Characterization Method and Application of Heterogeneous Reservoir Based on Different Data Quantity

Deep saline aquifers have strong heterogeneity under natural conditions, which affects the migration of carbon dioxide (CO2) injection into the reservoir. How to characterize the heterogeneity of rock mass is of great significance to research the CO2 migration law during CO2 storage. A method is proposed to construct different heterogeneous models from the point of view of whether the amount of data is sufficient or not, the wholly heterogeneous model with sufficient data, the deterministic multifacies heterogeneous model which is simplified by lithofacies classification, and the random multifacies heterogeneous model which is derived from known formation based on transfer probability theory are established, respectively. Numerical simulation is carried out to study the migration law of CO2 injected into the above three heterogeneous models. The results show that the migration of CO2 in heterogeneous deep saline aquifers shows a significant fingering flow phenomenon and reflect the physical process in CO2 storage; the migration law of CO2 in the deterministic multifacies heterogeneous model is similar to that in the wholly heterogeneous model and indicates that the numerical simulation of simplifying the wholly heterogeneous structure to the lithofacies classification structure is suitable for simulating the CO2 storage process. The random multifacies heterogeneous model based on the transfer probability theory accords with the development law of sedimentary formation and can be used to evaluate the CO2 migration law in unknown heterogeneous formations. On the other hand, by comparing the dry-out effect of CO2 in different heterogeneous models, it is pointed out that the multifacies characterization method will weaken the influence due to the local homogenization of the model in small-scale research; it is necessary to refine the grid and subdivide the lithofacies of the local key area elements to eliminate the research error. The research results provide feasible references and suggestions for the heterogeneous modeling of the missing data area and the simplification of large-scale heterogeneous models.

ModelRevelator: Fast phylogenetic model estimation via deep learning

Selecting the best model of sequence evolution for a multiple sequence alignment (MSA) constitutes the first step of phylogenetic tree reconstruction. Common approaches for inferring nucleotide models typically apply maximum likelihood (ML) methods, with discrimination between models determined by one of several information criteria. This requires tree reconstruction and optimisation which can be computationally expensive. We demonstrate that neural networks can be used to perform model selection, without the need to reconstruct trees, optimise parameters, or calculate likelihoods. We introduce ModelRevelator, a model selection tool underpinned by two deep neural networks. The first neural network, NNmodelfind, recommends one of six commonly used models of sequence evolution, ranging in complexity from JC to GTR. The second, NNalphafind, recommends whether or not a Γ--distributed rate heterogeneous model should be incorporated, and if so, provides an estimate of the shape parameter, ɑ. Users can simply input an MSA into ModelRevelator, and swiftly receive output recommending the evolutionary model, inclusive of the presence or absence of rate heterogeneity, and an estimate of ɑ. We show that ModelRevelator performs comparably with likelihood-based methods over a wide range of parameter settings, with significant potential savings in computational effort. Further, we show that this performance is not restricted to the alignments on which the networks were trained, but is maintained even on unseen empirical data. ModelRevelator will be made freely available in the forthcoming version of IQ-Tree (http://www.iqtree.org), and we expect it will provide a valuable alternative for phylogeneticists, especially where traditional methods of model selection are computationally prohibitive.

Selecting and averaging relaxed clock models in Bayesian tip dating of Mesozoic birds

Relaxed clock models are fundamental in Bayesian clock dating, but a single distribution characterizing the clock variation is typically selected. Hence, I developed a new reversible-jump Markov chain Monte Carlo (rjMCMC) algorithm for drawing posterior samples between the independent lognormal (ILN) and independent gamma rates (IGR) clock models. The ability of the rjMCMC algorithm to infer the true model was verified through simulations. I then applied the algorithm to the Mesozoic bird data previously analyzed under the white noise (WN) clock model. In comparison, averaging over the ILN and IGR models provided more reliable estimates of the divergence times and evolutionary rates. The ILN model showed slightly better fit than the IGR model and much better fit than the autocorrelated lognormal (ALN) clock model. When the data were partitioned, different partitions showed heterogeneous model fit for ILN and IGR clocks. The implementation provides a general framework for selecting and averaging relaxed clock models in Bayesian dating analyses.

New Insight into the Interplay of Method of Deposition, Chemical State of Pd, Oxygen Storage Capability and Catalytic Activity of Pd-Containing Perovskite Catalysts for Combustion of Methane

Elaboration of Pd-supported catalysts for catalytic combustion is, nowadays, considered as an imperative task to reduce the emissions of methane. This study provides new insight into the method of deposition, chemical state of Pd and oxygen storage capability of transition metal ions and their effects on the catalytic reactivity of supported catalysts for the combustion of methane. The catalyst with nominal composition La(Co0.8Ni0.1Fe0.1)0.85Pd0.15O3 was supported on SiO2-modified/γ-alumina using two synthetic procedures: (i) aerosol assisted chemical vapor deposition (U-AACVD) and (ii) wet impregnation (Imp). A comparative analysis shows that a higher catalytic activity is established for supported catalyst obtained by wet impregnation, where the PdO-like phase is well dispersed and the transition metal ions display a high oxygen storage capability. The reaction pathway over both catalysts proceeds most probably through Mars–van Krevelen mechanism. The supported catalysts are thermally stable when they are aged at 505 °C for 120 h in air containing 1.2 vol.% water vapor. Furthermore, the experimentally obtained data on La(Co0.8Ni0.1Fe0.1)0.85Pd0.15O3—based catalyst, supported on monolithic substrate VDM®Aluchrom Y Hf are simulated by using a two-dimensional heterogeneous model for monolithic reactor in order to predict the performance of an industrial catalytic reactor for abatement of methane emissions.

3D City Online Visualization and Cluster Architecture for Digital City

As an important carrier of human production, life, and social development, the emergence of cities symbolizes the maturity and civilization of mankind. For more than 40 years of reform and opening up, our country’s economic development has become increasingly prosperous, and urbanization is booming. At present, our country is in a decisive period for building a well-off society in an all-round way, with rapid progress in socio-economic growth and urbanization. Based on this, this article is oriented towards urban visualization modeling work and proposes a cluster modeling method that is compatible with the combination of urban geological structure and three-dimensional urban space, so that urban space modeling work not only pays attention to the rationality of above-ground planning and construction but also fully considers underground geology the stability and safety of the structure. This paper uses the 3D city online visualization modeling technology to efficiently and reasonably complete the 3D urban geological modeling under the fusion of multiple geological data and combines the organic combination of multisource heterogeneous model data to convert the geological model data into a 3D geographic information model; the universal standard format analyzes the rapid construction of large-scale complex geological structure models and the integrated expression of multisource heterogeneous model data. Experiments have proved that from the cluster capacity of 5,000 to 100,000, no matter how much the modeling time is different, whether it is to search the entire territory or part of the scope, the search time of the 3D city visualization model is less than 20 ms, and the 3D city visualization model map of the city can be well established. This shows that the three-dimensional city visualization model highlights the impact of the urban geological environment on urban construction and development and visually and vividly displays region geological structure and other information in a three-dimensional way, providing corresponding information for urban geological stability assessment and geological disaster rescue reference and help.

The Impact of Predicted Climate Change on Groundwater Resources in a Mediterranean Archipelago: A Modelling Study of the Maltese Islands

The effects of changes in climate predicted for 2100—reduction in recharge, increase in water demand and sea-level rise—on groundwater volume and saltwater intrusion have been quantified in the Maltese Islands, an archipelago located at the center of the Mediterranean Sea. A three-dimensional density dependent and heterogeneous model, working in transient conditions, was developed based on morphological and geological information. The hydraulic conductivity and porosity of the lithological formations were derived from previous tests and studies conducted on the islands. The complex fault system intersecting the area has also been included in the model. The results show that among the three considered factors affecting groundwater resources, the most significant is the increase in water demand, which is closely followed by the decrease in groundwater recharge. Sea-level rise plays a marginal role. The 80-year simulation period showed that these combined impacts would cause a loss of more than 16% of groundwater volume.

Algorithmic Analysis of Finite-Source Multi-Server Heterogeneous Queueing Systems

The paper deals with a finite-source queueing system serving one class of customers and consisting of heterogeneous servers with unequal service intensities and of one common queue. The main model has a non-preemptive service when the customer can not change the server during its service time. The optimal allocation problem is formulated as a Markov-decision one. We show numerically that the optimal policy which minimizes the long-run average number of customers in the system has a threshold structure. We derive the matrix expressions for performance measures of the system and compare the main model with alternative simplified queuing systems which are analysed for the arbitrary number of servers. We observe that the preemptive heterogeneous model operating under a threshold policy is a good approximation for the main model by calculating the mean number of customers in the system. Moreover, using the preemptive and non-preemptive queueing models with the faster server first policy the lower and upper bounds are calculated for this mean value.

Three-Dimensional Numerical Simulation of Multiscale Fractures and Multiphase Flow in Heterogeneous Unconventional Reservoirs with Coupled Fractal Characteristics

A simulated reservoir model, based on the permeability fractal model and three-dimensional (3D) Gaussian filter, was established to account for in-layer and interlayer heterogeneity so that the result conforms to the law of geological statistics. Combined with an embedded discrete fracture method (EDFM), a multiscale fracture system was established, forming the numerical simulation method of multiphase flow in horizontal wells in heterogeneous reservoirs with complex fractures. The heterogeneity and saturation of the reservoir mixed five-point pattern of vertical and horizontal wells and the injection and production of horizontal wells were discussed. The results show that it is difficult to characterize complex reservoirs using a homogeneous permeability model. Thus, it is best to use a heterogeneous model that considers permeability differences in tight reservoirs. Formation fluids coexist in multiple phases, and water saturation has a direct effect on the production. Thus, a multiphase flow model is needed and can play a greater role in injection and production technology. The mixed five-point pattern of vertical and horizontal wells can improve productivity to a certain extent, but the dual effects of heterogeneity and fracturing will cause a decline in production by accelerating the communication of injected fluid. The reservoir is heterogeneous between wells, and there are differing effects on adjacent wells. Therefore, near-well natural microfractures are opened because of fracturing in horizontal wells, and the heterogeneity cannot be ignored, especially when multiple wells are simultaneously injected and produced.

Process Knowledge Graph Modeling Techniques and Application Methods for Ship Heterogeneous Models

In the process design and reuse of marine component products, there are a lot of heterogeneous models, causing the problem that the process knowledge and process design experience contained in them are difficult to express and reuse. Therefore, a process knowledge representation model for ship heterogeneous model is proposed in this paper. Firstly, the multi-element process knowledge graph is constructed, and the heterogeneous ship model is described in a unified way. Then, the multi-strategy ontology mapping method is applied, and the semantic expression between the process knowledge graph and the entity model is realized. Finally, by obtaining implicit semantics based on case-based reasoning and checking the similarity of the matching results, the case knowledge reuse is achieved, to achieve rapid design of the process. This method provides reliable technical support for the design of ship component assembly and welding process, greatly shortens the design cycle, and improves the working efficiency. In addition, a case study of the test model is carried out to verify the feasibility and efficiency of the proposed method.