SHEMAT-Suite
SHEMAT-Suite-open

Repository



Open-source SHEMAT-Suite
SHEMAT-Suite (Simulator for HEat and MAss Transport) is a
numerical code for computing flow, heat and species transport
equations in porous media. The governing equations of the code are the
groundwater flow equation, the heat transport equation and the species
transport equation.
SHEMAT-Suite includes parameter estimation and data assimilation
approaches, both stochastic (Monte Carlo, ensemble Kalman filter) and
deterministic (Bayesian inversion using automatic differentiation for
calculating derivatives).
SHEMAT-Suite is written in Fortran-95.
SHEMAT-Suite uses finite-difference discretization on a Cartesian grid
with x, y, z coordinates and block centered nodes.  The system of
equations can be solved explicitly, implicitly or semi-implicitly.
More detailed information on the
equations

Installation
Guide to installing SHEMAT-Suite:
Installation

Tutorial
If you want to run SHEMAT-Suite for the first time you should check
the SHEMAT-Suite Tutorial.

For Developers
Fortran-95 styleguide for SHEMAT-Suite.
Doxygen documentation.

Most visited Wiki-pages
Input File
Compilation
Equations and Discretization

SHEMAT-Suite Wiki topics

Howtos: howtos

Property Modules: props

User Directories: user

Branches: branches


Outline of the directories in branch master


Important code developments of SHEMAT-Suite
Table: Important code developments of
SHEMAT-Suite.

(^{\mathrm{x}}) Functionalities not available in
the open-source package.
(*) Simplified functionality available in
the open-source package.
(**) SHEMAT-Suite functionality available
open-source, additional software required.\


Newly implemented functionality
Key Reference


Inverse parameter estimation based on automatic differentiation
Rath et al., 2006


Latent heat effects due to freezing and melting
Mottaghy and Rath, 2006


Monte Carlo techniques for uncertainty quantification and reduction
Vogt et al., 2010


Borehole heat exchanger module(*)
Mottaghy and Dijkshoorn, 2012


Shared-memory parallelization
Wolf, 2011


Data assimilation based on the ensemble Kalman Filter
Vogt et al., 2012


Multi-phase flow module using automatic differentiation (^{\mathrm{x}})
Büsing et al., 2014


Distributed-memory parallelization (^{\mathrm{x}})
Rostami and Bücker, 2014


Heat transfer model for plane thermo-active geotechnical systems(^{\mathrm{x}})
Kürten et al., 2014


Anisotropic flow module using the full permeability tensor (^{\mathrm{x}})
Chen et al., 2016


Supercritical water/steam module using automatic differentiation (^{\mathrm{x}})
Büsing et al., 2017


Optimal borehole positioning with respect to reservoir characterization via optimal experimental design (**)
Seidler et al., 2016


Halite precipitation model in porous sedimentary rock adjacent to salt diapirs(^{\mathrm{x}})
Li et al., 2017


Efficient two-phase flow in heterogeneous porous media using exact Jacobians (^{\mathrm{x}})
Büsing, 2020


Rath, V., Wolf, A., & Bücker, H. M., Joint three-dimensional
inversion of coupled groundwater flow and heat transfer based on
automatic differentiation: sensitivity calculation, verification,
and synthetic examples, Geophysical Journal International, 167(1),
453–466 (2006).  http://dx.doi.org/10.1111/j.1365-246x.2006.03074.x

Mottaghy, D., & Rath, V., Latent heat effects in subsurface heat
transport modelling and their impact on palaeotemperature
reconstructions, Geophysical Journal International, 164(1), 236–245
(2006).  http://dx.doi.org/10.1111/j.1365-246x.2005.02843.x

Vogt, C., Mottaghy, D., Wolf, A., Rath, V., Pechnig, R., & Clauser,
C., Reducing temperature uncertainties by stochastic geothermal
reservoir modelling, Geophysical Journal International, 181(1),
321–333 (2010).  http://dx.doi.org/10.1111/j.1365-246x.2009.04498.x

Mottaghy, D., & Dijkshoorn, L., Implementing an effective finite
difference formulation for borehole heat exchangers into a heat and
mass transport code, Renewable Energy, 45(), 59–71 (2012).
http://dx.doi.org/10.1016/j.renene.2012.02.013

Wolf, A., Ein softwarekonzept zur hierarchischen parallelisierung
von stochastischen und deterministischen inversionsproblemen auf
modernen ccnuma-plattformen unter nutzung automatischer
programmtransformation. (Doctoral dissertation) (2011). RWTH Aachen
University.
Vogt, C., Marquart, G., Kosack, C., Wolf, A., & Clauser, C.,
Estimating the permeability distribution and its uncertainty at the
egs demonstration reservoir soultz-sous-forêts using the ensemble
Kalman filter, Water Resources Research, 48(8), (2012).
http://dx.doi.org/10.1029/2011wr011673

Büsing, H., Willkomm, J., Bischof, C. H., & Clauser, C., Using
exact jacobians in an implicit newton method for solving multiphase
flow in porous media, International Journal of Computational
Science and Engineering, 9(5/6), 499 (2014).
http://dx.doi.org/10.1504/ijcse.2014.064535

Rostami, M. A., & H. M. Bücker, Preservation of non-uniform memory
architecture characteristics when going from a nested OpenMP to a
hybrid MPI/OpenMP approach, In M. S. Obaidat, J. Kacprzyk, &
T. Ören, SIMULTECH 2014, Proceedings of the 4th International
Conference on Simulation and Modeling Methodologies, Technologies
and Applications, Vienna, Austria, August~28--30, 2014
(pp. 286–291) (2014). : SciTePress.
Kürten, S., Mottaghy, D., & Ziegler, M., A new model for the
description of the heat transfer for plane thermo-active
geotechnical systems based on thermal resistances, Acta
Geotechnica, 10(2), 219–229 (2014).
http://dx.doi.org/10.1007/s11440-014-0311-6

Chen, T., Clauser, C., Marquart, G., Willbrand, K., & Büsing, H.,
Modeling anisotropic flow and heat transport by using mimetic
finite differences, Advances in Water Resources, 94(), 441–456
(2016).  http://dx.doi.org/10.1016/j.advwatres.2016.06.006

Büsing, H., Vogt, C., Ebigbo, A., & Klitzsch, N., Numerical study
on co2leakage detection using electrical streaming potential data,
Water Resources Research, 53(1), 455–469 (2017).
http://dx.doi.org/10.1002/2016wr019803

Seidler, R., Padalkina, K., Bücker, H. M., Ebigbo, A., Herty, M.,
Marquart, G., & Niederau, J., Optimal experimental design for
reservoir property estimates in geothermal exploration,
Computational Geosciences, 20(2), 375–383 (2016).
http://dx.doi.org/10.1007/s10596-016-9565-4

Li, S., Reuning, L., Marquart, G., Wang, Y., & Zhao, P., Numerical
model of halite precipitation in porous sedimentary rocks adjacent
to salt diapirs, Journal of Geophysics and Engineering, 14(5),
1160–1166 (2017).  http://dx.doi.org/10.1088/1742-2140/aa73f9

H. Büsing, Efficient solution techniques for two-phase flow in
heterogeneous porous media using exact Jacobians, Computational
Geosciences, In Review (2020).