SimPEG: An open source framework for simulation and gradient based parameter estimation in geophysical applications

Kang

et al. 2019

Exploration Geophysics

Self Cite

Electromagnetics has an important role to play in solving the next generation of geoscience problems. These problems are multidisciplinary, complex, and require collaboration. This is especially true at the base scientific level where the underlying physical equations need to be solved, and data, associated with physical experiments, need to be inverted. In this paper, we present arguments for adopting an open-source methodology for geophysics and provide some background about open-source software for electromagnetics. Immediate benefits are the reduced time required to carry out research, being able to collaborate, having reproducible results, and being able to disseminate results quickly. To illustrate the use of an open-source methodology in electromagnetics, we present two challenges. The first is to simulate data from a time domain airborne system over a conductive plate buried in a more resistive earth. The second is to jointly invert airborne TDEM and FDEM data with ground TDEM. SimPEG, Simulation and Parameter Estimation in Geophysics, (https://simpeg.xyz) is used for the open-source software. The figures in this paper can be reproduced by downloading the Jupyter Notebooks we provide with this paper (https://github.com/simpegresearch/oldenburg-2018-AEM). Access to the source code allows the researcher to explore the simulations and inversions by changing model and inversion parameters, plot fields and fluxes to gain further insight about the EM phenomena, and solve a new research problem by using open-source software as a base. By providing results in a manner that allows others to reproduce, further explore, and even extend them, we hope to demonstrate that an open-source paradigm has the potential to enable more rapid progress of the geophysics community as a whole.

“…choice of the regularization functional) be tested and re-evaluated within the context of the initial geoscientific question. Adapted from Cockett et al (2015).…”

Section: D Em: a Case For Open-sourcementioning

confidence: 99%

“…These packages differ in objectives, capabilities, structure, interactivity, license, and coding language (commonly Python and Julia). Our efforts have been focused on the development of SimPEG (Cockett et al, 2015;Heagy et al, 2017).…”

Section: Open-source Developmentmentioning

confidence: 99%

3D electromagnetic modelling and inversion: a case for open source

Oldenburg

Kang

et al. 2019

Exploration Geophysics

Self Cite

“…The parameter m denotes the inversion model, which is the set of parameters sought in the inversion; β is a trade-off parameter which weights the relative contribution of the data misfit and the regularization in the inversion. The mathematical description of the data misfit and regularization follow a standard 2 formulation and are described in Cockett et al (2015).…”

Section: Stitched 1d Inversion Of Aem Datamentioning

confidence: 99%

Open-source software for simulations and inversions of airborne electromagnetic data

Kang

Cockett

et al. 2019

Exploration Geophysics

Self Cite

Inversions of airborne EM data are often an iterative process, not only requiring that the researcher be able to explore the impact of changing components such as the choice of regularization functional or model parameterization, but also often requiring that forward simulations be run and fields and fluxes visualized in order to build an understanding of the physical processes governing what we observe in the data. In the hope of facilitating this exploration and promoting reproducibility of geophysical simulations and inversions, we have developed the open source software package, SimPEG. The software has been designed to be modular and extensible with the goal of allowing researchers to interrogate all of the components and to facilitate the exploration of new inversion strategies. We present an overview of the software in its application to airborne EM and demonstrate its use for visualizing fields and fluxes in a forward simulation as well as its flexibility in formulating and solving the inverse problem. We invert a line of airborne TDEM data over a conductive vertical plate using a 1D voxelinversion, a 2D voxel inversion and a parametric inversion, where all of the forward modelling is done on a 3D grid. The results in this paper can be reproduced by using the provided Jupyter notebooks. The Python software can also be modified to allow users to experiment with parameters and explore the physics of the electromagnetics and intricacies of inversion.Open source software for AEM arXiv:1902.08238v1 [physics.geo-ph]

“…All of the numerical simulations are run with the open source software described in Heagy & Oldenburg (2019), which relies on the electromagnetics module within SimPEG (Cockett et al 2015;Heagy et al 2017). In Heagy & Oldenburg (2019), we demonstrate validation of the code by comparing a time-domain EM simulation, which uses the same DC resistivity forward simulation code as used in this paper to compute the initial condition, with solutions presented in Commer et al (2015) as well as with the Finite Volume OcTree code described in Haber et al (2007).…”

Section: Governing Equations and Numerical Modellingmentioning

confidence: 99%

Direct current resistivity with steel-cased wells

Geophysical Journal International

Oldenburg

2019

The work in this paper is motivated by the increasing use of electrical and electromagnetic methods in geoscience problems where steel-cased wells are present. Applications of interest include monitoring carbon capture and storage and hydraulic fracturing operations, as well as detecting flaws or breaks in degrading steel-casings -such wells pose serious environmental hazards. The general principles of electrical methods with steel-cased wells are understood, and several authors have demonstrated that the presence of steel-cased wells can be beneficial for detecting signal due to targets at depth. However, the success of a DC resistivity survey lies in the details. Secondary signals might only be a few percent of the primary signal. In designing a survey, the geometry of the source and receivers, and whether the source is at the top of the casing, inside of it, or beneath the casing will impact measured responses. Also the physical properties and geometry of the background geology, target, and casing will have a large impact on the measured data. Because of the small values of the diagnostic signals, it is important to understand the detailed physics of the problem and also to be able to carry out accurate simulations. This latter task is computationally challenging because of the extreme geometry of the wells, which extend kilometers in depth but have millimeter variations in the ra-arXiv:1810.12446v2 [physics.geo-ph] 8 Jul 2019 2 Lindsey J. Heagy, Douglas W. Oldenburg dial direction, and the extreme variation in the electrical conductivity (typically 5-7 orders of magnitude between the casing and the background geology).In this paper, we adopt a cylindrical discretization for numerical simulations to investigate three important aspects of DC resistivity in settings with steel-cased wells.(1) We examine the feasibility of using a surface-based DC resistivity survey for diagnosing impairments along a well in a casing integrity experiment. This parameter study demonstrates the impact of the background conductivity, the conductivity of the casing, the depth of the flaw, and the proportion of the casing circumference that is compromised, on amplitude of the secondary electric fields measured at the surface.(2) Next, we consider elements of survey design for exciting a conductive or resistive target at depth. We show that conductive targets generate stronger secondary responses than resistive targets, and that having an electrical connection between the target and well can significantly increase the measured secondary responses.(3) Finally, we examine common strategies for approximating the fine-scale structure of a steel cased well with a coarse-scale representation to reduce computational load. We show that for DC resistivity experiments, the product of the conductivity and the cross-sectional area of the casing is the important quantity for controlling the distribution of currents and charges along its length.To promote insight into the physics, we present results by plotting the currents, charges, and electric fi...