Sink or float: microtextural controls on the fate of pumice deposition during the 2012 submarine Havre eruption

Silicic submarine volcanic eruptions can produce large volumes of pumices that may rise buoyantly to the ocean surface and/or sink to the seafloor. For eruptions that release significant volumes of pumice into rafts, the proximal to medial submarine geologic record is thus depleted in large volumes of pumice that would have sedimented closer to source in any subaerial eruption. The 2012 eruption of Havre volcano, a submarine volcano in the Kermadec Arc, presents a unique opportunity to study the partitioning of well-constrained rafted and seafloor pumice. Macro- and microtextural analysis was performed on clasts from the Havre pumice raft and from coeval pumiceous seafloor units around the Havre caldera. The raft and seafloor clasts have indistinguishable macrotextures, componentry, and vesicularity ranges. Microtextural differences are apparent as raft pumices have higher vesicle number densities (109 cm−3 vs. 108 cm−3) and significantly lower pore space connectivity (0.3–0.95 vs. 0.9–1.0) than seafloor pumices. Porosity analysis shows that high vesicularity raft pumices required trapping of gas in the connected porosity to remain afloat, whereas lower vesicularity raft pumices could float just from gas within isolated porosity. Measurements of minimum vesicle throat openings further show that raft pumices have a larger proportion of small vesicle throats than seafloor pumices. Narrow throats increase gas trapping as a result of higher capillary pressures acting over gas–water interfaces between vesicles and lower capillary number inhibiting gas bubble escape. Differences in isolated porosity and pore throat distribution ultimately control whether pumices sink or float and thus whether pumice deposits are preserved or not on the seafloor.

Specific features of the probability petrophysical estimation of rock formations using the approaches of the concept of porous space connectedness

Background. The technology of probability petrophysical estimation of parameters using layer-bylayer interpretation of well logging data is present in this paper. Specific features of the technology is to using both the vertical and horizontal processing. Aim. The aim of the technology is the possibility of its adaptation when interpreting well logging data using the approaches of the concept of pore space connectedness, which reduce the variability of estimates of productive thicknesses of reservoirs in comparison with traditional approaches to calculating geological reserves using fixed cutoff porosity coefficient. Materials and methods. The paper discusses the main features of modeling the uncertainties of the input parameters and ways of representing them in the form of various distributions with a description of a generalized algorithm for the probabilistic assessment of geological reserves. The distributions of the reservoir area, oil density and conversion factor, the basic version of the results of the reservoir logging data interpretation in the form of a table continuous in depth with readings from the logging methods curves in intervals homogeneous in lithology are use as input parameters when executing the algorithm. In addition, distributions reflecting variations in the uncertainties of geophysical parameters, constants of petrophysical models, boundary cutoff s for identifying reservoirs and assessing their saturation nature are used to the input of the algorithm. Results. An algorithm for probabilistic petrophysical assessment has been developed taking into account the use of petrophysical modeling within the framework of the concept of pore space connectivity and the layer-by-layer mode of interpretation of well logging data. It is shown that additional petrotyping, which makes it possible to clarify the parameter of pore space connectivity, reduces the error of the resulting estimates, which can reduce the risk of making ineffective decisions. Conclusions. It is show that additional petrotyping, which makes it possible to clarify the parameter of pore space connectedness, reduces the error of the resulting estimates, which can reduce the risk of making ineffective decisions.

Computational methods for airspace sectorisation

A problem of combining elementary sectors of an airspace region is considered, in which a minimum number of combined sectors must be obtained with restrictions on their load and feasibility of combinations such as the requirement of the space connectivity or the membership of a given set of permissible combinations. Computational methods are proposed and tested to be used for solution of general problems of airspace sectorization. In particular, two types of combinatorial algorithms are proposed for constructing partitions of a finite set with specified element weights and graph-theoretical relationships between the elements. Partitions are constructed by use of a branch and bound method to minimize the number of subsets in the final partition, while limiting the total weight of elements in the subset. In the first type algorithm, ready-made components of the final partition are formed in each node of the branch and bound tree. The remaining part of the original set is further divided at the lower nodes. In the second type algorithm, the entire current partition is formed in each node, the components of which are supplemented at the lower nodes. When comparing algorithms performance, the problems are divided into two groups, one of which contains a connectivity requirement, and the other does not. Several integer programming formulations are also presented. Computational complexity of two problem variants is established: a bin packing type problem with restrictions on feasible combinations, and covering type problem.

Effect of different spatial normalization approaches on tractography and structural brain networks

To facilitate the comparison of white matter morphologic connectivity across target populations, it is invaluable to map the data to a standardized neuroanatomical space. Here, we evaluated direct streamline normalization (DSN), where the warping was applied directly to the streamlines, with two publically available approaches that spatially normalize the diffusion data and then reconstruct the streamlines. Prior work has shown that streamlines generated after normalization from reoriented diffusion data do not reliably match the streamlines generated in native space. To test the impact of these different normalization methods on quantitative tractography measures, we compared the reproducibility of the resulting normalized connectivity matrices and network metrics with those originally obtained in native space. The two methods that reconstruct streamlines after normalization led to significant differences in network metrics with large to huge standardized effect sizes, reflecting a dramatic alteration of the same subject’s native connectivity. In contrast, after normalizing with DSN we found no significant difference in network metrics compared with native space with only very small-to-small standardized effect sizes. DSN readily outperformed the other methods at preserving native space connectivity and introduced novel opportunities to define connectome networks without relying on gray matter parcellations.

Development of a Resistivity Model That Incorporates Quantitative Directional Connectivity and Tortuosity for Enhanced Assessment of Hydrocarbon Reserves

Summary Success of the strategies to exploit hydrocarbon reservoirs depends on the availability of reliable information about pore structure and spatial distribution of fluids within the pore space. Reliable quantification of directional pore-space connectivity and characterization of pore architecture are, however, challenging. The objectives of this paper include (1) quantifying the directional connectivity of pore space [connected pore volume (PV)] and rock components, (2) identifying geometry-defined fabric features that contribute to the pore-connectivity variations within the same formation (e.g., tortuosity, constriction factor) and introducing analytical/numerical methods and mechanistic models to estimate them, and (3) improving assessment of hydrocarbon saturation by introducing a new resistivity model that incorporates the directional pore-space-connectivity factor. We introduce a new resistivity model that minimizes calibration efforts and improves assessment of hydrocarbon saturation in complex formations by incorporating a directional connectivity factor. The directional pore-space connectivity is defined as the geometry and texture of the porous media resulting from sedimentary and diagenetic processes, and is estimated with pore-scale images. The directional connectivity factor is a function of electrical tortuosity, and, therefore, we introduce a mechanistic equation that incorporates geometrical features of the pore space to accurately estimate electrical tortuosity. Then, we validate the new tortuosity model against results obtained from a semianalytical streamline algorithm in 3D pore-scale images from each rock type of interest in the formation. The actual electrical tortuosity obtained from numerical simulations is calculated with the geometry of the streamlines associated with the electric current and the corresponding time of flight (TOF) of electric charges. We successfully applied the introduced method to two carbonate formations. The results confirm that the introduced directional-connectivity factor can detect rock-fabric features, through quantifying the connected PV and tortuosity, and that it is a function of the directional-diffusivity coefficient. The quantification of rock fabric and pore-space connectivity improves the estimation of hydrocarbon saturation by 43% compared with conventional methods. The use of such a parameter for rock-fabric characterization from pore-scale images helps to decrease the need for calibration efforts in the interpretation of borehole geophysical measurements. Just a few cuttings from different rock types are sufficient for the proposed method.

Topological and network analysis of lithium ion battery components: the importance of pore space connectivity for cell operation

Pore space connectivity is a useful metric for describing microstructure of lithium ion battery components.

QCMA hardness of ground space connectivity for commuting Hamiltonians

In this work we consider the ground space connectivity problem for commuting local Hamiltonians. The ground space connectivity problem asks whether it is possible to go from one (efficiently preparable) state to another by applying a polynomial length sequence of 2-qubit unitaries while remaining at all times in a state with low energy for a given HamiltonianH. It was shown in [Gharibian and Sikora, ICALP15] that this problem is QCMA-complete for general local Hamiltonians, where QCMA is defined as QMA with a classical witness and BQP verifier. Here we show that the commuting version of the problem is also QCMA-complete. This provides one of the first examples where commuting local Hamiltonians exhibit complexity theoretic hardness equivalent to general local Hamiltonians.

Approximate answering of queries involving polyline–polyline topological relationships

In geographic information systems, pictorial query languages are visual languages which make easier the user to express queries by free-hand drawing. In this perspective, this article proposes an approach to provide approximate answers to pictorial queries that do not match with the content of the database, that is, the results are null. It addresses the polyline–polyline topological relationships and is based on an algorithm, called Approximate Answer Computation algorithm, which exploits the notions of Operator Conceptual Neighborhood graph and 16-intersection matrix. The operator conceptual neighborhood graph represents the conceptual topological neighborhood between Symbolic Graphical Objects and is used for relaxing constraints of queries. The nodes of the operator conceptual neighborhood graph are labeled with geo-operators whose semantics has been formalized. The 16-intersection matrix provides enriched query details with respect to the well-known Dimensionally Extended 9-Intersection Model proposed in the literature. A set of minimal 16-intersection matrices associated with each node of the operator conceptual neighborhood graph, upon the external space connectivity condition, is defined and the proof of its minimality is provided. The main idea behind each introduced notion is illustrated using a running example throughout this article.