Python for HPC geophysical electromagnetic applications: experiences and perspectives

Nowadays, the electromagnetic modelling are a fun-damental tool in geophysics due to their wide field of application: hydrocarbon and mineral exploration, reservoir monitoring, CO storage characterization, geothermal reservoir imaging and many others. In particular, the 3D CSEM forward modelling (FM) is an established tool in the oil & gas industry because of the hope that the application of such methods would eventually lead to the direct detection of hydrocarbons through their insulating properties. Although 3D CSEM FM is nowadays a well-known geophysical prospecting tool and his fundamental mathematical theory is well-established, the state-of-art shows a relative scarsity of robust, flexible, modular and open-source codes to simulate these problems on HPC platforms, which is crucial in the future goal of solving inverse problems. In this talk we describe our experience and perspectives in the development of an HPC python code for the 3D CSEM FM, namely, PETGEM. We focus on three points: 1) 3D CSEM FM theory from a practical point of view, 2) PETGEM features and Python potential for HPC applications, and 3) Modelling results of real-life 3D CSEM FM cases. These points depict that PETGEM could be an attractive and competitive HPC tool to simulate real-scale of 3D CSEM FM in geophysics

Parallel 3-D marine controlled-source electromagnetic modelling using high-order tetrahedral Nédélec elements

We present a parallel and high-order Nédélec finite element solution for the marine controlled-source electromagnetic (CSEM) forward problem in 3-D media with isotropic conductivity. Our parallel Python code is implemented on unstructured tetrahedral meshes, which support multiple-scale structures and bathymetry for general marine 3-D CSEM modelling applications. Based on a primary/secondary field approach, we solve the diffusive form of Maxwell’s equations in the low-frequency domain. We investigate the accuracy and performance advantages of our new high-order algorithm against a low-order implementation proposed in our previous work. The numerical precision of our high-order method has been successfully verified by comparisons against previously published results that are relevant in terms of scale and geological properties. A convergence study confirms that high-order polynomials offer a better trade-off between accuracy and computation time. However, the optimum choice of the polynomial order depends on both the input model and the required accuracy as revealed by our tests. Also, we extend our adaptive-meshing strategy to high-order tetrahedral elements. Using adapted meshes to both physical parameters and high-order schemes, we are able to achieve a significant reduction in computational cost without sacrificing accuracy in the modelling. Furthermore, we demonstrate the excellent performance and quasi-linear scaling of our implementation in a state-of-the-art high-performance computing architecture.This project has received funding from the European Union's Horizon 2020 programme under the Marie Sklodowska-Curie grant agreement No. 777778. Furthermore, the research leading to these results has received funding from the European Union's Horizon 2020 programme under the ChEESE Project (https://cheese-coe.eu/ ), grant agreement No. 823844. In addition, the authors would also like to thank the support of the Ministerio de Educación y Ciencia (Spain) under Projects TEC2016-80386-P and TIN2016-80957-P. The authors would like to thank the Editors-in-Chief and to both reviewers, Dr. Martin Cuma and Dr. Raphael Rochlitz, for their valuable comments and suggestions which helped to improve the quality of the manuscript. This work benefited from the valuable suggestions, comments, and proofreading of Dr. Otilio Rojas (BSC). Last but not least, Octavio Castillo-Reyes thanks Natalia Gutierrez (BSC) for her support in CSEM modeling with BSIT.Peer ReviewedPostprint (author's final draft

Overview on agent-based social modelling and the use of formal languages

Transdisciplinary Models and Applications investigates a variety of programming languages used in validating and verifying models in order to assist in their eventual implementation. This book will explore different methods of evaluating and formalizing simulation models, enabling computer and industrial engineers, mathematicians, and students working with computer simulations to thoroughly understand the progression from simulation to product, improving the overall effectiveness of modeling systems.Postprint (author's final draft

HPC and edge elements for geophysical electromagnetic problems: an overview

In Finite Element Methods for solving electromagnetic problems, the use of Nédélec Elements has become very popular. In fact, Nédélec Elements are often said to be a cure to many difficulties that are encountered, particularly eliminating spurious solutions, and are claimed to yield accurate results. In this paper, we present our first steps in developing a Nédélec Elements code for simulation of geophysical electromagnetic problems and first ideas on how implement the key issues of Edge Elements in an efficient way on HPC platforms

HPC and edge elements for geophysical electromagnetic problems: an overview

In Finite Element Methods for solving electromagnetic problems, the use of Nédélec Elements has become very popular. In fact, Nédélec Elements are often said to be a cure to many difficulties that are encountered, particularly eliminating spurious solutions, and are claimed to yield accurate results. In this paper, we present our first steps in developing a Nédélec Elements code for simulation of geophysical electromagnetic problems and first ideas on how implement the key issues of Edge Elements in an efficient way on HPC platforms

HPC geophysical electromagnetics: a synthetic VTI model with complex bathymetry

We introduce a new synthetic marine model for 3D controlled-source electromagnetic method (CSEM) surveys. The proposed model includes relevant features for the electromagnetic geophysical community such as large conductivity contrast with vertical transverse isotropy and a complex bathymetry profile. In this paper, we present the experimental setup and several 3D CSEM simulations in the presence of a resistivity unit denoting a hydrocarbon reservoir. We employ a parallel and high-order vector finite element routine to perform the CSEM simulations. By using tailored meshes, several scenarios are simulated to assess the influence of the reservoir unit presence on the electromagnetic responses. Our numerical assessment confirms that resistivity unit strongly influences the amplitude and phase of the electromagnetic measurements. We investigate the code performance for the solution of fundamental frequencies on high-performance computing architectures. Here, excellent performance ratios are obtained. Our benchmark model and its modeling results are developed under an open-source scheme that promotes easy access to data and reproducible solutions.The work of O.C-R., conducted in the frame of PIXIL project, has been 65% cofinanced by the European Regional Development Fund (ERDF) through the Interreg V-A SpainFrance-Andorra program (POCTEFA2014-2020). BSC authors have received funding from the European Union’s Horizon 2020 programme under the Marie Sklodowska-Curie grant agreement N◦ 777778. Furthermore, the development of PETGEM has received funding from the European Union’s Horizon 2020 programme, grant agreement N◦ 828947, and from the Mexican Department of Energy, CONACYT-SENER Hidrocarburos grant agreement N◦ B-S-69926.Peer ReviewedPostprint (published version

Demographic agent-based simulation of Gambians immigrants in Spain

Changes in our society have created a challenge for policymakers, who confront a need of tools to evaluate the possible effects of their policies. Agent-based modelling and simulation is a promising methodology which can be used in the study of population dynamics. In this paper we introduce an agent-based simulation approach to project the population of Gambian migrants in Spain during 10 years. Our approach not only enables to simulate the life course of individuals, but also allows deeping on the movements, interactions, and behaviours of the target population. The model is able to capture individual characteristics and to overcome some data-related limitations with assumptions on behavioural rules. With this methodology, we want to show the potential of the tool with the study of a real case scenario.Postprint (author's final draft

Parallel simulation of large population dynamics

Agent-based modeling and simulation is a promising methodology that can be used in the study of population dynamics. We present the design and development of a simulation tool which provides basic support for modeling and simulating agent-based demographic systems. Our results prove that agent-based modeling can work effectively in the study of demographic scenarios which can help to better policy planning and analysis. Moreover, parallel environment looks suitable for the study of large-scale individual-based simulations of this kind.Postprint (published version

Approaching simulation to modelers: a user interface for large-scale demographic simulation

Extended version / Versió extesaAgent-based modeling is one of the promising modeling tools that can be used in the study of population dynamics. Two of the main obstacles hindering the use of agent-based simulation in practice are its scalability when the analysis requires large-scale models such as policy studies, and its ease-of-use especially for users with no programming experience. While there has been a significant work on the scalability issue, ease-of-use aspect has not been addressed in the same intensity. This paper presents a graphical user interface designed for a simulation tool which allows modelers with no programming background to specify agent-based demographic models and run them on parallel environments. The interface eases the definition of models to describe individual and group dynamics processes with both qualitative and quantitative data. The main advantage is to allow users to transparently run the models on high performance computing infrastructures.Postprint (author's final draft