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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

The cation inversion and magnetization in nanopowder zinc ferrite obtained by soft mechanochemical processing

Graphical abstract: - Highlights: • Nano powder of ZnFe{sub 2}O{sub 4} prepared by a soft mechanochemical route after 18 h milling. • Phase formation controlled by XRD, Raman spectroscopy and magnetic measurements. • Size, strain and cation inversion degree determined by Rietveld refinement. • We were able to estimate the degree of inversion at most 0.348 and 0.4. • Obtained extremely high values of saturation magnetizations at T = 4.5 K. - Abstract: Two zinc ferrite nanoparticle materials were prepared by the same method – soft mechanochemical synthesis, but starting from different powder mixtures: (1) Zn(OH){sub 2}/α-Fe{sub 2}O{sub 3} and (2) Zn(OH){sub 2}/Fe(OH){sub 3}. In both cases a single phase system was obtained after 18 h of milling. The progress of the synthesis was controlled by X-ray diffractometry (XRD), Raman spectroscopy, TEM and magnetic measurements. Analysis of the XRD patterns by Rietveld refinement allowed determination of the cation inversion degree for both obtained single phase ZnFe{sub 2}O{sub 4} samples. The sample obtained from mixture (1) has the cation inversion degree 0.3482 and the sample obtained from mixture (2) 0.400. Magnetization measurements were confirmed that the degrees of the inversion were well estimated. Comparison with published data shows that used method of synthesis gives nano powder samples with extremely high values of saturation magnetizations: sample (1) 78.3 emu g{sup −1} and sample (2) 91.5 emu g{sup −1} at T = 4.5 K.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Comparison of forward and inverse cam generation methods for the design of cam-linkage mechanisms

This paper presents a comparison between the forward and inverse cam generation methods applied to the design of a multi-lobed cam-rocker slider mechanism for function generation. In the forward method, the cam profile is specified directly and then the linkage output is determined using kinematics. In the inverse method, the trajectory of the output link is specified first and then the cam profile is determined using inverse linkage kinematics. First, the cam-linkage mechanism is introduced, and relevant kinematic equations are presented. Then, the cam generation methods are thoroughly explained. Here, the two cam generation methods are applied to a case study of a hydraulic motor using a multi-lobed cam and multiple linkage mechanisms. While the forward method has direct control of the cam shape, the inverse method has direct control of the linkage output and offers an advantage in calculation speed. For the mechanism selected, the cam designed with the inverse method achieved a reduction of at least 50.97% in the torque ripple when compared to the cam designed with the forward method.

42 ENGINEERING↗
DOE OSTI2016

Waves and vortices in the inverse cascade regime of stratified turbulence with or without rotation

We study the partition of energy between waves and vortices in stratified turbulence, with or without rotation, for a variety of parameters, focusing on the behaviour of the waves and vortices in the inverse cascade of energy towards the large scales. To this end, we use direct numerical simulations in a cubic box at a Reynolds number $Re\approx 1000$ , with the ratio between the Brunt–Väisälä frequency $N$ and the inertial frequency $f$ varying from $1/4$ to 20, together with a purely stratified run. The Froude number, measuring the strength of the stratification, varies within the range $0.02\leqslant Fr\leqslant 0.32$ . We find that the inverse cascade is dominated by the slow quasi-geostrophic modes. Their energy spectra and fluxes exhibit characteristics of an inverse cascade, even though their energy is not conserved. Surprisingly, the slow vortices still dominate when the ratio $N/f$ increases, also in the stratified case, although less and less so. However, when $N/f$ increases, the inverse cascade of the slow modes becomes weaker and weaker, and it vanishes in the purely stratified case. We discuss how the disappearance of the inverse cascade of energy with increasing $N/f$ can be interpreted in terms of the waves and vortices, and identify the main effects that can explain this transition based on both inviscid invariants arguments and viscous effects due to vertical shear.

Mechanics↗
DOE OSTI2020

Inversion of Time-Lapse Seismic Reservoir Monitoring Data Using CycleGAN: A Deep Learning-Based Approach for Estimating Dynamic Reservoir Property Changes

Carbon capture and storage is being pursued globally as a geoengineering measure for reducing the emission of anthropogenic CO 2 the atmosphere. Comprehensive monitoring, verification, and accounting programs must be established for demonstrating the safe storage of injected CO 2 . One of the most commonly deployed monitoring techniques is time-lapse seismic reservoir monitoring (also known as 4-D seismic), which involves comparing 3-D seismic survey data taken at the same study site but over different times. Analyses of 4-D seismic data volumes can help improve the quality of storage reservoir characterization, track the movement of injected CO 2 plume, and identify potential CO 2 spillover/leakage from the storage reservoirblue. However, the derivation of high-resolution CO 2 saturation maps from 4-D seismic data is a highly nonlinear and ill-posed inverse problem, often requiring significant computational effort. In this research, we apply a physics-based deep learning method to facilitate the solution of both the forward and inverse problems in seismic inversion while honoring physical constraints. A cycle generative adversarial neural network (CycleGAN) model is trained to learn the bidirectional functional mappings between the reservoir dynamic property changes and seismic attribute changes, such that both forward and inverse solutions can be obtained efficiently from the trained model. We show that our CycleGAN-based approach not only improves the reliability of 4-D seismic inversion but also expedites the quantitative interpretation. Our deep learning-based workflow is generic and can be readily used for reservoir characterization and reservoir model updates involving the use of 4-D seismic data.

58 GEOSCIENCES↗
DOE OSTI2021

Regional-scale, sector-specific evaluation of global CO2 inversion models using aircraft data from the ACT-America project

We use vertical profiles of airborne measurements of CO2 from frontal cases during the summer 2016 Atmospheric Carbon and Transport – America (ACT-America) campaign to evaluate the skill of a set of ten global CO2 inversion models participating in the Orbiting Carbon Observatory – 2 (OCO-2) Model Intercomparison Project (MIP). Model errors and biases (model minus observation) were categorized by region (Mid-Atlantic, Midwest, and South), frontal sector (warm or cold), and transport model (predominantly Tracer Model 5 (TM5) and Goddard Earth Observing System – Chemistry (GEOS-Chem)). Overall, the inversions reproduce the general structures of the observed vertical profiles and the enhanced / depleted low-level CO2 in warm / cold sectors, but tend to underestimate the magnitude of the sector difference in each region. In the Midwest and South warm sectors, inversion biases were about 1 ppm above 1500 m AGL, though model spread (quantified by interquartile range) was often even smaller; below 1500 m AGL, model biases were negative and about -2 ppm near the surface. For the Midwest and South cold sectors, models had +2-3 ppm biases below 1500 m AGL, but with comparable model spread. Uniquely, in the Mid-Atlantic there was a consistent difference between TM5 and GEOS-Chem mole fractions for both sectors up to 3000 m AGL (TM5 lower by 2 ppm), on the order of the observation-relative biases. In the MidAtlantic TM5 inversions had negative biases in warm sectors, while GEOS-Chem inversions had positive biases in cold sectors. Possible reasons for the regional variability are discussed.

Gaudet, Brian J.↗
DOE OSTI2019

Cascading phase transformations in high carbon steel resulting in the formation of inverse bainite: An atomic scale investigation

Atom probe tomography (APT) has been implemented to understand the redistribution of solutes during the isothermal cascading phase transformations from supersaturated austenite resulting in the formation of inverse bainite. Different cascading reactions resulting in the formation of inverse bainite, namely the cementite midrib formation, ferrite formation, secondary cementite formation, and the degenerated microstructure of inverse bainite have been studied in detail. Solute profiles across the different transformation interfaces indicate Negligible Partitioning Local Equilibrium (NPLE) type growth kinetics for cementite midrib, whereas a transition in growth kinetics from Para Equilibrium (PE) to Negligible Partitioning Local Equilibrium (NPLE) is observed for secondary cementite and ferrite transformation. The results demonstrate a strong indication that the inverse bainitic transformation occurs as a consequence of individual cascading phase transformations starting from parent austenite, and the transformation of inverse bainite occurs in a similar manner to Widmanstatten ferrite/bainitic ferrite with carbon diffusion-controlled growth, and without any reconstructive or long-range diffusion of substitutional solutes.

36 MATERIALS SCIENCE↗
DOE OSTI2013

Synchrotron-based far infrared study of the rotation-vibration-inversion spectrum of silacyclobutane below 500 cm{sup −1}: The ν{sub 29} and ν{sub 30} bands

Fourier transform spectra of the four-membered heterocycle silacyclobutane (c-C{sub 3}H{sub 8}Si) were recorded in the far infrared region from 100 to 500 cm{sup −1} with a maximum resolution of 0.000959 cm{sup −1} using synchrotron radiation from the Canadian Light Source. The two fundamental bands observed in this region correspond to motions best described as the out-of-plane modes related to ring puckering (ν{sub 30}) at ∼158 cm{sup −1} and SiH{sub 2} rocking (ν{sub 29}) at ∼410 cm{sup −1}. Both bands exhibit complex, dense spectral patterns that arise from ring inversion tunneling of the puckered SCB ring through a planar (C{sub 2v}) intermediate configuration. Analysis of these patterns revealed rotation-vibration transitions between states of the same inversion symmetry as well as rotation-vibration-inversion transitions that connect states of different inversion symmetry. Infrared ground state combination differences from 1871 pairs of P and R branch transitions were used to accurately determine the spectroscopic parameters for the tunneling-doubled ground state based on a broad range of quantum levels. With the ground state energy levels well-determined, 8255 infrared transitions were assigned and analyzed to derive the band centers, rotational and centrifugal distortion constants for the inversion split ν{sub 29} and ν{sub 30} vibrational states. Comparison with the band centers predicted via DFT (B3LYP) and MP2 calculations [6-311++G(2d,2p)] suggests that anharmonic corrections found via perturbation theory typically agree within 2% when compared with the observed spectrum of SCB.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Self-annihilation of inversion domains by high energy defects in III-Nitrides

Low-defect density InN films were grown on Si(111) by molecular beam epitaxy over an ∼1 μm thick GaN/AlN buffer/nucleation layer. Electron microscopy observations revealed the presence of inverse polarity domains propagating across the GaN layer and terminating at the sharp GaN/InN (0001{sup ¯}) interface, whereas no inversion domains were detected in InN. The systematic annihilation of GaN inversion domains at the GaN/InN interface is explained in terms of indium incorporation on the Ga-terminated inversion domains forming a metal bonded In-Ga bilayer, a structural instability known as the basal inversion domain boundary, during the initial stages of InN growth on GaN.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Contributed Review: Experimental characterization of inverse piezoelectric strain in GaN HEMTs via micro-Raman spectroscopy

Micro-Raman thermography is one of the most popular techniques for measuring local temperature rise in gallium nitride (GaN) high electron mobility transistors with high spatial and temporal resolution. However, accurate temperature measurements based on changes in the Stokes peak positions of the GaN epitaxial layers require properly accounting for the stress and/or strain induced by the inverse piezoelectric effect. It is common practice to use the pinched OFF state as the unpowered reference for temperature measurements because the vertical electric field in the GaN buffer that induces inverse piezoelectric stress/strain is relatively independent of the gate bias. Although this approach has yielded temperature measurements that agree with those derived from the Stokes/anti-Stokes ratio and thermal models, there has been significant difficulty in quantifying the mechanical state of the GaN buffer in the pinched OFF state from changes in the Raman spectra. In this paper, we review the experimental technique of micro-Raman thermography and derive expressions for the detailed dependence of the Raman peak positions on strain, stress, and electric field components in wurtzite GaN. We also use a combination of semiconductor device modeling and electro-mechanical modeling to predict the stress and strain induced by the inverse piezoelectric effect. Based on the insights gained from our electro-mechanical model and the best values of material properties in the literature, we analyze changes in the E{sub 2} high and A{sub 1} (LO) Raman peaks and demonstrate that there are major quantitative discrepancies between measured and modeled values of inverse piezoelectric stress and strain. We examine many of the hypotheses offered in the literature for these discrepancies but conclude that none of them satisfactorily resolves these discrepancies. Further research is needed to determine whether the electric field components could be affecting the phonon frequencies apart from the inverse piezoelectric effect in wurtzite GaN, which has been predicted theoretically in zinc blende gallium arsenide (GaAs).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

A comparative study of structural similarity and regularization for joint inverse problems governed by PDEs

Joint inversion refers to the simultaneous inference of multiple parameter fields from observations of systems governed by single or multiple forward models. In many cases these parameter fields reflect different attributes of a single medium and are thus spatially correlated or structurally similar. By imposing prior information on their spatial correlations via a joint regularization term, we seek to improve the reconstruction of the parameter fields relative to inversion for each field independently. One of the main challenges is to devise a joint regularization functional that conveys the spatial correlations or structural similarity between the fields while at the same time permitting scalable and efficient solvers for the joint inverse problem. We describe several joint regularizations that are motivated by these goals: a cross-gradient and a normalized cross-gradient structural similarity term, the vectorial total variation, and a joint regularization based on the nuclear norm of the gradients. Based on numerical results from three classes of inverse problems with piecewise-homogeneous parameter fields, we conclude that the vectorial total variation functional is preferable to the other methods considered. Besides resulting in good reconstructions in all experiments, it allows for scalable, efficient solvers for joint inverse problems governed by PDE forward models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Where did the tumor start? An inverse solver with sparse localization for tumor growth models

In this work, we present a numerical scheme for solving an inverse problem for parameter estimation in tumor growth models for glioblastomas, a form of aggressive primary brain tumor. The growth model is a reaction–diffusion partial differential equation (PDE) for the tumor concentration. We use a PDE-constrained optimization formulation for the inverse problem. The unknown parameters are the reaction coefficient (proliferation), the diffusion coefficient (infiltration), and the initial condition field for the tumor PDE. Segmentation of magnetic resonance imaging (MRI) scans drive the inverse problem where segmented tumor regions serve as partial observations of the tumor concentration. Like most cases in clinical practice, we use data from a single time snapshot. Moreover, the precise time relative to the initiation of the tumor is unknown, which poses an additional difficulty for inversion. We perform a frozen-coefficient spectral analysis and show that the inverse problem is severely ill-posed. We introduce a biophysically motivated regularization on the structure and magnitude of the tumor initial condition. In particular, we assume that the tumor starts at a few locations (enforced with a sparsity constraint on the initial condition of the tumor) and that the initial condition magnitude in the maximum norm is equal to one. We solve the resulting optimization problem using an inexact quasi-Newton method combined with a compressive sampling algorithm for the sparsity constraint. Our implementation uses PETSc and AccFFT libraries. We conduct numerical experiments on synthetic and clinical images to highlight the improved performance of our solver over a previously existing solver that uses standard two-norm regularization for the calibration parameters. The existing solver is unable to localize the initial condition. Our new solver can localize the initial condition and recover infiltration and proliferation. In clinical datasets (for which the ground truth is unknown), our solver results in qualitatively different solutions compared to the two-norm regularized solver.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Accelerating full-waveform inversion using source stacking: synthetic experiments at the global scale in a realistic 3-D earth model

SUMMARY The spectral element method is currently the method of choice for computing accurate synthetic seismic wavefields in realistic 3-D earth models at the global scale. However, it requires significantly more computational time, compared to normal mode-based approximate methods. Source stacking, whereby multiple earthquake sources are aligned on their origin time and simultaneously triggered, can reduce the computational costs by several orders of magnitude. We present the results of synthetic tests performed on a realistic radially anisotropic 3-D model, slightly modified from model SEMUCB-WM1 with three component synthetic waveform ‘data’ for a duration of 10 000 s, and filtered at periods longer than 60 s, for a set of 273 events and 515 stations. We consider two definitions of the misfit function, one based on the stacked records at individual stations and another based on station-pair cross-correlations of the stacked records. The inverse step is performed using a Gauss–Newton approach where the gradient and Hessian are computed using normal mode perturbation theory. We investigate the retrieval of radially anisotropic long wavelength structure in the upper mantle in the depth range 100–800 km, after fixing the crust and uppermost mantle structure constrained by fundamental mode Love and Rayleigh wave dispersion data. The results show good performance using both definitions of the misfit function, even in the presence of realistic noise, with degraded amplitudes of lateral variations in the anisotropic parameter ξ. Interestingly, we show that we can retrieve the long wavelength structure in the upper mantle, when considering one or the other of three portions of the cross-correlation time series, corresponding to where we expect the energy from surface wave overtone, fundamental mode or a mixture of the two to be dominant, respectively. We also considered the issue of missing data, by randomly removing a successively larger proportion of the available synthetic data. We replace the missing data by synthetics computed in the current 3-D model using normal mode perturbation theory. The inversion results degrade with the proportion of missing data, especially for ξ, and we find that a data availability of 45 per cent or more leads to acceptable results. We also present a strategy for grouping events and stations to minimize the number of missing data in each group. This leads to an increased number of computations but can be significantly more efficient than conventional single-event-at-a-time inversion. We apply the grouping strategy to a real picking scenario, and show promising resolution capability despite the use of fewer waveforms and uneven ray path distribution. Source stacking approach can be used to rapidly obtain a starting 3-D model for more conventional full-waveform inversion at higher resolution, and to investigate assumptions made in the inversion, such as trade-offs between isotropic, anisotropic or anelastic structure, different model parametrizations or how crustal structure is accounted for.

Geochemistry & Geophysics↗
DOE OSTI2020

Inverse energy transfer in decaying, three-dimensional, non-helical magnetic turbulence due to magnetic reconnection

ABSTRACT It has been recently shown numerically that there exists an inverse transfer of magnetic energy in decaying, non-helical, magnetically dominated, magnetohydrodynamic turbulence in three dimensions (3D). We suggest that magnetic reconnection is the underlying physical mechanism responsible for this inverse transfer. In the two-dimensional (2D) case, the inverse transfer is easily inferred to be due to smaller magnetic islands merging to form larger ones via reconnection. We find that the scaling behaviour is similar between the 2D and 3D cases, i.e. the magnetic energy evolves as t−1, and the magnetic power spectrum follows a slope of k−2. We show that on normalizing time by the magnetic reconnection time-scale, the evolution curves of the magnetic field in systems with different Lundquist numbers collapse on to one another. Furthermore, transfer function plots show signatures of magnetic reconnection driving the inverse transfer. We also discuss the conserved quantities in the system and show that the behaviour of these quantities is similar between the 2D and 3D simulations, thus making the case that the dynamics in 3D could be approximately explained by what we understand in 2D. Lastly, we also conduct simulations where the magnetic field is subdominant to the flow. Here, too, we find an inverse transfer of magnetic energy in 3D. In these simulations, the magnetic energy evolves as t−1.4 and, interestingly, a dynamo effect is observed.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Effect of the inversion symmetry breaking on the orbital Hall effect: A model study

The orbital Hall effect (OHE) is the transverse flow of orbital moment in a solid in response to an applied electric field, analogous to the flow of spin moment in the spin Hall effect (SHE). Although the effect has not been directly observed, there is ample indirect evidence for its existence in a number of experiments. Here, we show that the OHE is enhanced in solids with broken inversion symmetry, which may be more suitable to observe the effect. The mechanism of the OHE is fundamentally different in solids with inversion symmetry, where the orbital moment is quenched in the Brillouin zone (BZ), from that in a solid with broken inversion symmetry, where an intrinsic orbital moment is already present, the motion of which under the applied electric field could lead to a robust OHE. Using a tight-binding model Hamiltonian of a simple cubic lattice with two atoms in the unit cell, we study the effect of the inversion symmetry breaking on the OHE. We show that with the increase in the strength of the broken symmetry, the magnitude of the intrinsic orbital moment in the Brillouin zone increases. This, in turn, enhances the orbital Hall conductivity, in particular, the part that is directly proportional to the orbital moment in the BZ, which we call the “noncentrosymmetric contribution.” If the spin-orbit coupling is present, which couples the orbital and spin moments, the OHE leads to the SHE, which also becomes enhanced by the broken inversion symmetry. Furthermore, our work has important implications for experimenters, suggesting that noncentrosymmetric solids may be more suitable for direct observation of the OHE.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Learning-Based Inversion-Free Model-Data Integration to Advance Ecosystem Model Prediction

Ecosystem model prediction is important for understanding ecosystem responses to climate change and for management support. Model prediction and quantification of predictive uncertainty of ecosystems have long been investigated. The traditional workflow, which calibrates models to match observations and then uses the calibrated models for predictions, relies heavily on inverse modeling to constrain uncertain parameters in complex forward models. This inversion-based prediction approach is infeasible for complex models with heterogeneous parameter uncertainties and incapable of rapid integration of streaming and multiple sources of data because of the difficulty and computational cost in the model inversion, which is typically ill-posed and can require hundreds of thousands of expensive forward simulations to be performed iteratively. We propose to circumvent inverse modeling by precomputing an ensemble of unconstrained forward simulations and then using machine learning (ML) methods to learn the statistical relationship between simulated observation and prediction quantities. Once the ML model has learned the relationship, it can be used to make predictions of future system behavior with uncertainty quantification based on observations. The proposed learningbased inversion-free model prediction (LIMP) framework is computationally efficient which only requires a few thousands of fully parallelizable forward simulations. Additionally, LIMP can continually update predictions based on streaming observations from multiple locations and sources without necessarily requiring extra model simulations. In this study, we apply LIMP to a regional terrestrial ecosystem model with 47 parameters for testing, refining, and evaluating the approach. We demonstrate that LIMP can be used for efficient model prediction, rapid data assimilation, and cost-effective experimental design for improving robust predictive understanding of ecosystems.

Lu, Dan↗
DOE OSTI2021

Inverse Design of Two-Dimensional Airfoils Using Conditional Generative Models and Surrogate Log-Likelihoods

Abstract This paper shows how to use conditional generative models in two-dimensional (2D) airfoil optimization to probabilistically predict good initialization points within the vicinity of the optima given the input boundary conditions, thus warm starting and accelerating further optimization. We accommodate the possibility of multiple optimal designs corresponding to the same input boundary condition and take this inversion ambiguity into account when designing our prediction framework. To this end, we first employ the conditional formulation of our previous work BézierGAN–Conditional BézierGAN (CBGAN)—as a baseline, then introduce its sibling conditional entropic BézierGAN (CEBGAN), which is based on optimal transport regularized with entropy. Compared with CBGAN, CEBGAN overcomes mode collapse plaguing conventional GANs, improves the average lift-drag (Cl/Cd) efficiency of airfoil predictions from 80.8% of the optimal value to 95.8%, and meanwhile accelerates the training process by 30.7%. Furthermore, we investigate the unique ability of CEBGAN to produce a log-likelihood lower bound that may help select generated samples of higher performance (e.g., aerodynamic performance). In addition, we provide insights into the performance differences between these two models with low-dimensional toy problems and visualizations. These results and the probabilistic formulation of this inverse problem justify the extension of our GAN-based inverse design paradigm to other inverse design problems or broader inverse problems.

Engineering↗
DOE OSTI2016

Poster - 33: Dosimetry Comparison of Prone Breast Forward and Inverse Treatment planning considering daily setup variations

Introduction: The purpose of this study is to investigate the effects of daily setup variations on prone breast forward field-in-field (FinF) and inverse IMRT treatment planning. Methods: Rando Phantom (Left breast) and Pixy phantom (Right breast) were built and CT scanned in prone position. The treatment planning (TP) is performed in Eclipse TP system. Forward FinF plan and inverse IMRT plan were created to satisfy the CTV coverage and OARs criteria. The daily setup variations were assumed to be 5 mm at left-right, superior-inferior, and anterior-posterior directions. The DVHs of CTV coverage and OARs were compared for both forward FinF plan and inverse IMRT plans due to 5mm setup variation. Results and Discussions: DVHs of CTV coverage had fewer variations for 5m setup variation for forward FinF and inverse IMRT plan for both phantoms. However, for the setup variations in the left-right direction, the DVH of CTV coverage of IMRT plan showed the worst variation due to lateral setup variation for both phantoms. For anterior-posterior variation, the CTV could not get full coverage when the breast chest wall is shallow; however, with the guidance of MV imaging, breast chest wall will be checked during the MV imaging setup. So the setup variations have more effects on inverse IMRT plan, compared to forward FinF plan, especially in the left-right direction. Conclusions: The Forward FinF plan was recommended clinically considering daily setup variation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Inversion of downhole electrical measurements for proppant mapping using very fast simulated annealing

Proppant mapping is critical for optimizing fracture treatment design and improving wells’ productivity. An electrode-based resistivity tool concept was developed earlier for proppant mapping in cased-hole wells. An array of insulating gaps is installed and cemented in place as a permanent part of the casing string. The electrical measurements are performed by imposing a voltage across each insulating gap, one at a time, before and after hydraulic fracture operations. The voltages across other insulating gaps near the transmitter gap are recorded. The method relies on direct excitation of the casing, which is expected to overcome the severe limitations of induction tools in cased-hole wells. A forward model based on a finite volume method has been developed to simulate the tool’s response to one or multiple fractures. To enable the implementation of such a practical system in multistage fractured horizontal wells, a fast and robust inversion approach is required. To that end, we have developed a divide-and-conquer approach based on a global optimization algorithm very fast simulated annealing (VFSA). Specifically, the original inverse problem is divided into subproblems and each subproblem can be solved separately using VFSA. The results indicate that our approach can invert the data and output widths and radii of multiple fractures without requiring a large number of forward simulations. The robustness of the inverse solver is also tested by adding Gaussian noise to the synthetic data. We tested example cases that demonstrate that when up to 5% noise is introduced, VFSA still provides very accurate inversion results with moderate uncertainties. Inversion results with some more realistic conditions, e.g., tilted fractures, complex fractures, and so on, are also presented.

Geochemistry & Geophysics↗