$\mathbf{\mathbb{E}^{FWI}}$: Multi-parameter Benchmark Datasets for Elastic Full Waveform Inversion of Geophysical Properties
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Abstract:
Elastic geophysical properties (such as P- and S-wave velocities) are of great importance to various subsurface applications like CO$_2$ sequestration and energy exploration (e.g., hydrogen and geothermal). Elastic full waveform inversion (FWI) is widely applied for characterizing reservoir properties. In this paper, we introduce $\mathbf{\mathbb{E}^{FWI}}$, a comprehensive benchmark dataset that is specifically designed for elastic FWI. $\mathbf{\mathbb{E}^{FWI}}$ encompasses 8 distinct datasets that cover diverse subsurface geologic structures (flat, curve, faults, etc). The benchmark results produced by three different deep learning methods are provided. In contrast to our previously presented dataset (pressure recordings) for acoustic FWI (referred to as OpenFWI), the seismic dataset in $\mathbf{\mathbb{E}^{FWI}}$ has both vertical and horizontal components. Moreover, the velocity maps in $\mathbf{\mathbb{E}^{FWI}}$ incorporate both P- and S-wave velocities. While the multicomponent data and the added S-wave velocity make the data more realistic, more challenges are introduced regarding the convergence and computational cost of the inversion. We conduct comprehensive numerical experiments to explore the relationship between P-wave and S-wave velocities in seismic data. The relation between P- and S-wave velocities provides crucial insights into the subsurface properties such as lithology, porosity, fluid content, etc. We anticipate that $\mathbf{\mathbb{E}^{FWI}}$ will facilitate future research on multiparameter inversions and stimulate endeavors in several critical research topics of carbon-zero and new energy exploration. All datasets, codes and relevant information can be accessed through our website at https://efwi-lanl.github.io/Keywords:
Benchmark (surveying)
Lithology
Lahendong geothermal field is located in the northern part of Sulawesi island. The first exploration stage was started in the early 70’s. Numerous geophysical investigation were carried out such as Gravity, Magneto Telluric (MT), Resistivity and Mise-a-lamasse (MAM) methods. However, the precise geothermal boundary is not identified clearly. This paper will emphasize on geophysical data processing in determining the geothermal boundary at Lahendong area. In geothermal exploration, which use several geophysical methods, no single method can give satisfactory result in featuring the subsurface geometry. Therefore, we have to integrate all of the acquired geophysical data to get a realistic model for the studied geothermal field. The Lahendong geothermal field reality is unique, consequently our geophysical model parameter must be inferred from this unique realization. This paper, we demonstrated the advantage of integration the geological and geophysical data of Lahendong area. Knowledge of geology in the prospective area is fundamental to develop a correct model of the geothermal reservoir. Development of the geothermal models is an iterative process.
Geothermal exploration
Exploration geophysics
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P206 PECULIARITIES OF THE GEOTHERMAL FIELD AT THE DEPTH OF MEDITERRANEAN ALPINE FOLDED BELT IN ALBANIDES EXAMPLE 1 In the paper are presented the geothermal regime of the Albanides which represent an important part of Mediterranean Alpine Folded Belt. The geological factors that condition this geothermal regime are analyzed too. Introduction Geothermal studies in Albania during the 1989-2004 years period were performed in the framework of Atlas of the Geothermal Resources in Albania (1997) Geothermal Atlas of Europe (1992) and Atlas of the Geothermal Resources in Europe (1996). Geothermal studies were based on the temperature logs in the 137 deep
Geothermal exploration
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