Robust Dynamic Watermarking for Cyber-Physical Security of Inverter-Based Resources in Power Distribution Systems
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Cost reduction can be achieved by utilizing drilling simulators to efficiently optimize new wells to be drilled using available adjacent or offset well drilling data. Different approaches involving simulators that use inverted rate of penetration (ROP) models have been implemented to help improve the drilling performance of wells primarily within the Caney shale. A complete simulation and optimization technique is presented herein which utilizes drilling data from a nearby or offset well (Garrett well) to create an optimized drilling program for a new well to be drilled (Gallaway well).
Abstract Hydrogeophysical methods have been increasingly used to study subsurface soil–water dynamics, yet their application beyond the soil compartment or the quantitative link to soil hydraulic properties remains limited. To examine how these methods can inform model‐based evapotranspiration (ET) calculation under varying soil water conditions, we conducted a pilot‐scale field study at an experimental maize plot with manipulated irrigation treatments. Our goal was to develop a workflow for (1) acquiring and inverting field electrical resistivity tomography (ERT) data, (2) correlating ERT to soil hydraulic properties, (3) spatially characterizing soil water stress that feeds into ET modeling (the FAO‐56 model), and (4) evaluating the performance of ERT‐based ET computation. Our results showed that ERT was able to capture decimeter‐scale soil water content (SWC) dynamics from root water uptake and irrigation manipulation and the contrast of soil water stress between deficiently and fully irrigated maize. We also demonstrated the flexibility of using ERT to spatially integrate soil water stress in the soil volume of interest, which could be adjusted based on different crops and plot layouts. The integration of the ERT datasets into ET modeling provided insights into the spatial heterogeneity of the subsurface that has been challenging for point‐based sensing, which can further our understanding of the hydraulic dynamics in the soil‐plant‐atmosphere continuum.
Wastewater injection over the past decade has increased seismicity in the central USA, in some cases accompanied by detectable surface uplift. Here in this paper, we use this uplift to constrain subsurface properties and pore pressure evolution. We apply an advanced multitemporal interferometric algorithm to 35 synthetic aperture radar images acquired by ALOS satellite over four years before the 2012 earthquake sequence in east Texas, where large volumes of wastewater are disposed at depths of ~800 m and ~1800 m. To solve for the hydraulic diffusivity of the injection layers, we jointly inverted the injected volume and uplift data, considering a poroelastic layered half space. We find diffusivity values of 0.3±0.1 m 2 /s and 0.7±0.15 m 2 /s for shallow and deep injection layers, respectively, which combined with seismically-derived bulk moduli yields permeability values of 5.5±2.6×10 -14 m 2 and 1.9±0.25×10 -13 m 2 for these layers, consistent with permeability range reported for Rodessa formation and well test values. Hydraulic conductivity determines the evolution of pore pressure and thus the origin and location of induced seismicity. This study highlights the value of geodetic observations to constrain key hydrogeological properties of injection layers and to monitor the evolution of the subsurface pressure change.
Simulation of multiphase flow systems are of critical importance in managing hydrological systems. Flow simulations are affected by a number of factors including structure and flow properties including porosity and permeability as well as the anisotropy and heterogeneity of these properties. In many cases traditional hydrological and reservoir data are highly affected by these parameters, but are not directly sensitive to them. As such modellers often adjust these parameters in an ad hoc manner until solutions numerically converge. Simulation models are generally based on structural data from reflection seismics whose physical flow properties are then populated using geostatistical extrapolation techniques utilizing a sparse number of borehole logs and core analysis. In multiphase systems including enhanced oil recovery and carbon capture and sequestration uncertainties regarding phase-dependent physical properties confounds this challenge further. Geophysical methods provide a means by which to gain an improved understanding of phase distributions in the subsurface. In this paper we will look at applications from active carbon capture and sequestration and enhanced oil recovery applications, as well as synthetic examples. Geophysical data including electromagnetic and gravity are inverted using structural constraints from the reservoir model. Inversions are then mapped into flow properties using calibrated relations such as Archie’s Equation. The coupled models can then be used to both verify and improve on the reservoir flow model which improves it’s predictive power and utility as a management tool.
Interpreting strain data measured during well testing requires inverting poroelastic forward models set up to represent an aquifer or reservoir. One approach is to use stochastic methods to conduct the inversion. Subsurface parameters such as elastic modulus, permeability, and geometry of heterogeneities are estimated by searching the parameter space. This is feasible, but cumbersome, requiring more than a week of computation using many hundreds of computer nodes in one of our earlier analyses. This motivated us to consider alternative methods, including an artificial neural network (ANN) as a surrogate model.
Program studies materials for use in static inverters and converters. It gives suitable data on the behavior of commonly used materials when excited with square wave power.
An attempt has been made to invert a large set of attenuation data for Love waves and toroidal oscillations in the earth, using a recent method by Backus and Gilbert. The difficulty in finding an acceptable model of internal friction which explains the data, under the assumption that the internal friction is independent of frequency, casts doubt on the validity of this assumption. A frequency-dependent model of internal friction is presented which is in good agreement with the seismic data and with recent experimental measurements of attenuation in rocks.
This paper discusses the inversion problem for aerosols using the solar extinction method. A series of numerical experiments is described in which solar extinction measurement systems are modeled. A numerical model of a solar extinction measurement system has been coupled with model atmospheres that exhibit fine scale structures to produce numerically generated data signals. These signals were then inverted to study the effect that measurement errors and desired vertical resolution produce in the inverted results. Knowledge o2 the trade off between vertical resolution and the accuracy of inversion aid in the interpretation of the inverted results.
The cleaning and magnetic tape storage of spherical Earth processing programs are reported. These programs include: NVERTSM which inverts total or vector magnetic anomaly data on a distribution of point dipoles in spherical coordinates; SMFLD which utilizes output from NVERTSM to compute total or vector magnetic anomaly fields for a distribution of point dipoles in spherical coordinates; NVERTG; and GFLD. Abstracts are presented for papers dealing with the mapping and modeling of magnetic and gravity anomalies, and with the verification of crustal components in satellite data.
Solar Maximum Mission coronagraph/polarimeter observations of the coronal transient of March 15-16, 1980, which show a bright front convex toward the sun propagating out through the corona at 175 km/sec, are reported. A fan-shaped bright region connecting this front to the inner corona collapses into a narrow, bright ray over the next few hours. These observations are interpreted as resulting from the disconnection of magnetic loops from the underlying prominencelike loop structures seen rising earlier in the event. Other similar inverted arches exist in the C/P data, but are usually seen with poorer temporal resolution.
Altimetric data from the TOPEX/POSEIDON mission will be used for studies of global ocean circulation and marine geophysics. However, it is first necessary to remove the ocean tides, which are aliased in the raw data. The tides are constrained by the two distinct types of information: the hydrodynamic equations which the tidal fields of elevations and velocities must satisfy, and direct observational data from tide gauges and satellite altimetry. Here we develop and apply a generalized inverse method, which allows us to combine rationally all of this information into global tidal fields best fitting both the data and the dynamics, in a least squares sense. The resulting inverse solution is a sum of the direct solution to the astronomically forced Laplace tidal equations and a linear combination of the representers for the data functionals. The representer functions (one for each datum) are determined by the dynamical equations, and by our prior estimates of the statistics or errors in these equations. Our major task is a direct numerical calculation of these representers. This task is computationally intensive, but well suited to massively parallel processing. By calculating the representers we reduce the full (infinite dimensional) problem to a relatively low-dimensional problem at the outset, allowing full control over the conditioning and hence the stability of the inverse solution. With the representers calculated we can easily update our model as additional TOPEX/POSEIDON data become available. As an initial illustration we invert harmonic constants from a set of 80 open-ocean tide gauges. We then present a practical scheme for direct inversion of TOPEX/POSEIDON crossover data. We apply this method to 38 cycles of geophysical data records (GDR) data, computing preliminary global estimates of the four principal tidal constituents, M(sub 2), S(sub 2), K(sub 1) and O(sub 1). The inverse solution yields tidal fields which are simultaneously smoother, and in better agreement with altimetric and ground truth data, than previously proposed tidal models. Relative to the 'default' tidal corrections provided with the TOPEX/POSEIDON GDR, the inverse solution reduces crossover difference variances significantly (approximately 20-30%), even though only a small number of free parameters (approximately equal to 1000) are actually fit to the crossover data.
We propose a simple method to quantify a possible exclusion of the inverted neutrino mass ordering from cosmological bounds on the sum of the neutrino masses. The method is based on Bayesian inference and allows for a calculation of the posterior odds of normal versus inverted ordering. We apply the method for a specific set of current data from Planck CMB data and large-scale structure surveys, providing an upper bound on the sum of neutrino masses of 0.14 eV at 95% CL. With this analysis we obtain posterior odds for normal versus inverted ordering of about 2:1. If cosmological data is combined with data from oscillation experiments the odds reduce to about 3:2. For an exclusion of the inverted ordering from cosmology at more than 95% CL, an accuracy of better than 0.02 eV is needed for the sum. We demonstrate that such a value could be reached with planned observations of large scale structure by analysing artificial mock data for a EUCLID-like survey.
Synthetic aperture radar (SAR) interferometry and GPS have shown that during the quiescent period from 1993-1995 Mt. Etna volcano, Italy, inflated. Since the initiation of eruptive activity since late 1995 the deformation has been more contentious. We will explore the detailed deformation during the period from 1995-1996 spanning the late stages of inflation and the beginning of eruptive activity. We use SAR interferometry and GPS data to measure the volcano deformation. We invert the observed deformation for both simple point source. le crack elastic sources or if warranted for a spheroidal pressure So In particular, we will examine the evolution of the inflation and the transition to a lesser deflation observed at the end of 1995. We use ERS-1/2 SAR data from both ascending and descending passes to allow for dense temporal 'sampling of the deformation and to allow us to critically assess atmospheric noise. Preliminary results from interferometry suggest that the inflation rate accelerated prior to resumption of activity in 1995, while GPS data suggest a more steady inflation with some fluctuation following the start of activity. This study will compare and contrast the interferometric SAR and GPS results and will address the strengths and weaknesses of each technique towards volcano deformation studies.
We investigate angular velocity vectors of the Philippine Sea (PH) plate relative to the adjacent major plates, Eurasia (EU) and Pacific (PA), and the smaller Caroline (CR) plate. Earthquake slip vector data along the Philippine Sea plate are inverted, subject to the constraint that EU-PA motion equals that predicted by the global relative plate model NUVEL-1. The resulting solution fails to satisfy geological constraints along the Caroline-Pacific boundary: convergence along the Mussau Trench and divergence along the Sorol Trough. We then seek solutions satisfying both the CR-PA boundary conditions and the Philippine Sea slip vector data, by adjusting the PA-PH and EU-PH best fitting poles within their error ellipses. We also consider northern Honshu to be part of the North American plate and impose the constraint that the Philippine Sea plate subducts beneath northern Honshu along the Sagmi Trough in a NNW-NW direction. Of the solutions satisfying these conditions, we select the best EU-PH as 48.2 deg N, 157.0 deg E, 1.09 deg/my, corresponding to a pole far from Japan and south of Kamchatka, and PA-PH, 1.2 deg N, 134.2 deg E, 1.00 deg/my. Predicted NA-PH and EU-PH convergence rates in central Honshu are consistent with estimated seismic slip rates. Previous estimates of the EU-PH pole close to central Honshu are inconsistent with extension within the Bonin backarc implied by earthquake slip vectors and NNW-NW convergence of the Bonin forearc at the Sagami Trough.
There is a growing need to assess long-term impacts of active remediation strategies on treated aquifers. A variety of biogeochemical alterations can result from interactions of the amendment with the aquifer, conceivably leading to a geophysical footprint of the long-term alteration of an aquifer. This concept of post-remediation geophysical assessment was investigated in a shallow, chlorinated solvent-contaminated aquifer six to eight years after amendment delivery. Surface resistivity imaging and cross-borehole resistivity and induced polarization (IP) imaging were performed on a transect that spanned treated and untreated zones of the aquifer. Established relationships between IP parameters and surface electrical conductivity were used to predict vertical profiles of electrolytic conductivity and surface conductivity from the inverted cross-borehole images. Aqueous geochemistry data, along with natural gamma and magnetic susceptibility logs, were used to constrain the interpretation. The electrical conductivity structure determined from surface and borehole imaging was foremost controlled by the electrolytic conductivity of the interconnected pore space, being linearly related to fluid specific conductance. The electrolytic conductivity (and thus the conductivity images alone) did not discriminate between treated and untreated zones of the aquifer. In contrast, inverted phase angles and surface conductivities did discriminate between treated and untreated zones of the aquifer, with the treated zone being up to an order of magnitude more polarizable in places. Supporting aqueous chemistry and borehole logging datasets indicate that this geophysical footprint of the long-term impact of the remediation on the aquifer is most likely associated with the formation of polarizable, dispersed iron sulfide minerals. The study opens the door to the possibility of employing time-lapse electrical geophysical measurements to assist with long-term environmental stewardship of legacy sites undergoing active remediation.
In remote sensing, the encountered geophysical media such as agricultural canopy, forest, snow, or ice are inhomogeneous and contain scatters in a random manner. Furthermore, weather conditions such as fog, mist, or snow cover can intervene the electromagnetic observation of the remotely sensed media. In the modelling of such media accounting for the weather effects, a multi-layer random medium model has been developed. The scattering effects of the random media are described by three-dimensional correlation functions with variances and correlation lengths corresponding to the fluctuation strengths and the physical geometry of the inhomogeneities, respectively. With proper consideration of the dyadic Green's function and its singularities, the strong fluctuation theory is used to calculate the effective permittivities which account for the modification of the wave speed and attenuation in the presence of the scatters. The distorted Born approximation is then applied to obtain the correlations of the scattered fields. From the correlation of the scattered field, calculated is the complete set of scattering coefficients for polarimetric radar observation or brightness temperature in passive radiometer applications. In the remote sensing of terrestrial ecosystems, the development of microwave remote sensing technology and the potential of SAR to measure vegetation structure and biomass have increased effort to conduct experimental and theoretical researches on the interactions between microwave and vegetation canopies. The overall objective is to develop inversion algorithms to retrieve biophysical parameters from radar data. In this perspective, theoretical models and experimental data are methodically interconnected in the following manner: Due to the complexity of the interactions involved, all theoretical models have limited domains of validity; the proposed solution is to use theoretical models, which is validated by experiments, to establish the region in which the radar response is most sensitive to the parameters of interest; theoretically simulated data will be used to generate simple invertible models over the region. For applications to the remote sensing of sea ice, the developed theoretical models need to be tested with experimental measurements. With measured ground truth such as ice thickness, temperature, salinity, and structure, input parameters to the theoretical models can be obtained to calculate the polarimetric scattering coefficients for radars or brightness temperature for radiometers and then compare theoretical results with experimental data. Validated models will play an important role in the interpretation and classification of ice in monitoring global ice cover from space borne remote sensors in the future. We present an inversion algorithm based on a recently developed inversion method referred to as the Renormalized Source-Type Integral Equation approach. The objective of this method is to overcome some of the limitations and difficulties of the iterative Born technique. It recasts the inversion, which is nonlinear in nature, in terms of the solution of a set of linear equations; however, the final inversion equation is still nonlinear. The derived inversion equation is an exact equation which sums up the iterative Neuman (or Born) series in a closed form and, thus, is a valid representation even in the case when the Born series diverges; hence, the name Renormalized Source-Type Integral Equation Approach.
Power system simulations with long-term data typically have large time steps varying from one second to a few minutes. However, for PV inverter semiconductors, the minimum thermal stress cycle occurs over the fundamental grid frequency (50 or 60 Hz). This requires the time step of the fatigue simulation to be around 100 µs. This small time step requires long computation times to process yearly power production profiles. This paper proposes a fast fatigue simulation for inverter semiconductors using the quasi-static time series (QSTS) simulation concept. The proposed simulation calculates the steady state of the semiconductor junction temperature by using a Fast Fourier Transform (FFT). The small thermal cycling during a switching period and even over the fundamental waveform is disregarded to further accelerate the simulation speed. The resulting time step of the fatigue simulation is 15 minutes, which is consistent with the solar dataset. The error of the proposed simulation is 0.16% compared to the fatigue simulation results using the complete thermal stress profile. A PV inverter that responds to a Transactive Energy System (TES) is simulated to demonstrate the use of the proposed fatigue simulation. The proposed simulation has the potential to co-simulate with system level simulation tools that also adopt the QSTS concept.