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At least 91 records · Page 5Linked to original sources

Feasibility of waveform inversion of Rayleigh waves for shallow shear-wave velocity using a genetic algorithm

Conventional surface wave inversion for shallow shear (S)-wave velocity relies on the generation of dispersion curves of Rayleigh waves. This constrains the method to only laterally homogeneous (or very smooth laterally heterogeneous) earth models. Waveform inversion directly fits waveforms on seismograms, hence, does not have such a limitation. Waveforms of Rayleigh waves are highly related to S-wave velocities. By inverting the waveforms of Rayleigh waves on a near-surface seismogram, shallow S-wave velocities can be estimated for earth models with strong lateral heterogeneity. We employ genetic algorithm (GA) to perform waveform inversion of Rayleigh waves for S-wave velocities. The forward problem is solved by finite-difference modeling in the time domain. The model space is updated by generating offspring models using GA. Final solutions can be found through an iterative waveform-fitting scheme. Inversions based on synthetic records show that the S-wave velocities can be recovered successfully with errors no more than 10% for several typical near-surface earth models. For layered earth models, the proposed method can generate one-dimensional S-wave velocity profiles without the knowledge of initial models. For earth models containing lateral heterogeneity in which case conventional dispersion-curve-based inversion methods are challenging, it is feasible to produce high-resolution S-wave velocity sections by GA waveform inversion with appropriate priori information. The synthetic tests indicate that the GA waveform inversion of Rayleigh waves has the great potential for shallow S-wave velocity imaging with the existence of strong lateral heterogeneity.

Journal of Applied Geophysics

Total uncertainty quantification in inverse solutions with deep learning surrogate models

We propose an approximate Bayesian method for quantifying the total uncertainty in inverse partial differential equation (PDE) solutions obtained with machine learning surrogate models, including operator learning models. The proposed method accounts for uncertainty in the observations, PDE, and surrogate models. First, we use the surrogate model to formulate a minimization problem in the reduced space for the maximum a posteriori (MAP) inverse solution. Then, we randomize the MAP objective function and obtain samples of the posterior distribution by minimizing different realizations of the objective function. We test the proposed framework by comparing it with the iterative ensemble smoother and deep ensembling methods for a nonlinear diffusion equation with an unknown space-dependent diffusion coefficient. Among other applications, this equation describes the flow of groundwater in an unconfined aquifer. Depending on the training dataset and ensemble sizes, the proposed method provides similar or more descriptive posteriors of the parameters and states than the iterative ensemble smoother method. Deep ensembling underestimates uncertainty and provides less-informative posteriors than the other two methods. Our results show that, despite inherent uncertainty, surrogate models can be used for parameter and state estimation as an alternative to the inverse methods relying on (more accurate) numerical PDE solvers.

Journal of Computational Physics

Application of an iterative least-squares waveform inversion of strong-motion and teleseismic records to the 1978 Tabas, Iran, earthquake

An iterative least-squares technique is used to simultaneously invert the strong-motion records and teleseismic P waveforms for the 1978 Tabas, Iran, earthquake to deduce the rupture history. The effects of using different data sets and different parametrizations of the problem (linear versus nonlinear) are considered. A consensus of all the inversion runs indicates a complex, multiple source for the Tabas earthquake, with four main source regions over a fault length of 90 km and an average rupture velocity of 2.5 km/sec.

Bulletin of the Seismological Society of America

Characterizing fractured-zone flow using numerical flow-log models

Water-quality monitoring and hydraulic testing in fractured bedrock aquifers involves two important tasks: 1) identifying the hydraulically active fractures intersecting the borehole, and 2) inferring how the specific entry or exit ports in the borehole wall are connected to large-scale flow paths in the region surrounding the borehole. Effective characterization of fractured bedrock flow results when hydraulically active fractures and fracture zones are first identified using flow logs, and then the hydraulic properties of these active zones are given by subsequent hydraulic tests. A more difficult technical problem is relating the hydraulic properties of the few specific fractures that serve as borehole entry ports to the large-scale hydraulic properties of the surrounding rock mass. This problem is addressed through a generalized borehole flow model inversion formulated so that the boundary conditions at the outer edge of the boundary layer can be inferred from the properties of measured borehole flow.

Book chapter

Time‐lapse inversion of crosswell radar data

The combination of differential radar tomography with conventional tracer and/or hydraulic tests facilitates high‐resolution characterization of subsurface heterogeneity and enables the identification of preferential flow paths. In dynamic imaging, each tomogram is typically inverted independently, under the assumption that data sets are collected quickly relative to changes in the imaged property (e.g., attenuation or velocity); however, such “snapshot” tomograms may contain large errors if the imaged property changes significantly during data collection. Acquisition of less data over a shorter time interval could ameliorate the problem, but the resulting decrease in ray density and angular coverage could degrade model resolution. To address these problems, we propose a new sequential approach for time‐lapse tomographic inversion. The method uses space‐time parameterization and regularization to combine data collected at multiple times and to account for temporal variation. The inverse algorithm minimizes the sum of weighted squared residuals and a measure of solution complexity based on an a priori space‐time covariance function and a spatiotemporally variable mean. We demonstrate our approach using a synthetic 2‐D time‐lapse ( x , z , t ) data set based loosely on a field experiment in which difference‐attenuation radar tomography was used to monitor the migration of a saline tracer in fractured rock. We quantitatively show the benefits of space‐time inversion by comparing results for snapshot and time‐lapse inversion schemes. Inversion over both space and time results in superior estimation error, model resolution, and data reproduction compared to conventional snapshot inversion. Finally, we suggest strategies to improve time‐lapse cross‐hole inversions using ray‐based inversion constraints and a modified survey design in which different sets of rays are collected in alternating time steps.

Geophysics

1r2dinv: A finite-difference model for inverse analysis of two dimensional linear or radial groundwater flow

We have developed a program for inverse analysis of two-dimensional linear or radial groundwater flow problems. The program, 1r2dinv, uses standard finite difference techniques to solve the groundwater flow equation for a horizontal or vertical plane with heterogeneous properties. In radial mode, the program simulates flow to a well in a vertical plane, transforming the radial flow equation into an equivalent problem in Cartesian coordinates. The physical parameters in the model are horizontal or x-direction hydraulic conductivity, anisotropy ratio (vertical to horizontal conductivity in a vertical model, y-direction to x-direction in a horizontal model), and specific storage. The program allows the user to specify arbitrary and independent zonations of these three parameters and also to specify which zonal parameter values are known and which are unknown. The Levenberg-Marquardt algorithm is used to estimate parameters from observed head values. Particularly powerful features of the program are the ability to perform simultaneous analysis of heads from different tests and the inclusion of the wellbore in the radial mode. These capabilities allow the program to be used for analysis of suites of well tests, such as multilevel slug tests or pumping tests in a tomographic format. The combination of information from tests stressing different vertical levels in an aquifer provides the means for accurately estimating vertical variations in conductivity, a factor profoundly influencing contaminant transport in the subsurface. ?? 2001 Elsevier Science Ltd. All rights reserved.

Computers & Geosciences

Geophysical mapping of plume discharge to surface water at a crude oil spill site: Inversion versus machine learning

The interpretation of geophysical survey results to answer hydrologic, engineering, and geologic questions is critical to diverse problems for management of water, energy, and mineral resources. Although geophysical images provide valuable qualitative insight into subsurface architecture and conditions, translating geophysical images into quantitative information (e.g., saturation, concentration, and hydraulic properties) often involves substantial nonuniqueness and uncertainty owing to the limited resolution of geophysical imaging and uncertainty in petrophysical relations. We have developed a machine-learning approach to address these challenges in the context of a field-based investigation to map zones where a hydrocarbon plume was discharging to surface water at the National Crude Oil Spill Fate and Natural Attenuation Research Site in Bemidji, Minnesota, USA. The two-step approach combines multiple types of geophysical and direct information and effectively bypasses inversion and its associated assumptions. Integrating multifrequency electromagnetic induction, ground-penetrating radar, and fluid-sampling data, we first identify discharge zones and second estimate specific conductance versus depth. Compared with conventional inversion results, the machine-learning results (1) directly address the study objectives (delineating the discharge zones); (2) better extract depth-dependent information from the data, for which sensitivity diminishes rapidly with depth; and (3) quantify the uncertainty of the predictions (i.e., discharge versus nondischarge zones), rather than the uncertainty of the geophysical estimates (i.e., the standard error of estimation for the logarithm of electrical conductivity).

Minnesota

Trends and management of wolf-livestock conflicts in Minnesota

The nature and extent of wolf-livestock conflicts in Minnesota during 1975-86 was studied as part of a wolf depredation control program. The level of wolf (Canis lupus) depredation on livestock in Minnesota, as determined from the total number of complaints verified annually during 1975-86, showed a slight upward trend but did not increase significantly. A significant portion of the annual variation in verified complaints-perhaps the best index on severity of the depredation problem was explained by variation in severity of the winter before the depredation season (inverse relation). The addition of a time variable did not account for a significant portion of the remaining variation. Verified complaints of depredations averaged 30 per year, affecting an average of 21 farms (0.33% of producers) annually. Conflicts were highly seasonal and involved primarily cattle (mainly calves), sheep, and domestic turkeys. Annual variation in losses of sheep and turkeys was higher than for cattle. In recent years, sheep and turkey losses in two northwestern counties have increased; preventive control may be warranted in those areas. Site-specific trapping and removal of wolves in response to depredations was the primary control method, resulting in captures of 437 wolves in 12 depredation seasons. For the wolf range as a whole, no relation was found between wolf removal and subsequent depredation rates; however, wolf removal seemed to reduce depredations locally at some farms. When adults and yearlings were removed, no subsequent losses occurred in about 55% of instances; removal of young of the year reduced losses in 22%. Removal of breeding wolves did not reduce the incidence of subsequent losses more than removal of nonbreeding adults and yearlings did. The low number of conflicts for 1975-86 was remarkable considering the frequent contact between wolves and livestock. However, an update of complaints for 1987-89 revealed a definite upward trend in depredations (Epilogue). Improvements in farm management practices may reduce the present number of conflicts.

Resource Publication

Convergent radial dispersion: A note on evaluation of the Laplace transform solution

A numerical inversion algorithm for Laplace transforms that is capable of handling rapid changes in the computed function is applied to the Laplace transform solution to the problem of convergent radial dispersion in a homogeneous aquifer. Prior attempts by the author to invert this solution were unsuccessful for highly advective systems where the Peclet number was relatively large. The algorithm used in this note allows for rapid and accurate inversion of the solution for all Peclet numbers of practical interest, and beyond. Dimensionless breakthrough curves are illustrated for tracer input in the form of a step function, a Dirac impulse, or a rectangular input.

Water Resources Research

A trade-off between model resolution and variance with selected Rayleigh-wave data

Inversion of multimode surface-wave data is of increasing interest in the near-surface geophysics community. For a given near-surface geophysical problem, it is essential to understand how well the data, calculated according to a layered-earth model, might match the observed data. A data-resolution matrix is a function of the data kernel (determined by a geophysical model and a priori information applied to the problem), not the data. A data-resolution matrix of high-frequency (??? 2 Hz) Rayleigh-wave phase velocities, therefore, offers a quantitative tool for designing field surveys and predicting the match between calculated and observed data. First, we employed a data-resolution matrix to select data that would be well predicted and to explain advantages of incorporating higher modes in inversion. The resulting discussion using the data-resolution matrix provides insight into the process of inverting Rayleigh-wave phase velocities with higher mode data to estimate S-wave velocity structure. Discussion also suggested that each near-surface geophysical target can only be resolved using Rayleigh-wave phase velocities within specific frequency ranges, and higher mode data are normally more accurately predicted than fundamental mode data because of restrictions on the data kernel for the inversion system. Second, we obtained an optimal damping vector in a vicinity of an inverted model by the singular value decomposition of a trade-off function of model resolution and variance. In the end of the paper, we used a real-world example to demonstrate that selected data with the data-resolution matrix can provide better inversion results and to explain with the data-resolution matrix why incorporating higher mode data in inversion can provide better results. We also calculated model-resolution matrices of these examples to show the potential of increasing model resolution with selected surface-wave data. With the optimal damping vector, we can improve and assess an inverted model obtained by a damped least-square method.

Conference Paper

Data-resolution matrix and model-resolution matrix for Rayleigh-wave inversion using a damped least-squares method

Inversion of multimode surface-wave data is of increasing interest in the near-surface geophysics community. For a given near-surface geophysical problem, it is essential to understand how well the data, calculated according to a layered-earth model, might match the observed data. A data-resolution matrix is a function of the data kernel (determined by a geophysical model and a priori information applied to the problem), not the data. A data-resolution matrix of high-frequency (>2 Hz) Rayleigh-wave phase velocities, therefore, offers a quantitative tool for designing field surveys and predicting the match between calculated and observed data. We employed a data-resolution matrix to select data that would be well predicted and we find that there are advantages of incorporating higher modes in inversion. The resulting discussion using the data-resolution matrix provides insight into the process of inverting Rayleigh-wave phase velocities with higher-mode data to estimate S-wave velocity structure. Discussion also suggested that each near-surface geophysical target can only be resolved using Rayleigh-wave phase velocities within specific frequency ranges, and higher-mode data are normally more accurately predicted than fundamental-mode data because of restrictions on the data kernel for the inversion system. We used synthetic and real-world examples to demonstrate that selected data with the data-resolution matrix can provide better inversion results and to explain with the data-resolution matrix why incorporating higher-mode data in inversion can provide better results. We also calculated model-resolution matrices in these examples to show the potential of increasing model resolution with selected surface-wave data. ?? Birkhaueser 2008.

Pure and Applied Geophysics

Finite‐fault Bayesian inversion of teleseismic body waves

Inverting geophysical data has provided fundamental information about the behavior of earthquake rupture. However, inferring kinematic source model parameters for finite‐fault ruptures is an intrinsically underdetermined problem (the problem of nonuniqueness), because we are restricted to finite noisy observations. Although many studies use least‐squares techniques to make the finite‐fault problem tractable, these methods generally lack the ability to apply non‐Gaussian error analysis and the imposition of nonlinear constraints. However, the Bayesian approach can be employed to find a Gaussian or non‐Gaussian distribution of all probable model parameters, while utilizing nonlinear constraints. We present case studies to quantify the resolving power and associated uncertainties using only teleseismic body waves in a Bayesian framework to infer the slip history for a synthetic case and two earthquakes: the 2011 M w 7.1 Van, east Turkey, earthquake and the 2010 M w 7.2 El Mayor–Cucapah, Baja California, earthquake. In implementing the Bayesian method, we further present two distinct solutions to investigate the uncertainties by performing the inversion with and without velocity structure perturbations. We find that the posterior ensemble becomes broader when including velocity structure variability and introduces a spatial smearing of slip. Using the Bayesian framework solely on teleseismic body waves, we find rake is poorly constrained by the observations and rise time is poorly resolved when slip amplitude is low.

Bulletin of the Seismological Society of America

Parallel Fortran-MPI software for numerical inversion of the Laplace transform and its application to oscillatory water levels in groundwater environments

A parallel Fortran-MPI (Message Passing Interface) software for numerical inversion of the Laplace transform based on a Fourier series method is developed to meet the need of solving intensive computational problems involving oscillatory water level's response to hydraulic tests in a groundwater environment. The software is a parallel version of ACM (The Association for Computing Machinery) Transactions on Mathematical Software (TOMS) Algorithm 796. Running 38 test examples indicated that implementation of MPI techniques with distributed memory architecture speedups the processing and improves the efficiency. Applications to oscillatory water levels in a well during aquifer tests are presented to illustrate how this package can be applied to solve complicated environmental problems involved in differential and integral equations. The package is free and is easy to use for people with little or no previous experience in using MPI but who wish to get off to a quick start in parallel computing. ?? 2004 Elsevier Ltd. All rights reserved.

Environmental Modelling and Software

A test of geographic assignment using isotope tracers in feathers of known origin

We used feathers of known origin collected from across the breeding range of a migratory shorebird to test the use of isotope tracers for assigning breeding origins. We analyzed δD, δ 13 C, and δ 15 N in feathers from 75 mountain plover ( Charadrius montanus ) chicks sampled in 2001 and from 119 chicks sampled in 2002. We estimated parameters for continuous-response inverse regression models and for discrete-response Bayesian probability models from data for each year independently. We evaluated model predictions with both the training data and by using the alternate year as an independent test dataset. Our results provide weak support for modeling latitude and isotope values as monotonic functions of one another, especially when data are pooled over known sources of variation such as sample year or location. We were unable to make even qualitative statements, such as north versus south, about the likely origin of birds using both δD and δ 13 C in inverse regression models; results were no better than random assignment. Probability models provided better results and a more natural framework for the problem. Correct assignment rates were highest when considering all three isotopes in the probability framework, but the use of even a single isotope was better than random assignment. The method appears relatively robust to temporal effects and is most sensitive to the isotope discrimination gradients over which samples are taken. We offer that the problem of using isotope tracers to infer geographic origin is best framed as one of assignment, rather than prediction.

Oecologia

Convergent radial dispersion: A Laplace transform solution for aquifer tracer testing

A Laplace transform solution was obtained for the injection of a tracer in a well situated in a homogeneous aquifer where steady, horizontal, radially convergent flow has been established due to pumping at a second well. The standard advection-dispersion equation for mass transfer was used as the controlling equation. For boundary conditions, mass balances that account for mixing of the tracer with the fluid residing in the injection and pumped wells were used. The derived solution, which can be adapted for either resident or flux-averaged concentration, is of practical use only for the pumped well. This problem is of interest because it is easily applied to field determination of aquifer dispersivity and effective porosity. Breakthrough curves were obtained by numerical inversion of the Laplace transform solution. It was found that tracer mixing with fluid in the pumped and injection wells, especially in low-porosity aquifers, may have a significant influence on the shape of the tracer breakthrough curves.

Water Resources Research

Approaches in highly parameterized inversion - PEST++, a Parameter ESTimation code optimized for large environmental models

An object-oriented parameter estimation code was developed to incorporate benefits of object-oriented programming techniques for solving large parameter estimation modeling problems. The code is written in C++ and is a formulation and expansion of the algorithms included in PEST, a widely used parameter estimation code written in Fortran. The new code is called PEST++ and is designed to lower the barriers of entry for users and developers while providing efficient algorithms that can accommodate large, highly parameterized problems. This effort has focused on (1) implementing the most popular features of PEST in a fashion that is easy for novice or experienced modelers to use and (2) creating a software design that is easy to extend; that is, this effort provides a documented object-oriented framework designed from the ground up to be modular and extensible. In addition, all PEST++ source code and its associated libraries, as well as the general run manager source code, have been integrated in the Microsoft Visual Studio® 2010 integrated development environment. The PEST++ code is designed to provide a foundation for an open-source development environment capable of producing robust and efficient parameter estimation tools for the environmental modeling community into the future.

Techniques and Methods

Geophysical characterization of the American River levees, Sacramento, California, with electromagnetics, capacitively coupled resistivity, and DC resistivity

A geophysical characterization of a portion of American River levees in Sacramento, California was conducted in May, 2007. Targets of interest included the distribution and thickness of sand lenses that underlie the levees and the depth to a clay unit that underlies the sand. The concern is that the erosion of these sand lenses can lead to levee failure in highly populated areas of Sacramento. DC resistivity (Geometric’s OhmMapper and Advanced Geosciences, Inc.’s SuperSting R8 systems) and electromagnetic surveys (Geophex’s GEM-2) were conducted over a 6 mile length of the levee on roads and bicycle and horse trails. 2-D inversions were conducted on all the geophysical data. The OhmMapper and SuperSting surveys produced consistent inversion results that delineated potential sand and clay units. GEM-2 apparent resistivity data were consistent with the DC inversion results. However, the GEM-2 data could not be inverted due to low electromagnetic response levels, high ambient electromagnetic noise, and large system drifts. While this would not be as large a problem in conductive terrains, it is a problem for a small induction number electromagnetic profiling system such as the GEM-2 in a resistive terrain (the sand lenses). An integrated interpretation of the geophysical data acquired in this investigation is presented in this report that includes delineation of those areas consisting of predominantly sand and those areas consisting predominantly of clay. In general, along most of this part of the American River levee system, sand lenses are located closest to the river and clay deposits are located further away from the river. The interpreted thicknesses of the detected sand deposits are variable and range from 10 ft up to 60 ft. Thus, despite issues with the GEM-2 inversion, this geophysical investigation successfully delineated sand lenses and clay deposits along the American River levee system and the approximate depths to underlying clay zones. The results of this geophysical investigation should help the USACE to maintain the current levee system while also assisting the designers and planners of levee enhancements with the knowledge of what is to be expected from the near-surface geology and where zones of concern may be located.

California