Recent Submissions

  • Remotely sensing phytoplankton size structure in the Red Sea

    Gittings, John; Brewin, Robert J.W.; Raitsos, Dionysios E.; Kheireddine, Malika; Ouhssain, Mustapha; Jones, Burton; Hoteit, Ibrahim (Remote Sensing of Environment, Elsevier BV, 2019-10-09) [Article]
    Phytoplankton size structure impacts ocean food-web dynamics and biogeochemical cycling, and is thus an important ecological indicator that can be utilised to quantitatively evaluate the state of marine ecosystems. Potential alterations to size structure are predicted to occur in tropical regions under future scenarios of climate change. Therefore, there is an increasing requirement for the synoptic monitoring of phytoplankton size structure in marine systems. The Red Sea remains a comparatively unexplored tropical marine ecosystem, particularly with regards to its large-scale biological dynamics. Using an in situ pigment dataset acquired in the Red Sea, we parameterise a two-component, abundance-based phytoplankton size model and apply it to remotely-sensed observations of chlorophyll-a (Chl-a) concentration, to infer Chl-a in two size classes of phytoplankton, small cells <2 μm in size (picophytoplankton) and large cells >2 μm in size. Satellite-derived estimates of phytoplankton size structure are in good agreement with corresponding in situ measurements and also capture the spatial variability related to regional mesoscale dynamics. Our analysis reveals that, for the estimation of Chl-a in the two size classes, the model performs comparably or in some cases better, to validations in other oceanic regions. Our model parameterisation will be useful for future studies on the seasonal and interannual variability of phytoplankton size classes in the Red Sea, which may ultimately be relevant for understanding trophic linkages between phytoplankton size structure and fisheries, and the development of marine management strategies.
  • Factors Regulating the Relationship Between Total and Size-Fractionated Chlorophyll-a in Coastal Waters of the Red Sea.

    Brewin, Robert J W; Moran, Xose Anxelu G.; Raitsos, Dionysios E; Gittings, John A; Calleja Cortes, Maria de Lluch; Viegas, Miguel; Ansari, Mohd Ikram; Al-otaibi, Najwa Aziz; Huete-Stauffer, Tamara M; Hoteit, Ibrahim (Frontiers in microbiology, Frontiers Media SA, 2019-09-26) [Article]
    Phytoplankton biomass and size structure are recognized as key ecological indicators. With the aim to quantify the relationship between these two ecological indicators in tropical waters and understand controlling factors, we analyzed the total chlorophyll-a concentration, a measure of phytoplankton biomass, and its partitioning into three size classes of phytoplankton, using a series of observations collected at coastal sites in the central Red Sea. Over a period of 4 years, measurements of flow cytometry, size-fractionated chlorophyll-a concentration, and physical-chemical variables were collected near Thuwal in Saudi Arabia. We fitted a three-component model to the size-fractionated chlorophyll-a data to quantify the relationship between total chlorophyll and that in three size classes of phytoplankton [pico- (<2 μm), nano- (2-20 μm) and micro-phytoplankton (>20 μm)]. The model has an advantage over other more empirical methods in that its parameters are interpretable, expressed as the maximum chlorophyll-a concentration of small phytoplankton (pico- and combined pico-nanophytoplankton, Cpm and Cp,nm , respectively) and the fractional contribution of these two size classes to total chlorophyll-a as it tends to zero (D p and D p,n ). Residuals between the model and the data (model minus data) were compared with a range of other environmental variables available in the dataset. Residuals in pico- and combined pico-nanophytoplankton fractions of total chlorophyll-a were significantly correlated with water temperature (positively) and picoeukaryote cell number (negatively). We conducted a running fit of the model with increasing temperature and found a negative relationship between temperature and parameters Cpm and Cp,nm and a positive relationship between temperature and parameters D p and D p,n . By harnessing the relative red fluorescence of the flow cytometric data, we show that picoeukaryotes, which are higher in cell number in winter (cold) than summer (warm), contain higher chlorophyll per cell than other picophytoplankton and are slightly larger in size, possibly explaining the temperature shift in model parameters, though further evidence is needed to substantiate this finding. Our results emphasize the importance of knowing the water temperature and taxonomic composition of phytoplankton within each size class when understanding their relative contribution to total chlorophyll. Furthermore, our results have implications for the development of algorithms for inferring size-fractionated chlorophyll from satellite data, and for how the partitioning of total chlorophyll into the three size classes may change in a future ocean.
  • Generalized Extreme Value Statistics, Physical Scaling and Forecasts of Oil Production in the Bakken Shale

    Saputra, Wardana; Kirati, Wissem; Patzek, Tadeusz (Energies, MDPI AG, 2019-09-25) [Article]
    We aim to replace the current industry-standard empirical forecasts of oil production from hydrofractured horizontal wells in shales with a statistically and physically robust, accurate and precise method of matching historic well performance and predicting well production for up to two more decades. Our Bakken oil forecasting method extends the previous work on predicting fieldwide gas production in the Barnett shale and merges it with our new scaling of oil production in the Bakken. We first divide the existing 14,678 horizontal oil wells in the Bakken into 12 static samples in which reservoir quality and completion technologies are similar. For each sample, we use a purely data-driven non-parametric approach to arrive at an appropriate generalized extreme value (GEV) distribution of oil production from that sample’s dynamic well cohorts with at least 1 , 2 , 3 , ⋯ years on production. From these well cohorts, we stitch together the P50, P10, and P 90 statistical well prototypes for each sample. These statistical well prototypes are conditioned by well attrition, hydrofracture deterioration, pressure interference, well interference, progress in technology, and so forth. So far, there has been no physical scaling. Now we fit the parameters of our physical scaling model to the statistical well prototypes, and obtain a smooth extrapolation of oil production that is mechanistic, and not just a decline curve. At late times, we add radial inflow from the outside. By calculating the number of potential wells per square mile of each Bakken region (core and noncore), and scheduling future drilling programs, we stack up the extended well prototypes to obtain the plausible forecasts of oil production in the Bakken. We predict that Bakken will ultimately produce 5 billion barrels of oil from the existing wells, with the possible addition of 2 and 6 billion barrels from core and noncore areas, respectively.
  • Optimal 3D trajectory planning for AUVs using ocean general circulation models

    Albarakati, Sultan Saud; Lima, Ricardo; Giraldi, Loic; Hoteit, Ibrahim; Knio, Omar (Ocean Engineering, Elsevier Ltd, 2019-09-15) [Article]
    In this paper, we consider the autonomous underwater vehicle (AUV) trajectory planning problem under the influence of a realistic 3D current as simulated by an ocean general circulation model (OGCM). Attention is focused on the case of a deterministic steady OGCM field, which is used to specify data for both the ocean current and for ocean bathymetry. A general framework for optimal trajectory planning is developed for this setting, accounting for the 3D ocean current and for static obstacle avoidance constraints. A nonlinear programming approach is used for this purpose, which leads to a low complexity discrete-time model that can be efficiently solved. To demonstrate the efficiency of the model, we consider the optimal time trajectory planning of an AUV operating in the Red Sea and Gulf of Aden, with velocity, and bathymetric data provided by an eddy-resolving MITgcm. Different optimal-time trajectory planning scenarios are implemented to demonstrate the capabilities of the model to identify trajectories that adapt to favorable and adverse currents and to avoid obstacles corresponding to a complex bathymetry environment. The simulations are also used to evaluate the performance of the proposed approach, and to illustrate the application of advanced visualization tools to interpret the model predictions.
  • Multiple stressor effects on coral reef ecosystems.

    Ellis, J I; Jamil, Tahira; Anlauf, Holger; Coker, Darren James; Curdia, Joao; Hewitt, J; Jones, B H; Krokos, Georgios; Kürten, Benjamin; Prasad, D; Roth, Florian; Carvalho, Susana; Hoteit, Ibrahim (Global change biology, Wiley, 2019-09-05) [Article]
    Global climate change has profound implications on species distributions and ecosystem functioning. In the coastal zone, ecological responses may be driven by various biogeochemical and physical environmental factors. Synergistic interactions can occur when the combined effects of stressors exceed their individual effects. The Red Sea, characterized by strong gradients in temperature, salinity, and nutrients along the latitudinal axis provides a unique opportunity to study ecological responses over a range of these environmental variables. Using multiple linear regression models integrating in situ, satellite and oceanographic data, we investigated the response of coral reef taxa to local stressors and recent climate variability. Taxa and functional groups responded to a combination of climate (temperature, salinity, air-sea heat fluxes, irradiance, wind speed), fishing pressure and biogeochemical (chlorophyll a and nutrients - phosphate, nitrate, nitrite) factors. The regression model for each species showed interactive effects of climate, fishing pressure and nutrient variables. The nature of the effects (antagonistic or synergistic) was dependent on the species and stressor pair. Variables consistently associated with the highest number of synergistic interactions included heat flux terms, temperature, and wind speed followed by fishing pressure. Hard corals and coralline algae abundance were sensitive to changing environmental conditions where synergistic interactions decreased their percentage cover. These synergistic interactions suggest that the negative effects of fishing pressure and eutrophication may exacerbate the impact of climate change on corals. A high number of interactions were also recorded for algae, however for this group, synergistic interactions increased algal abundance. This study is unique in applying regression analysis to multiple environmental variables simultaneously to understand stressor interactions in the field. The observed responses have important implications for understanding climate change impacts on marine ecosystems and whether managing local stressors, such as nutrient enrichment and fishing activities, may help mitigate global drivers of change. This article is protected by copyright. All rights reserved.
  • Darcy-scale phase equilibrium modeling with gravity and capillarity

    Sun, Shuyu (Journal of Computational Physics, Elsevier BV, 2019-09-05) [Article]
    The modeling of multiphase fluid mixture and its flow in porous media is of great interest in the field of reservoir simulation. In this paper, we formulate a novel energy-based framework to model multi-component two-phase fluid systems at equilibrium. Peng-Robinson equation of state (EOS) is used to model the bulk properties of each phase, though our framework works well also with other equations of state. Our model reduces to the conventional compositional grading if restricted to one spatial vertical dimension together with the assumption of monodisperse pore-size distribution (all pores being one size). However, our model can be combined with a general distribution of pore size, which can generate interesting behaviors of capillarity in porous media. In particular, the model can be used to predict the capillary pressure of two-phase fluid as a function of saturation, with a given pore-size distribution. This model is the quantitative study of the first time in the literature for the capillarity of a two-phase fluid with partial miscibility. We proposed an unconditional-stable energy-decay numerical algorithm based on convex-concave splitting, which has been demonstrated to be both robust and efficient using numerical examples. To verify our model, we simulate the compositional grading of a binary fluid mixture consisting of carbon dioxide and normal decane. To demonstrate powerful features of our model, we provide an interesting example of fluid mixture in a porous medium with wide pore size distribution, where the competition of capillarity and gravity is observed. This work represents the first effort in the literature that rigorously incorporates capillarity and gravity effects into EOS-based phase equilibrium modeling.
  • A Lagrangian Method for Extracting Eddy Boundaries in the Red Sea and the Gulf of Aden

    Friederici, Anke; Mahamadou Kele, Habib Toye; Hoteit, Ibrahim; Weinkauf, Tino; Theisel, Holger; Hadwiger, Markus (IEEE, 2019-09-05) [Conference Paper]
    Mesoscale ocean eddies play a major role for both the intermixing of water and the transport of biological mass. This makes the identification and tracking of their shape, location and deformation over time highly important for a number of applications. While eddies maintain a roughly circular shape in the free ocean, the narrow basins of the Red Sea and Gulf of Aden lead to the formation of irregular eddy shapes that existing methods struggle to identify. We propose the following model: Inside an eddy, particles rotate around a common core and thereby remain at a constant distance under a certain parametrization. The transition to the more unpredictable flow on the outside can thus be identified as the eddy boundary. We apply this algorithm on a realistic simulation of the Red Sea circulation, where we are able to identify the shape of irregular eddies robustly and more coherently than previous methods. We visualize the eddies as tubes in space-time to enable the analysis of their movement and deformation over several weeks.
  • Influence of ring faulting in localizing surface deformation at subsiding calderas

    Liu, Yuan-Kai; Ruch, Joel; Vasyura-Bathke, Hannes; Jonsson, Sigurjon (Earth and Planetary Science Letters, Elsevier BV, 2019-09-04) [Article]
    Caldera unrest can lead to major volcanic eruptions. Analysis of subtle subsidence or inflation at calderas helps understanding of their subsurface volcanic processes and related hazards. Several subsiding calderas have shown similar patterns of ground deformation composed of broad subsidence affecting the entire volcanic edifice and stronger localized subsidence focused inside the caldera. Physical models of internal deformation sources used to explain these observations typically consist of two magma reservoirs at different depths in an elastic half-space. However, such models ignore important subsurface structures, such as ring faults, that may influence the deformation pattern. Here we use both analog subsidence experiments and boundary element modeling to study the three-dimensional geometry and kinematics of caldera subsidence processes, evolving from an initial downsag to a later collapse stage. We propose that broad subsidence is mainly caused by volume decrease within a single magma reservoir, whereas buried ring-fault activity localizes the deformation within the caldera. Omitting ring faulting in physical models of subsiding calderas and using multiple point/sill-like sources instead can result in erroneous estimates of magma reservoir depths and volume changes.
  • Controlling Factors of Degassing in Crosslinked Polyethylene Insulated Cables

    Youn, Dong Joon; Li, Jingfa; Livazovic, Sara; Sun, Yabin; Sun, Shuyu (Polymers, MDPI AG, 2019-09-03) [Article]
    Here, we analyze the degassing process of a byproduct (methane) formed during the peroxide-induced crosslinking of polyethylene. A diffusion model based on Fick’s law is used to obtain the controlling factors of degassing in a crosslinked polyethylene (XLPE) insulated power cable (132 kV with 18 mm of insulation). We quantitatively analyze different scenarios of the diffusion of methane through the XLPE insulation and two semiconductor layers under various in situ degassing conditions. The analyzed degassing conditions include heat transfer and its effect on the diffusion properties, the different transport and boundary conditions due to the free spaces within the cable conductor, and the nonuniform distribution of methane concentrations within the insulation layers. Our simulation results clearly demonstrate that the free spaces between the copper strands in the cable conductor significantly affect the degassing efficiency. However, the temperature-diffusion coupling has a relatively minor effect on the overall degassing efficiency due to the rapid temperature increase of the polymer layers during the initial stages of degassing. Moreover, we find that the nonuniform distribution of methane in the initial stages also plays an important role in degassing in the cable, but this effect varies significantly during the degassing process.
  • Impact of Dynamical Representational Errors on an Indian Ocean Ensemble Data Assimilation System

    Sanikommu, Siva Reddy; Benerjee, Deep Sankar; Baduru, Balaji; Paul, Biswamoy; Paul, Arya; Chakraborty, Kunal; Hoteit, Ibrahim (Quarterly Journal of the Royal Meteorological Society, Wiley, 2019-08-27) [Article]
    This study investigates the impact of dynamical representational error (RE) on the analysis of an ocean ensemble Kalman filter-based data assimilation system, LETKF-ROMS (Local Ensemble Transform Kalman Filter - Regional Ocean Modeling system) configured for the Indian Ocean and assimilating in-situ temperature and salinity observations from Argo. Three different approaches to account for the RE are studied and inter-compared: (i) static RE (varies in horizontal and vertical direction), (ii) dynamic RE (varies in space and time) estimated from concurrent observations, and (iii) dynamic RE estimated using concurrent high resolution model outputs. RE estimated from the model outputs exhibits rich spatial and temporal variability with an estimated temporal mean RE for temperature below 0.5 °C and 0.2 °C in the surface and deep layers, respectively, and reaching up to 1°C in the thermocline layers. The region encompassing the Great Whirl displays a large seasonal variability reaching up to 0.8°C, and the South Equatorial Current (SEC)a large inter-annual variability reaching up to 0.4°C. Neglecting such spatio-temporal variations of RE and assimilating with a static RE limited the benefits of assimilation by entertaining over-fitting issues that caused degradations in the Bay of Bengal, the western parts of the Arabian Sea, and the equatorial Indian ocean. Assimilating with the observations-based dynamic RE improved the results in these regions, but the best performances were obtained with the configuration using the model-based dynamic RE, which yielded further improvements (e.g. reduction of sea surface height root-mean-square-errors reaches 30% with respect to the observations-based dynamic RE). The latter also better handled the rich spatial variability regions and areas not well sampled by the observations. Improved estimates of the spatial and temporal variations of RE helped to better exploit the assimilated observations and provided enhanced analyses less prone to assimilation shocks.
  • Dust emission modeling using a new high-resolution dust source function in WRF-Chem with implications for air quality

    Parajuli, Sagar P.; Stenchikov, Georgiy L.; Ukhov, Alexander; Kim, Hyunglok (Journal of Geophysical Research: Atmospheres, American Geophysical Union (AGU), 2019-08-23) [Article]
    Air-borne dust affects all aspects of human life. The sources of dust have high spatial variation and a better quantification of dust emission helps to identify remediation measures. Orographic and statistical source functions allow a better estimation of dust emission fluxes in coarse-scale modeling, but a high-resolution source function is necessary to represent the highly heterogeneous nature of dust sources at the finer scale. Here we use a newly developed high-resolution (~ 500 m) source function in WRF-Chem to simulate dust emission over the Middle East and North Africa, and evaluate our simulated results against observations. Using a 4 km grid spacing, we also simulate the emission and transport of dust originating from the Tigris-Euphrates basin, one of the most important regional dust sources, and quantify the effects of this source on the air quality of the entire Arabian Peninsula. Results show that the use of new source function effectively represents the key dust sources, and provides reasonable estimates of dust optical depth and concentrations. We find that the atmospheric dust originating from the Tigris-Euphrates basin alone exceeds the PM10 air quality standards in several downwind cities. Our results have broader environmental implications and indicate that the mobilization of depleted uranium (DU) deposited in Kuwait and Southern Iraq during the Gulf War (1991) could potentially affect the urban centers over the peninsula, albeit in low concentrations. Our results suggest that an integrated and coordinated management of the Tigris-Euphrates basin is necessary to maintain good air quality across the Arabian Peninsula.
  • Advances in Gaussian random field generation: a review

    Liu, Yang; Li, Jingfa; Sun, Shuyu; Yu, Bo (Computational Geosciences, Springer Science and Business Media LLC, 2019-08-05) [Article]
    Gaussian (normal) distribution is a basic continuous probability distribution in statistics, it plays a substantial role in scientific and engineering problems that related to stochastic phenomena. This paper aims to review state-of-the-art of Gaussian random field generation methods, their applications in scientific and engineering issues of interest, and open-source software/packages for Gaussian random field generation. To this end, first, we briefly introduce basic mathematical concepts and theories in the Gaussian random field, then seven commonly used Gaussian random field generation methods are systematically presented. The basic idea, mathematical framework of each generation method are introduced in detail and comparisons of these methods are summarized. Then, representative applications of the Gaussian random field in various areas, especially of engineering interest in recent two decades, are reviewed. For readers’ convenience, four representative example codes are provided, and several relevant up-to-date open-source software and packages that freely available from the Internet are introduced.
  • Parallel reservoir simulators for fully implicit complementarity formulation of multicomponent compressible flows

    Yang, Haijian; Sun, Shuyu; Li, Yiteng; Yang, Chao (Computer Physics Communications, Elsevier B.V., 2019-07-30) [Article]
    The numerical simulation of multicomponent compressible flow in porous media is an important research topic in reservoir modeling. Traditional semi-implicit methods for such problems are usually conditionally stable, suffer from large splitting errors, and may accompany with violations of the boundedness requirement of the numerical solution. In this study we reformulate the original multicomponent equations into a nonlinear complementarity problem and discretize it using a fully implicit finite element method. We solve the resultant nonsmooth nonlinear system of equations arising at each time step by a parallel, scalable, and nonlinearly preconditioned semismooth Newton algorithm, which is able to preserve the boundedness of the solution and meanwhile treats the possibly imbalanced nonlinearity of the system. Some numerical results are presented to demonstrate the robustness and efficiency of the proposed algorithm on the Tianhe-2 supercomputer for both standard benchmarks as well as realistic problems in highly heterogeneous media.
  • Structure, Thermodynamics, and Dynamics of Thin Brine Films in Oil-Brine-Rock Systems.

    Fang, Chao; Sun, Shuyu; Qiao, Rui (Langmuir : the ACS journal of surfaces and colloids, American Chemical Society (ACS), 2019-07-23) [Article]
    Thin brine films are ubiquitous in oil-brine-rock systems such as oil reservoirs and play a crucial role in applications such as enhanced oil recovery. We report the results of molecular simulations of brine films that are confined between model oil (n-decane) and rock (neutral or negatively charged quartz slabs), with a focus on their structure, electrical double layers (EDLs), disjoining pressure, and dynamics. As brine films are squeezed to ∼0.7 nm (∼3 water molecule layers), the structures of the water-rock and water-oil interfaces change only marginally, except that the oil surface above the brine film becomes less diffuse. As the film is thinned from ∼1.0 to ∼0.7 nm, ions are enriched (depleted) near the rock (oil) surface, especially at a bath ion concentration of 0.1 M. These changes are caused primarily by the reduced dielectric screening of water and the weakened ion hydration near water-oil interfaces and, to a smaller extent, by the increased confinement. When the brine film is ∼1.0 nm thick, hydration and EDL forces contribute to the disjoining pressure between the charged rock and the oil. The EDL forces are reduced substantially as the ion concentration increases from 0.1 to 1.0 M, and the magnitude of the reduction is close to that predicted by the Poisson-Boltzmann equation. When the brine film is thinned from ∼1.0 to ∼0.7 nm, the disjoining pressure increases by ∼10 MPa, which is mostly due to an increase in the hydration forces. The first layer of water on the rock surface is nearly stagnant, even in 0.74 nm-thick brine films, whereas the viscosity of water beyond the first layer is bulk-like, and the slip coefficient of oil-water interfaces is close to that under unconfined conditions. The insights that are obtained here help lay a foundation for the rational application of technologies such as low-salinity waterflooding.
  • Structural mapping of dike-induced faulting in harrat lunayyir (saudi arabia) by using high resolution drone imagery

    Trippanera, Daniele; Ruch, Joel; Passone, Luca; Jonsson, Sigurjon (Frontiers in Earth Science, Frontiers Media S.A.info@frontiersin.org, 2019-07-17) [Article]
    Dike intrusions produce faulting at the surface along with seismic swarms and possible eruptions. Understanding the geometry and kinematics of dike-induced fractures can provide relevant information on what controls magma emplacement and the associated hazards. Here, we focus on the Harrat Lunayyir volcanic field (western Saudi Arabia), where in 2009 a dike intrusion formed a NNW-SSE oriented, ten-kilometer-long and up to one-meter deep graben. This widens from ∼2 km in the SSE to ∼5 km in the NNW, showing a well-defined border normal fault to the west but a diffused fracture zone to the east. We conducted a fixed-wing drone survey to create high resolution (∼3.4 cm) ortho-rectified images and DEMs of the western fault and of a portion of the eastern fracture zone to determine the fracture geometry and kinematics. We then integrated these results with field observations and InSAR data from the 2009 intrusion. Both fault zones contain smaller segments (hundreds of meters long) consisting of normal faults and extension fractures, showing two dominant orientation patterns: NNW-SSE (N330° ± 10°) and NW-SE (N300° ± 10°). The NNW-ESE oriented segments are sub-parallel to the inferred 2009 dike strike (N340°), to pre-historical Harrat Lunayyir eruptive fissures (N330°) and to the overall Red Sea axis (N330°). This suggests that these segments reflect the present-day off-rift stress field close to the Red Sea shoulder. However, the NW-SE oriented segments are oblique to this pattern and exhibit en–echelon structures, suggesting different processes such as: (1) a transfer (or soft-linkage) between dike-parallel fault segments, (2) a topographic control on the fault propagation and (3) a possible reactivation of inherited regional faults. Vertical fault offsets obtained by the drone survey along the western fault vary with the local lithology and these data are not consistent everywhere with the offsets derived from the 2009 InSAR measurements. Field evidence within lava flows also shows the occurrence of previous slipping event(s) on the fault before the 2009 intrusion. Collectively, we suggest that the mismatch between the drone and InSAR datasets is related to the different spatial and temporal resolutions offered by the two techniques.
  • Enhanced flood forecasting through ensemble data assimilation and joint state-parameter estimation

    Ziliani, Matteo G.; Ghostine, Rabih; Ait-El-Fquih, Boujemaa; McCabe, Matthew; Hoteit, Ibrahim (Journal of Hydrology, Elsevier BV, 2019-07-12) [Article]
    Accurate water level forecasts during flood events are crucial to mitigate the loss of human lives and economic damages. However, the accuracy of flood models can be affected by various factors, including the complexity of the terrain geometry and bathymetry, imperfect physics as well as uncertainties in the inflows and parameters. This paper describes a practical implementation of an ensemble Kalman filter (EnKF) based data assimilation system that is aimed towards enhancing the forecasting skill of flood models. The system was implemented and tested with a real world dam break flood, based on the experimentally scaled Toce River valley flood that occurred on July 8th, 1996. Water depth data are available for assimilation from a network of 21 sensors distributed across the domain. Our results demonstrate that assimilating data into the flood model significantly improves the model prediction by up to 90% after assimilation and 60% during forecasting. Assimilating the data more frequently significantly enhances the system performances. Estimating the two-dimensional Manning coefficient together with the model’s dynamical variables (water depth and velocities) further improves the model prediction skill. Overall, our results suggest that assimilating data into the flood model, while jointly inferring the state and (poorly known) parameters, using an EnKF may provide an efficient framework for developing an operational flood forecasting system.
  • Efficient Dynamical Downscaling of General Circulation Models Using Continuous Data Assimilation

    Desamsetti, Srinivas; Dasari, Hari Prasad; Langodan, Sabique; Titi, Edriss S.; Knio, Omar; Hoteit, Ibrahim (Quarterly Journal of the Royal Meteorological Society, Wiley, 2019-07-09) [Article]
    Continuous data assimilation (CDA) is successfully implemented for the first timefor efficient dynamical downscaling of a global atmospheric reanalysis. A com-parison of the performance of CDA with the standard grid and spectral nudgingtechniques for representing long- and short-scale features in the downscaled fieldsusing the Weather Research and Forecast (WRF) model is further presented andanalysed. The WRF model is configured at 0.25◦×0.25◦horizontal resolution andis driven by 2.5◦×2.5◦initial and boundary conditions from NCEP/NCAR reanal-ysis fields. Downscaling experiments are performed over a one-month period inJanuary 2016. The similarity metric is used to evaluate the performance of thedownscaling methods for large (2,000 km) and small (300 km) scales. Similarityresults are compared for the outputs of the WRF model with different downscalingtechniques, NCEP/NCAR reanalysis, and NCEP Final Analysis (FNL, available at0.25◦×0.25◦horizontal resolution). Both spectral nudging and CDA describe betterthe small-scale features compared to grid nudging. The choice of the wave number iscritical in spectral nudging; increasing the number of retained frequencies generallyproduced better small-scale features, but only up to a certain threshold after which itssolution gradually became closer to grid nudging. CDA maintains the balance of thelarge- and small-scale features similar to that of the best simulation achieved by thebest spectral nudging configuration, without the need of a spectral decomposition.The different downscaled atmospheric variables, including rainfall distribution, withCDA is most consistent with the observations. The Brier skill score values furtherindicate that the added value of CDA is distributed over the entire model domain.The overall results clearly suggest that CDA provides an efficient new approach fordynamical downscaling by maintaining better balance between the global model andthe downscaled fields
  • Geostatistical modeling to capture seismic-shaking patterns from earthquake-induced landslides

    Lombardo, Luigi; Bakka, Haakon; Tanyas, Hakan; Westen, Cees; Mai, Paul Martin; Huser, Raphaël (Journal of Geophysical Research: Earth Surface, American Geophysical Union (AGU), 2019-07-05) [Article]
    We investigate earthquake-induced landslides using a geostatistical model featuring a latent spatial effect (LSE). The LSE represents the spatially structured residuals in the data, which remain after adjusting for covariate effects. To determine whether the LSE captures the residual signal from a given trigger, we test the LSE in reproducing the pattern of seismic shaking from the distribution of seismically induced landslides, without prior knowledge of the earthquake being included in the model. We assessed the landslide intensity, i.e., the expected number of landslides per mapping unit, for the area in which landslides triggered by the Wenchuan and Lushan earthquakes overlap. We examined this area to test our method on landslide inventories located in near and far fields of the earthquake. We generated three models for both earthquakes: i) seismic parameters only (proxy for the trigger); ii}) the LSE only; and iii) both seismic parameters and the LSE. The three configurations share the same morphometric covariates. This allowed us to study the LSE pattern and assess whether it approximated the seismic effects. Our results show that the LSE reproduced the shaking patterns for both earthquakes. In addition, the models including the LSE perform better than conventional models featuring seismic parameters only. Due to computational limitations we carried out a detailed analysis for a relatively small area (2112 km2), using a dataset with higher spatial resolution. Results were consistent with those of a subsequent analysis for a larger area (14648 km2) using coarser resolution data.
  • A fully implicit constraint-preserving simulator for the black oil model of petroleum reservoirs

    Yang, Haijian; Sun, Shuyu; Li, Yiteng; Yang, Chao (Journal of Computational Physics, Elsevier BV, 2019-07-05) [Article]
    Due to the rapid advancement of supercomputing resource, there is a growing interest in developing parallel algorithms for the large-scale reservoir simulation. In this paper, we present a parallel and fully implicit simulator for the black oil model based on the variational inequality (VI) framework, which can be used to enforce important mathematical and physical properties to obtain accurate constraint-preserving solutions. In other words, this framework ensures the predicted solution to stay within the physical range. In the proposed approach, the black oil model is reformulated as a variational inequality system that naturally satisfies the basic boundedness requirement of the solution, and then a fully implicit finite volume method is applied to discretize the model equations. In addition to that, a number of nonlinear and linear fast solver technologies, including a variant of inexact Newton methods and the domain decomposition based preconditioners, are employed to guarantee the robustness and parallel scalability of the simulator. A particular emphasis of the proposed framework is placed on the parallel and algorithmic performance of the variational inequality approach across large-scale and heterogeneous problems. Several numerical results pertaining to the problems in one, two and three dimensions are presented to illustrate the efficiency, robustness, and the overall performance of the fully implicit constraint-preserving simulator.
  • Generalized Extreme Value Statistics, Physical Scaling and Forecasts of Gas Production in the Barnett Shale

    Patzek, Tadeusz; Saputra, Wardana; Kirati, Wissem; Marder, Michael (American Chemical Society (ACS), 2019-06-27) [Preprint]
    We develop a method of predicting field-wide gas (or oil) production from unconventional reservoirs, using the Barnett shale as an illustration. Our method has six steps. First, divide a field of interest (here Barnett) into geographic/depositional regions, where -- upon statistical testing -- gas and/or oil production are statistically uniform. Second, in each region i, fit a generalized extreme value distribution to every cohort of gas/oil wells with 1,2,…,ni years on production. Third, obtain accurate estimates of uncertainties in the distribution parameters for each regional well cohort. As a result, obtain ni points for the stable mean (P50) well prototypes for each region i, and the corresponding high/low (P10/P90) bounds on well production. Fourth, by adjusting the producible gas/oil in place and pressure interference times between the adjacent hydrofractures, fit each statistical P50 well prototype with a physics-based scaling curve that also accounts for late-time external gas inflow. The physics-scaled well prototypes now extend 10-20 years into the future. Fifth, for each region, time-shift the dimensional, scaled well prototype and multiply it by the number of well completions during each year of field production. Add the production from all regions to match the past field production and predict decline of all wells up to current time. These well productivity estimates are more accurate and better quantified than anything a production decline curve analysis might yield. Sixth, by assuming different future drilling programs in each region, predict field production futures. We hope that the US Securities and Exchange Commission will adopt our robust, transparent approach as a new standard for booking gas (and oil) reserves in shale wells.

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