Construction of an integrated seismic-geological model of the East Siberian Sea shelf

2018 ◽  
pp. 30-34
Author(s):  
A.B. Popova ◽  
◽  
O.S. Makhova ◽  
N.A. Malyshev ◽  
V.E. Verzhbitskiy ◽  
...  
Keyword(s):  
Geological Model ◽  
East Siberian Sea

The Geosciences Applied to Lunar Exploration

1962 ◽  
Vol 14 ◽  
pp. 169-257 ◽  
Author(s):  
J. Green
Keyword(s):  
Lunar Surface ◽  
Probable Mechanism ◽  
Point Of View ◽  
Lunar Exploration ◽  
Geological Model ◽  
Apply Geophysics ◽  
Surface Features ◽  
The Impact

The term geo-sciences has been used here to include the disciplines geology, geophysics and geochemistry. However, in order to apply geophysics and geochemistry effectively one must begin with a geological model. Therefore, the science of geology should be used as the basis for lunar exploration. From an astronomical point of view, a lunar terrain heavily impacted with meteors appears the more reasonable; although from a geological standpoint, volcanism seems the more probable mechanism. A surface liberally marked with volcanic features has been advocated by such geologists as Bülow, Dana, Suess, von Wolff, Shaler, Spurr, and Kuno. In this paper, both the impact and volcanic hypotheses are considered in the application of the geo-sciences to manned lunar exploration. However, more emphasis is placed on the volcanic, or more correctly the defluidization, hypothesis to account for lunar surface features.

High-resolution geological model of the gravitational deformation affecting the western slope of Mt. Epomeo (Ischia)

2015 ◽  
Vol 35 ◽  
pp. 104-108
Author(s):  
Marta Della Seta ◽  
Carlo Esposito ◽  
Gian Marco Marmoni ◽  
Salvatore Martino ◽  
Antonella Paciello ◽  
...  
Keyword(s):  
High Resolution ◽  
Western Slope ◽  
Geological Model ◽  
Gravitational Deformation

The CO2CRC Otway Shallow CO2 Controlled Release Experiment: Geological Model and CO2 Migration Simulations

2019 ◽  
Author(s):  
Andrew Feitz ◽  
Bruce Radke ◽  
Md. Shahadat Hossain ◽  
Brett Harris ◽  
Ralf Schaa ◽  
...  
Keyword(s):  
Controlled Release ◽  
Geological Model ◽  
Release Experiment

A 3-D GEOLOGICAL MODEL OF THE RATTLESNAKE RIDGE LARAMIDE FOLD, WYOMING

2016 ◽  
Author(s):  
Schuyler T. Robinson ◽  
◽  
Robert W. Clayton
Keyword(s):  
Geological Model

Tectonic insight and 3-D modelling of the Lusi (Java, Indonesia) mud edifice through gravity analyses

2021 ◽  
Vol 225 (2) ◽  
pp. 984-997
Author(s):  
Álvaro Osorio Riffo ◽  
Guillaume Mauri ◽  
Adriano Mazzini ◽  
Stephen A Miller
Keyword(s):  
Risk Mitigation ◽  
Bouguer Anomaly ◽  
Geological Model ◽  
Resource Exploitation ◽  
Subsurface Structures ◽  
Central Java ◽  
Geostatistical Interpolation ◽  
Gravity Response ◽  
Anomaly Map ◽  
Bouguer Anomaly Map

SUMMARY Lusi is a sediment-hosted hydrothermal system located near Sidoarjo in Central Java, Indonesia, and has erupted continuously since May 2006. This mud eruption extends over a surface of ∼7 km2, and is framed by high containment dams. The present study investigates the geometry of the subsurface structures using a detailed gravimetric model to visualize in 3-D the Lusi system and surrounding lithologies. The obtained residual Bouguer anomaly map, simulated through geostatistical interpolation methods, supports the results of previous deformation studies. The negative gravity anomaly zones identified at Lusi are interpreted as fractured areas through which fluids can ascend towards the surface. A 3-D detailed geological model of the area was constructed with Geomodeller™ to highlight the main features. This model relies on the structures’ density contrasts, the interpreted residual Bouguer anomaly map, and geological data from previous authors. 3-D algorithms were used to calculate the gravity response of the model and validate it by inverse methods. The final output is a gravity constrained 3-D geological model of the Lusi mud edifice. These results provide essential details on the Lusi subsurface and may be useful for possible future geothermal resource exploitation and for the risk mitigation plans related to the maintenance of the man-made framing embankment.

scholarly journals Model-Based Probabilistic Inversion Using Magnetic Data: A Case Study on the Kevitsa Deposit

Geosciences ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 150
Author(s):  
Nilgün Güdük ◽  
Miguel de la Varga ◽  
Janne Kaukolinna ◽  
Florian Wellmann
Keyword(s):  
Structural Parameters ◽  
Rock Properties ◽  
Magnetic Data ◽  
Geological Model ◽  
Borehole Data ◽  
Likelihood Functions ◽  
Different Types ◽  
Geophysical Information ◽  
Different Sources

Structural geological models are widely used to represent relevant geological interfaces and property distributions in the subsurface. Considering the inherent uncertainty of these models, the non-uniqueness of geophysical inverse problems, and the growing availability of data, there is a need for methods that integrate different types of data consistently and consider the uncertainties quantitatively. Probabilistic inference provides a suitable tool for this purpose. Using a Bayesian framework, geological modeling can be considered as an integral part of the inversion and thereby naturally constrain geophysical inversion procedures. This integration prevents geologically unrealistic results and provides the opportunity to include geological and geophysical information in the inversion. This information can be from different sources and is added to the framework through likelihood functions. We applied this methodology to the structurally complex Kevitsa deposit in Finland. We started with an interpretation-based 3D geological model and defined the uncertainties in our geological model through probability density functions. Airborne magnetic data and geological interpretations of borehole data were used to define geophysical and geological likelihoods, respectively. The geophysical data were linked to the uncertain structural parameters through the rock properties. The result of the inverse problem was an ensemble of realized models. These structural models and their uncertainties are visualized using information entropy, which allows for quantitative analysis. Our results show that with our methodology, we can use well-defined likelihood functions to add meaningful information to our initial model without requiring a computationally-heavy full grid inversion, discrepancies between model and data are spotted more easily, and the complementary strength of different types of data can be integrated into one framework.

scholarly journals Meso- and microscale sea-ice motion in the East Siberian Sea as determined from ERS-1 SAR Data

1999 ◽  
Vol 45 (150) ◽  
pp. 370-383 ◽  
Author(s):  
Kim Morris ◽  
Shusun Li ◽  
Martin Jeffries
Keyword(s):  
Time Series ◽  
Sea Ice ◽  
Large Scale ◽  
Vector Fields ◽  
Lateral Displacement ◽  
Motion Vector ◽  
Sar Interferometry ◽  
East Siberian Sea ◽  
Pack Ice ◽  
Sar Data

Abstract Synthetic aperture radar- (SAR-)derived ice-motion vectors and SAR interferometry were used to study the sea-ice conditions in the region between the coast and 75° N (~ 560 km) in the East Siberian Sea in the vicinity of the Kolyma River. ERS-1 SAR data were acquired between 24 December 1993 and 30 March 1994 during the 3 day repeat Ice Phase of the satellite. The time series of the ice-motion vector fields revealed rapid (3 day) changes in the direction and displacement of the pack ice. Longer-term (≥ 1 month) trends also emerged which were related to changes in large-scale atmospheric circulation. On the basis of this time series, three sea-ice zones were identified: the near-shore, stationary-ice zone; a transitional-ice zone;and the pack-ice zone. Three 3 day interval and one 9 day interval interferometric sets (amplitude, correlation and phase diagrams) were generated for the end of December, the begining of February and mid-March. They revealed that the stationary-ice zone adjacent to the coast is in constant motion, primarily by lateral displacement, bending, tilting and rotation induced by atmospheric/oceanic forcing. The interferogram patterns change through time as the sea ice becomes thicker and a network of cracks becomes established in the ice cover. It was found that the major features in the interferograms were spatially correlated with sea-ice deformation features (cracks and ridges) and major discontinuities in ice thickness.

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