A Fast Algorithm for Parabolic PDE-based Inverse Problems Based on Laplace Transforms and Flexible Krylov Solvers

We consider the problem of estimating parameters in large-scale weakly nonlinear inverse problems for which the underlying governing equations is a linear, time-dependent, parabolic partial differential equation. A major challenge in solving these inverse problems using Newton-type methods is the computational cost associated with solving the forward problem and with repeated construction of the Jacobian, which represents the sensitivity of the measurements to the unknown parameters. Forming the Jacobian can be prohibitively expensive because it requires repeated solutions of the forward and adjoint time-dependent parabolic partial differential equations corresponding to multiple sources and receivers. We propose an efficient method based on a Laplace transform-based exponential time integrator combined with a flexible Krylov subspace approach to solve the resulting shifted systems of equations efficiently. Our proposed solver speeds up the computation of the forward and adjoint problems, thus yielding significant speedup in total inversion time. We consider an application from Transient Hydraulic Tomography (THT), which is an imaging technique to estimate hydraulic parameters related to the subsurface from pressure measurements obtained by a series of pumping tests. The algorithms discussed are applied to a synthetic example taken from THT to demonstrate the resulting computational gains of this proposed method

Fast Kalman Filter using Hierarchical-matrices and low-rank perturbative approach

We develop a fast algorithm for Kalman Filter applied to the random walk forecast model. The key idea is an efficient representation of the estimate covariance matrix at each time-step as a weighted sum of two contributions - the process noise covariance matrix and a low rank term computed from a generalized eigenvalue problem, which combines information from the noise covariance matrix and the data. We describe an efficient algorithm to update the weights of the above terms and the computation of eigenmodes of the generalized eigenvalue problem (GEP). The resulting algorithm for the Kalman filter with a random walk forecast model scales as \bigO(N) in memory and \bigO(N \log N) in computational cost, where $N$ is the number of grid points. We show how to efficiently compute measures of uncertainty and conditional realizations from the state distribution at each time step. An extension to the case with nonlinear measurement operators is also discussed. Numerical experiments demonstrate the performance of our algorithms, which are applied to a synthetic example from monitoring CO$_2$ in the subsurface using travel time tomography.Comment: published in Inverse Problems, 2015 31 01500

A Field Proof-of-Concept of Aquifer Imaging Using 3-D Transient Hydraulic Tomography with Modular, Temporarily-Emplaced Equipment

Hydraulic tomography is a field scale aquifer characterization method capable of estimating 3-D heterogeneous parameter distributions, and is directly sensitive to hydraulic conductivity (K), thus providing a useful data source for improving flow and transport models. We present results from a proof-of-concept field and modeling study in which we apply 3-D transient hydraulic tomography (3DTHT) to the relatively high-K and moderately heterogeneous unconfined aquifer at the Boise Hydrogeophysical Research Site. Short-duration (20 min) partially penetrating pumping tests, for which observed responses do not reach steady state, are used as the aquifer stimulation. To collect field data, we utilize a system of temporarily emplaced packer equipment to isolate multiple discrete intervals in boreholes. To analyze the data, we utilize MODFLOW combined with geostatistical inversion code based on the quasilinear approach of Kitanidis (1995). This combination of practical software allows inversion of large datasets (\u3e250 drawdown curves, and almost 1000 individual data points) and estimation of K at \u3e100,000 locations; reasonable runtimes are obtained using a single multicore computer with 12 GB of RAM. The K heterogeneity results from 3DTHT are cross-validated against K characterization from a large set of partially penetrating slug tests, and found to be quite consistent. The use of portable, modular equipment for field implementation means that 3DTHT data collection can be performed (including mobilization/demobilization) within a matter of days. Likewise, use of a practical, efficient and scalable numerical modeling and inversion strategy means that computational effort is drastically reduced, such that 3-D aquifer property distributions can be estimated quickly

An Interactive Bayesian Geostatistical Inverse Protocol for Hydraulic Tomography

Hydraulic tomography is a powerful technique for characterizing heterogeneous hydrogeologic parameters. An explicit trade-off between characterization based on measurement misfit and subjective characterization using prior information is presented. We apply a Bayesian geostatistical inverse approach that is well suited to accommodate a flexible model with the level of complexity driven by the data and explicitly considering uncertainty. Prior information is incorporated through the selection of a parameter covariance model characterizing continuity and providing stability. Often, discontinuities in the parameter field, typically caused by geologic contacts between contrasting lithologic units, necessitate subdivision into zones across which there is no correlation among hydraulic parameters. We propose an interactive protocol in which zonation candidates are implied from the data and are evaluated using cross validation and expert knowledge. Uncertainty introduced by limited knowledge of dynamic regional conditions is mitigated by using drawdown rather than native head values. An adjoint state formulation of MODFLOW-2000 is used to calculate sensitivities which are used both for the solution to the inverse problem and to guide protocol decisions. The protocol is tested using synthetic two-dimensional steady state examples in which the wells are located at the edge of the region of interest