Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Elvar K. Bjarkason"'
Autor:
Ryoichi Saito, Elvar K. Bjarkason, Norihiro Watanabe, Kazuya Ishitsuka, Yosuke Kobayashi, Tatsuya Kajiwara, Anna Suzuki, Hiroshi Asanuma, Yusuke Yamaya, T. Mogi, Takeshi Sugimoto
Publikováno v:
Natural Resources Research. 30:3289-3314
The temperature distribution at depth is a key variable when assessing the potential of a supercritical geothermal resource as well as a conventional geothermal resource. Data-driven estimation by a machine-learning approach is a promising way to est
Publikováno v:
Geothermics. 105:102480
Autor:
Takatoshi Ito, Markus O. Häring, Elvar K. Bjarkason, Michael Fehler, Hiroshi Asanuma, Yusuke Mukuhira
Variability in the b-value, which describes the frequency distribution of earthquake magnitudes, is usually attributed to variations in differential stress in the setting of natural and labo...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::89657d4c4f6ee728865b30eda8856109
https://doi.org/10.1002/essoar.10507492.1
https://doi.org/10.1002/essoar.10507492.1
Publikováno v:
Geothermics. 78:85-100
The application of the adjoint and direct methods to inverse modeling of the natural state of a convective geothermal system is discussed. The methods have been applied to other subsurface modeling problems, but they have seldom been used in the geot
Publikováno v:
The Proceedings of the Materials and Mechanics Conference. 2022:GS0208
Autor:
Elvar K. Bjarkason, Oliver J. Maclaren, Michael O'Sullivan, Ruanui Nicholson, John O'Sullivan
Publikováno v:
Water Resources Research. 56
We consider geothermal inverse problems and uncertainty quantification from a Bayesian perspective. Our main goal is to make standard, `out-of-the-box' Markov chain Monte Carlo (MCMC) sampling more feasible for complex simulation models by using suit
Publikováno v:
Water Resources Research. 54:2376-2404
The Levenberg-Marquardt (LM) method is commonly used for inverting models used to describe geothermal, groundwater, or oil and gas reservoirs. In previous studies LM parameter updates have been made tractable for highly parameterized inverse problems
Publikováno v:
The Proceedings of Conference of Tohoku Branch. :123
Autor:
Elvar K. Bjarkason
This paper describes practical randomized algorithms for low-rank matrix approximation that accommodate any budget for the number of views of the matrix. The presented algorithms, which are aimed at being as pass efficient as needed, expand and impro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::390f70cd8e27b3a736b57cb7d68ed0f7