Inversion methods and strategies to integrate multi-disciplinary geophysical data

  E-mail   Print

Topic Editor: Prof. Anibal Sosa

One major scientific target of many multidisciplinary research efforts in geosciences consists on advancing the understanding of the structure, dynamics, and evolution of the Earth. To accomplish this purpose analysis of individual geophysical and geological data sets has been traditional carry on, however it may lead to different models, mostly due to mischaracterization of errors and gaps in the information that each data set can provide. Most recently currently scientists around the world address the same problem by integrating distinct information sources in order to determine physical properties of the Earth. This special issue of AIMS Geosciences is dedicated to several aspects of state-of-the-art computing algorithmic tools and mathematical formulations for integrating data with varying accuracy and sensitivity.
Such approaches and methods are typically based on combining complimentary data sets since they are likely to reduce the ambiguity of inversion results and facilitate posterior interpretation. However, in spite of recent dramatic increases in computational power and improved techniques several computational challenges arise from multiscale character and complexity of the numerical models, which require sophisticated nonlinear and linear solver techniques. Some of these challenges are: what type of data can be considered complimentary?  How can we balance the influence of each data set in the inversion process? Is there any advantage on choosing between joint inversion, cooperative inversion, transdimensional inversion and other integrated inversion strategies? Is the associated uncertainty of the numerical simulations improved by these inversion methods?
This special issue will serve as a platform for innovative developments that include, but are not limited to address these grand challenges in inversion and seismic modeling. Also we welcome research using joint inversion or other approaches to combine different types of geophysical data that will advance our understanding of fundamental Earth processes and impact similar projects that collect or analyze large amounts of geophysical data. Also, studies that compare real-Earth model obtained using any of these methods, and assess repeatability, are particularly encouraged. Papers aimed at non-seismologists, that increase accessibility of the inverse problem formulations for non-seismological disciplines, are particularly welcomed.
Computational seismology, joint inversion,  multi-scale geophysical data, seismic imaging, inverse problems, numerical optimization.
Paper Submission:
Full text submission due date: 20th November 2015.
Full paper should be submitted online to the journal at
Before submission, authors should carefully read over the instruction for Authors which are located at

Lennox Thompson, Aaron A. Velasco, Vladik Kreinovich
AIMS Geosciences, 2016, 2(1): 63-87. doi: 10.3934/geosci.2016.1.63
+ Abstract     + HTML     + PDF(159077 KB)
C. Heining, M. Sellier
AIMS Geosciences, 2016, 2(1): 45-63. doi: 10.3934/geosci.2016.1.45
+ Abstract     + HTML     + PDF(3869 KB)
Paolo Dell’Aversana, Giancarlo Bernasconi, Fabio Chiappa
AIMS Geosciences, 2016, 2(1): 1-31. doi: 10.3934/geosci.2016.1.1
+ Abstract     + HTML     + PDF(2183 KB)
Open Access Journals
Open Access Journals