Survey decomposition: A scalable framework for 3D controlled-source electromagnetic inversion

Geophysics ◽  
2016 ◽  
Vol 81 (2) ◽  
pp. E69-E87 ◽  
Author(s):  
Dikun Yang ◽  
Douglas W. Oldenburg
Keyword(s):  
Spatial Scales ◽  
Data Set ◽  
Low Frequencies ◽  
Long Wavelength ◽  
Time Stepping ◽  
Large Loop ◽  
Trade Offs ◽  
Em Induction ◽  
Computationally Intensive ◽  
And Inversion

Numerical modeling and inversion of electromagnetic (EM) data is a computationally intensive task. To achieve efficiency, we have developed algorithms that were constructed from a smallest practical computational unit. This “atomic” building block, which yields the solution of Maxwell’s equations for a single time or frequency datum due to an infinitesimal current or magnetic dipole, is a self-contained EM problem that can be solved independently and inexpensively on a single core of CPU. Any EM data set can be composed from these units through assembling or superposition. This approach takes advantage of the rapidly expanding capability of multiprocessor computation. Our decomposition has allowed us to handle the computational complexity that arises because of the physical size of the survey, the large number of transmitters, and the large range of time or frequency in a data set; we did this by modeling every datum separately on customized local meshes and local time-stepping schemes. The counterpart to efficiency with atomic decomposition was that the number of independent subproblems could become very large. We have realized that not all of the data need to be considered at all stages of the inversion. Rather, the data can be significantly downsampled at late times or low frequencies and at the early stages of inversion when only long-wavelength signals are sought. We have therefore developed a random data subsampling approach, in conjunction with cross-validation, that selects data in accordance to the spatial scales of the EM induction and the degree of regularization. Alternatively, for many EM surveys, the atomic units can be combined into larger subproblems, thus reducing the number of subproblems needed. These trade-offs were explored for airborne and ground large-loop systems with specific survey configurations being considered. Our synthetic and field examples showed that the proposed framework can produce 3D inversion results in uncompromised quality in a more scalable manner.

Variable-depth streamer acquisition: Broadband data for imaging and inversion

Geophysics ◽  
2013 ◽  
Vol 78 (2) ◽  
pp. WA27-WA39 ◽  
Author(s):  
Robert Soubaras ◽  
Yves Lafet
Keyword(s):  
Signal To Noise Ratio ◽  
Real Data ◽  
Variable Depth ◽  
Constant Depth ◽  
Data Set ◽  
Low Frequencies ◽  
Optimal Receiver ◽  
Amplitude Versus Offset ◽  
Elastic Inversion ◽  
And Inversion

Conventional marine acquisition uses a streamer towed at a constant depth. The resulting receiver ghost notch gives the maximum recoverable frequency. To push this limit, the streamer must be towed at a quite shallow depth, but this compromises the low frequencies. Variable-depth streamer (VDS) acquisition is an acquisition technique aimed at achieving the best possible signal-to-noise ratio at low frequencies by towing the streamer very deeply, but by using a depth profile varying with offset in order not to limit the high-frequency bandwidth by notches as in conventional constant-depth streamer acquisition. The idea is to use notch diversity, each receiver having a different notch, so that the final result, combining different receivers, will have no notches. The key step to process VDS acquisitions is the receiver deghosting. We found that the optimal receiver deghosting, instead of being a preprocessing step, should be done postimaging, by using a dual-input, migration and mirror migration, and a new joint deconvolution algorithm that produces a 3D real amplitude deghosted output. This method can be applied poststack, the inputs being the migration and mirror migration images and the output being the deghosted image. Using a multichannel joint deconvolution, the inputs are the migrated and mirror migrated image gathers and the outputs are the prestack deghosted image gathers. This method preserves the amplitude-versus-offset behavior, as the deghosted output can be seen on synthetic examples to be equal to a reference computed by migrating the data modeled without any reflecting water surface. A real data set was used to illustrate this method, and another one was used to check the possibility of performing prestack elastic inversion on the deghosted gathers.

scholarly journals Responses of Vertebrate Wildlife to Oil and Natural Gas Development: Patterns and Frontiers

2021 ◽  
Author(s):  
A. D. Chalfoun
Keyword(s):  
Natural Gas ◽  
Anthropogenic Activities ◽  
Spatial Scales ◽  
Habitat Type ◽  
Population Level ◽  
Low Frequencies ◽  
Natural Gas Development ◽  
The Usa ◽  
Oil And Natural Gas

Abstract Purpose of Review Anthropogenic activities can lead to the loss, fragmentation, and alteration of wildlife habitats. I reviewed the recent literature (2014–2019) focused on the responses of avian, mammalian, and herpetofaunal species to oil and natural gas development, a widespread and still-expanding land use worldwide. My primary goals were to identify any generalities in species’ responses to development and summarize remaining gaps in knowledge. To do so, I evaluated the directionality of a wide variety of responses in relation to taxon, location, development type, development metric, habitat type, and spatiotemporal aspects. Recent Findings Studies (n = 70) were restricted to the USA and Canada, and taxonomically biased towards birds and mammals. Longer studies, but not those incorporating multiple spatial scales, were more likely to detect significant responses. Negative responses of all types were present in relatively low frequencies across all taxa, locations, development types, and development metrics but were context-dependent. The directionality of responses by the same species often varied across studies or development metrics. Summary The state of knowledge about wildlife responses to oil and natural gas development has developed considerably, though many biases and gaps remain. Studies outside of North America and that focus on herpetofauna are lacking. Tests of mechanistic hypotheses for effects, long-term studies, assessment of response thresholds, and experimental designs that isolate the effects of different stimuli associated with development, remain critical. Moreover, tests of the efficacy of habitat mitigation efforts have been rare. Finally, investigations of the demographic effects of development across the full annual cycle were absent for non-game species and are critical for the estimation of population-level effects.

scholarly journals Fundamental resource trade-offs for encoded distributed optimization

2020 ◽  
Author(s):  
A Salman Avestimehr ◽  
Seyed Mohammadreza Mousavi Kalan ◽  
Mahdi Soltanolkotabi
Keyword(s):  
Computational Time ◽  
Massive Data ◽  
Data Sets ◽  
Massive Data Sets ◽  
Computational Framework ◽  
Data Set ◽  
Trade Offs ◽  
Major Bottleneck ◽  
Computing Environments ◽  
Analyze Data

Abstract Dealing with the shear size and complexity of today’s massive data sets requires computational platforms that can analyze data in a parallelized and distributed fashion. A major bottleneck that arises in such modern distributed computing environments is that some of the worker nodes may run slow. These nodes a.k.a. stragglers can significantly slow down computation as the slowest node may dictate the overall computational time. A recent computational framework, called encoded optimization, creates redundancy in the data to mitigate the effect of stragglers. In this paper, we develop novel mathematical understanding for this framework demonstrating its effectiveness in much broader settings than was previously understood. We also analyze the convergence behavior of iterative encoded optimization algorithms, allowing us to characterize fundamental trade-offs between convergence rate, size of data set, accuracy, computational load (or data redundancy) and straggler toleration in this framework.

scholarly journals Economic and ecological trade-offs of agricultural specialization at different spatial scales

2016 ◽  
Vol 122 ◽  
pp. 111-120 ◽  
Author(s):  
Stephan Klasen ◽  
Katrin M. Meyer ◽  
Claudia Dislich ◽  
Michael Euler ◽  
Heiko Faust ◽  
...  
Keyword(s):  
Spatial Scales ◽  
Trade Offs

Demographic life history traits of reproductive natterjack toads (Bufo calamita) vary between northern and southern latitudes

2006 ◽  
Vol 27 (3) ◽  
pp. 365-375 ◽  
Author(s):  
Delfi Sanuy ◽  
Christoph Leskovar ◽  
Neus Oromi ◽  
Ulrich Sinsch
Keyword(s):  
Life History ◽  
Life History Traits ◽  
Large Female ◽  
Breeding Period ◽  
Female Size ◽  
Data Set ◽  
Bufo Calamita ◽  
Trade Offs ◽  
Age Variation ◽  
The Cost

AbstractDemographic life history traits were investigated in three Bufo calamita populations in Germany (Rhineland-Palatinate: Urmitz, 50°N; 1998-2000) and Spain (Catalonia: Balaguer, Mas de Melons, 41°N; 2004). We used skeletochronology to estimate the age as number of lines of arrested growth in breeding adults collected during the spring breeding period (all localities) and during the summer breeding period (only Urmitz). A data set including the variables sex, age and size of 185 males and of 87 females was analyzed with respect to seven life history traits (age and size at maturity of the youngest first breeders, age variation in first breeders, longevity, potential reproductive lifespan, median lifespan, age-size relationship). Spring and summer cohorts at the German locality differed with respect to longevity and potential reproductive lifespan by one year in favour of the early breeders. The potential consequences on fitness and stability of cohorts are discussed. Latitudinal variation of life history traits was mainly limited to female natterjacks in which along a south-north gradient longevity and potential reproductive lifespan increased while size decreased. These results and a review of published information on natterjack demography suggest that lifetime number of offspring seem to be optimized by locally different trade-offs: large female size at the cost of longevity in southern populations and increased longevity at the cost of size in northern ones.

A framework for the Integrated Assessment of SDG trade-offs in the Sundarbans Biosphere Reserve.

2021 ◽  
Author(s):  
Charlotte Marcinko ◽  
Robert Nicholls ◽  
Tim Daw ◽  
Sugata Hazra ◽  
Craig Hutton ◽  
...  
Keyword(s):  
Environmental Change ◽  
Integrated Assessment ◽  
Spatial Scales ◽  
Strong Dependence ◽  
Management Strategies ◽  
Rural Livelihoods ◽  
Biosphere Reserve ◽  
Integrated Analysis ◽  
Trade Offs ◽  
The Sundarbans

<p>The United Nations Sustainable Development Goals (SDGs) and their corresponding targets are significantly interconnected, with many interactions, synergies and trade-offs between individual goals across multiple temporal and spatial scales.  We propose a framework for the Integrated Assessment Modelling (IAM) of a complex deltaic socio-ecological system in order to analyse such SDG interactions. We focus on the Sundarbans Biosphere Reserve (SBR), India within the Ganges-Brahmaputra-Meghna Delta. It is densely populated with 4.4 million people (2011), high levels of poverty and a strong dependence on rural livelihoods. It is only 50 km from the growing megacity of Kolkata (about 15 million people in 2020). The area also includes the Indian portion of the world’s largest mangrove forest – the Sundarbans – hosting the iconic Bengal Tiger. Like all deltaic systems, this area is subject to multiple drivers of environmental change operating across different scales. The IAM framework is designed to investigate current and future trends in socio-environmental change and explore associated policy impacts, considering a broad range of sub-thematic SDG indicators. Integration is achieved through the soft coupling of multiple sub-models, knowledge and data of relevant environmental and socio-economic processes.  The following elements are explicitly considered: (1) agriculture; (2) aquaculture; (3) mangroves; (4) fisheries; and (5) multidimensional poverty. Key questions that can be addressed include the implications of changing monsoon patterns, trade-offs between agriculture and aquaculture, or the future of the Sundarbans mangroves under sea-level rise and different management strategies, including trade-offs with land use to the north.  The novel high-resolution analysis of SDG interactions allowed by the IAM will provide stakeholders and policy makers the opportunity to prioritize and explore the SDG targets that are most relevant to the SBR and provide a foundation for further integrated analysis.</p>

scholarly journals A multiscale approach to balance trade-offs among dam infrastructure, river restoration, and cost

2018 ◽  
Vol 115 (47) ◽  
pp. 12069-12074 ◽  
Author(s):  
Samuel G. Roy ◽  
Emi Uchida ◽  
Simone P. de Souza ◽  
Ben Blachly ◽  
Emma Fox ◽  
...  
Keyword(s):  
New England ◽  
River Restoration ◽  
Spatial Scales ◽  
Dam Removal ◽  
The United States ◽  
Multiscale Approach ◽  
Funding Policy ◽  
Net Benefit ◽  
Trade Offs ◽  
Aging Infrastructure

Aging infrastructure and growing interests in river restoration have led to a substantial rise in dam removals in the United States. However, the decision to remove a dam involves many complex trade-offs. The benefits of dam removal for hazard reduction and ecological restoration are potentially offset by the loss of hydroelectricity production, water supply, and other important services. We use a multiobjective approach to examine a wide array of trade-offs and synergies involved with strategic dam removal at three spatial scales in New England. We find that increasing the scale of decision-making improves the efficiency of trade-offs among ecosystem services, river safety, and economic costs resulting from dam removal, but this may lead to heterogeneous and less equitable local-scale outcomes. Our model may help facilitate multilateral funding, policy, and stakeholder agreements by analyzing the trade-offs of coordinated dam decisions, including net benefit alternatives to dam removal, at scales that satisfy these agreements.

scholarly journals Resolving ice cloud optical thickness biases between CALIOP and MODIS using infrared retrievals

2016 ◽  
Vol 16 (8) ◽  
pp. 5075-5090 ◽  
Author(s):  
Robert E. Holz ◽  
Steven Platnick ◽  
Kerry Meyer ◽  
Mark Vaughan ◽  
Andrew Heidinger ◽  
...  
Keyword(s):  
Optical Thickness ◽  
Spatial Scales ◽  
Radiative Properties ◽  
Radiation Balance ◽  
Data Set ◽  
Mean Values ◽  
Ice Cloud ◽  
Lidar Ratio ◽  
Cloud Optical Thickness ◽  
The Impact

Abstract. Despite its importance as one of the key radiative properties that determines the impact of upper tropospheric clouds on the radiation balance, ice cloud optical thickness (IOT) has proven to be one of the more challenging properties to retrieve from space-based remote sensing measurements. In particular, optically thin upper tropospheric ice clouds (cirrus) have been especially challenging due to their tenuous nature, extensive spatial scales, and complex particle shapes and light-scattering characteristics. The lack of independent validation motivates the investigation presented in this paper, wherein systematic biases between MODIS Collection 5 (C5) and CALIOP Version 3 (V3) unconstrained retrievals of tenuous IOT (< 3) are examined using a month of collocated A-Train observations. An initial comparison revealed a factor of 2 bias between the MODIS and CALIOP IOT retrievals. This bias is investigated using an infrared (IR) radiative closure approach that compares both products with MODIS IR cirrus retrievals developed for this assessment. The analysis finds that both the MODIS C5 and the unconstrained CALIOP V3 retrievals are biased (high and low, respectively) relative to the IR IOT retrievals. Based on this finding, the MODIS and CALIOP algorithms are investigated with the goal of explaining and minimizing the biases relative to the IR. For MODIS we find that the assumed ice single-scattering properties used for the C5 retrievals are not consistent with the mean IR COT distribution. The C5 ice scattering database results in the asymmetry parameter (g) varying as a function of effective radius with mean values that are too large. The MODIS retrievals have been brought into agreement with the IR by adopting a new ice scattering model for Collection 6 (C6) consisting of a modified gamma distribution comprised of a single habit (severely roughened aggregated columns); the C6 ice cloud optical property models have a constant g ≈ 0.75 in the mid-visible spectrum, 5–15 % smaller than C5. For CALIOP, the assumed lidar ratio for unconstrained retrievals is fixed at 25 sr for the V3 data products. This value is found to be inconsistent with the constrained (predominantly nighttime) CALIOP retrievals. An experimental data set was produced using a modified lidar ratio of 32 sr for the unconstrained retrievals (an increase of 28 %), selected to provide consistency with the constrained V3 results. These modifications greatly improve the agreement with the IR and provide consistency between the MODIS and CALIOP products. Based on these results the recently released MODIS C6 optical products use the single-habit distribution given above, while the upcoming CALIOP V4 unconstrained algorithm will use higher lidar ratios for unconstrained retrievals.

scholarly journals Robust estimation of vertical symmetry axis models via joint migration inversion: Including multiples in anisotropic parameter estimation

Geophysics ◽  
2019 ◽  
Vol 84 (1) ◽  
pp. C57-C74 ◽  
Author(s):  
Abdulrahman A. Alshuhail ◽  
Dirk J. Verschuur
Keyword(s):  
Symmetry Axis ◽  
Transverse Isotropy ◽  
Half Cycle ◽  
Anisotropic Parameter ◽  
Data Set ◽  
Trade Off ◽  
Trade Offs ◽  
Highly Nonlinear ◽  
Wide Range ◽  
Internal Multiples

Because the earth is predominately anisotropic, the anisotropy of the medium needs to be included in seismic imaging to avoid mispositioning of reflectors and unfocused images. Deriving accurate anisotropic velocities from the seismic reflection measurements is a highly nonlinear and ambiguous process. To mitigate the nonlinearity and trade-offs between parameters, we have included anisotropy in the so-called joint migration inversion (JMI) method, in which we limit ourselves to the case of transverse isotropy with a vertical symmetry axis. The JMI method is based on strictly separating the scattering effects in the data from the propagation effects. The scattering information is encoded in the reflectivity operators, whereas the phase information is encoded in the propagation operators. This strict separation enables the method to be more robust, in that it can appropriately handle a wide range of starting models, even when the differences in traveltimes are more than a half cycle away. The method also uses internal multiples in estimating reflectivities and anisotropic velocities. Including internal multiples in inversion not only reduces the crosstalk in the final image, but it can also reduce the trade-off between the anisotropic parameters because internal multiples usually have more of an imprint of the subsurface parameters compared with primaries. The inverse problem is parameterized in terms of a reflectivity, vertical velocity, horizontal velocity, and a fixed [Formula: see text] value. The method is demonstrated on several synthetic models and a marine data set from the North Sea. Our results indicate that using JMI for anisotropic inversion makes the inversion robust in terms of using highly erroneous initial models. Moreover, internal multiples can contain valuable information on the subsurface parameters, which can help to reduce the trade-off between anisotropic parameters in inversion.

scholarly journals Memories of Migrations Past: Sociality and Cognition in Dynamic, Seasonal Environments

2021 ◽  
Vol 9 ◽  
Author(s):  
Eliezer Gurarie ◽  
Sriya Potluri ◽  
George Christopher Cosner ◽  
Robert Stephen Cantrell ◽  
William F. Fagan
Keyword(s):  
Environmental Changes ◽  
Animal Movement ◽  
Spatial Scales ◽  
Rapid Change ◽  
Reference Memory ◽  
Migratory Behavior ◽  
Migration Behavior ◽  
Long Distance ◽  
Trade Offs ◽  
Resource Dynamics

Seasonal migrations are a widespread and broadly successful strategy for animals to exploit periodic and localized resources over large spatial scales. It remains an open and largely case-specific question whether long-distance migrations are resilient to environmental disruptions. High levels of mobility suggest an ability to shift ranges that can confer resilience. On the other hand, a conservative, hard-wired commitment to a risky behavior can be costly if conditions change. Mechanisms that contribute to migration include identification and responsiveness to resources, sociality, and cognitive processes such as spatial memory and learning. Our goal was to explore the extent to which these factors interact not only to maintain a migratory behavior but also to provide resilience against environmental changes. We develop a diffusion-advection model of animal movement in which an endogenous migratory behavior is modified by recent experiences via a memory process, and animals have a social swarming-like behavior over a range of spatial scales. We found that this relatively simple framework was able to adapt to a stable, seasonal resource dynamic under a broad range of parameter values. Furthermore, the model was able to acquire an adaptive migration behavior with time. However, the resilience of the process depended on all the parameters under consideration, with many complex trade-offs. For example, the spatial scale of sociality needed to be large enough to capture changes in the resource, but not so large that the acquired collective information was overly diluted. A long-term reference memory was important for hedging against a highly stochastic process, but a higher weighting of more recent memory was needed for adapting to directional changes in resource phenology. Our model provides a general and versatile framework for exploring the interaction of memory, movement, social and resource dynamics, even as environmental conditions globally are undergoing rapid change.

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