the fluvio-deltaic Book Cliffs outcrops contained eight lithotypes, within each of which a number of lithologies were grouped. While this model was an adequate representation of the overall depositional architecture, for reservoir-geological purposes the potential reservoir and non-reservoir lithologies needed to be separated. Here, a new and more detailed geological model is presented in which more differentiation is put on the potential reservoir lithologies. This new model contains 12 lithologies with layers down to 1 m in thickness. Assuming a burial depth of 3 km and an average clay content, representative rock physical properties are assigned to lithologies based on published data. After the model thickness has been stretched by a factor of 4 in order to represent a more realistic reservoir, a full-waveform forward seismic response is modelled. These data are used as inputs into an iterative elastic wave-equation-based inversion scheme, with the goal to retrieve the rock properties and layer geometries. The results of this conceptual study show that sandstone units in the shoreface and distributary channels, which are potential reservoirs, are successfully identified. The recovery of medium parameters has a high resolution because the non-linear relationship between rock properties and the seismic data has been exploited. @en

Transformations of a subaqueous density flow from proximal to distal regions are investigated. A classification of these transformations based on the state of the free shear and boundary layers and existence of a plug layer during transition from a debris flow to a turbidity current is presented. A connection between the emplaced deposit by the flow and the relevant flow type is drawn through the results obtained from a series of laboratory flume experiments. These were performed using 9%, 15%, and 21% sediment mixture concentrations composed of sand, silt, clay, and tap water, on varying bed slopes of 6, 8, and 9:5, and with discharge rates of 10[m3=h] and 15[m3=h]. Stress-controlled rheometry experiments were performed on the mixtures to obtain apparent viscosity data. A classification was developed based on the imposed flow conditions, where a cohesive flow may fall within one of five distinct flow types: 1) a cohesive plug flow (PF) with a laminar free shear and boundary layers, 2) a top transitional plug flow (TTPF) containing a turbulent free shear layer, a plug layer, and a laminar boundary layer, 3) a complete transitional plug flow (CTPF) consisting of a turbulent free shear and boundary layers and a plug, 4) a transitional turbidity current (TTC) with a turbulent free shear layer and a laminar boundary layer, and, 5) a completely turbulent turbidity current (TC). During the experiments, flow type PF resulted in en masse deposition of a thick uniform ungraded muddy sand mixture, which was emplaced once the yield stress overcame the gravitational forces within the tail region of the flow. Flow type TTPF resulted in deposition of a thin ungraded basal clean sand layer during the run. This layer was covered by a muddy sand deposit from the tail. Flow type TTC did not deposit any sediment during the run. A uniform muddy sand mixture was emplaced by the tail of the flow. Flow type TC resulted in deposition of poorly sorted massive bottom sand layer. This layer was overlain by either a muddy sand mixture or a sand and silt planar lamination. Flow type CTPF was not observed during the experiments. Furthermore, it was observed that flows which are in transition from a TTC to a TTPF result in a thin bottom clean sand layer covered by a banded transitional interval. This was overlain by a muddy sand layer and a very thin clean sand layer, resulting from traction by dilute turbulent wake. In all cases a mud cap was emplaced on top of the deposit after the runs were terminated.@en

ICDP workshop COring the NOrth Sea Cenozoic focused on the scientific objectives and the technical aspects of drilling and sampling. Some 55 participants attended the meeting, ranging from climate scientists, drilling engineers, and geophysicists to stratigraphers and public outreach experts. Discussion on the proposed research sharpened the main research lines and led to working groups and the necessary technical details to compile a full proposal that was submitted in January 2016.@en

The morphological evolution of submarine channel systems can be documented using high-resolution three-dimensional seismic data sets. However, these studies provide limited information on the distribution of sedimentary facies within channel fills, channelscale stacking patterns, or the detailed stratigraphic relationship with adjacent levee-overbank deposits. Seismic-scale outcrops of unit C2 in the Permian Fort Brown Formation, Karoo Basin, South Africa, on two subparallel fold limbs comprise thin-bedded successions, interpreted as external levee deposits, which are adjacent to channel complexes, with constituent channels filled with thick-bedded structureless sandstones, thinner-bedded channel margin facies, and internal levee deposits. Research boreholes intersect all these deposits, to link sedimentary facies and channel stacking patterns identified in core and on image logs and detailed outcrop correlation panels. Key characteristics, including depth of erosion, stacking patterns, and cross-cutting relationships, have been constrained, allowing paleogeographic reconstruction of six channel complexes in a 36-km² (14-mi²) area. The system evolved from an early, deeply incised channel complex, through a series of external levee-confined and laterally stepping channel complexes culminating in an aggradational channel complex confined by both internal and external levees. Down-dip divergence of six channel complexes from the same location suggests the presence of a unique example of an exhumed deep-water avulsion node. Down-dip, external levees are supplied by flows that escaped fromchannel complexes of different ages and spatial positions and are partly confined and share affinities with internal levee successions. The absence of frontal lobes suggests that the channels remained in sand bypass mode immediately after avulsion.

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