Archivio della ricerca di Triestehttps://arts.units.itIl sistema di repository digitale IRIS acquisisce, archivia, indicizza, conserva e rende accessibili prodotti digitali della ricerca.Sat, 28 Nov 2020 17:40:04 GMT2020-11-28T17:40:04Z10131Uncertainty budget of solid Earth data reductions to global gravity modelshttp://hdl.handle.net/11368/2951717Titolo: Uncertainty budget of solid Earth data reductions to global gravity models
Abstract: Solid Earth applications of satellite gravity models commonly involve some type of data reduction - i.e. forward
modelling the gravity effect of known mass distributions to isolate an anomaly from the observed field, which is
then attributed to the enquired phenomenon. The adopted "known masses" suffer from the uncertainties arising
from the non-modelled variance in the shape of geological bodies and the density distribution therein. These
uncertainties are propagated to the reduced gravity field, superimposed to the formal errors provided with the
gravity model. Given the different origin between formal errors of satellite global gravity models (GGM), arising
from observation and noise models, and the contribution of geophysical data reductions, we aimed at assessing
the comprehensive error characteristics of reduced-GGMs.
In order to do so, we computed a set of common reductions (topography, crustal layers, mantle inhomogeneities)
using a combination of spectral- and space-domain forward modelling. Uncertainties in the input
quantities (depths and densities) were propagated trough Monte Carlo methods.
Geometries were constrained by a topography-bedrock-ice model (Earth2014), by a global layered model of the
lithosphere (LITHO1.0), and by local higher detail models of the crust and sediments, where available. Depth
uncertainties, if not provided with the input data, were assigned according to method-specific assumptions. Estimates of density and its variance come from probability distributions fitted to literature data, from petrophysical
relationships (e.g. velocity-composition-temperature) and from worst-case assumptions where no sufficient data is
available.
We report the outcome of a set of global models, at a resolution and spectral content coherent with the
currently available satellite-only GGMs. We resort to global uncertainty maps and to the familiar representations
employed in GGM sensitivity assessments (e.g. degree error curves). Different combinations of data reductions
were applied, simulating the interest in different anomalies (e.g. by correcting either for the crust or the mantle).
Tue, 01 Jan 2019 00:00:00 GMThttp://hdl.handle.net/11368/29517172019-01-01T00:00:00ZUncertainity of satellite – gravity – derived Moho estimates : Contribution of data reductionshttp://hdl.handle.net/11368/2951724.1Titolo: Uncertainity of satellite – gravity – derived Moho estimates : Contribution of data reductions
Abstract: In the last years, the unparalleled spatial homogeneity provided by satellite-only global gravity models has been successfully exploited to obtain estimates on mass distribution in the solid Earth. Among these, the depth of the crust-mantle boundary (Mohorovicic discontinuity), has been a successful target of regional and global studies. Even when simplified to a sharp density discontinuity surface, its knowledge enables a reliable infill between terrestrial data, chiefly from seismic methods, and can be applied to the evaluation and comparison of different crustal models, at similar spatial scales.
Owing to the high degrees of GOCE-based GGMs, the theoretical resolving power can be estimated on the order of 0.1 km depth-wise, at less than 1 arc-degree of horizontal resolution. Such estimate assumes a perfectly isolated signal, i.e. no unmodelled masses in the data reductions, in a correctly constrained inversion (no unknown a-priori parameters, e.g. crust-mantle density contrast).
The Moho depth can be estimated from gravity data by solving the inverse problem relating the relief of a density discontinuity to the observed gravity field. This problem requires two input parameters, a density contrast and a reference depth; it is also necessary to isolate the signal due to Moho relief from all other contributions to the gravity field.
Input parameters are usually constrained by seismic data. Data reductions, applied to isolate a "residual anomaly", commonly consists in the forward-modelled effect of topography, of masses both above (e.g. sediments, upper crustal boundaries), and below the crust-mantle boundary (e.g. lateral density variations in the mantle).
Any variance in the input densities and geometries used in the data reduction, if not accounted for, and any uncertainty in the adopted constraints, is mapped in the inversion results, and thus propagated in any subsequent modelling that makes use of crustal thickness (e.g. temperature, rheology, velocity corrections). An uncertainty estimate is now commonly distributed alongside Moho depth models.
Starting from the theoretical Moho depth-error estimate, obtained from formal errors in the global gravity model, we compute the uncertainty effect that each data reduction step adds to this estimate. The gravity uncertainty is then propagated to a depth estimate using a reference inversion operator. This provides a quantitative assessment of the suitability of satellite-only GGMs in detecting Moho features, at different wavelengths, in a realistic geophysical framework. It also highlights where improvement in critical parameters would be more rewarding in terms of uncertainty reduction.
Up to degree and order 280, the cumulative reduction uncertainty can exceed 200 mGal, in terms of gravity anomaly. This results in local Moho depth uncertainties in the order of 10 km. A 10 points percent simulated improvement in the sediment thickness error improves the Moho depth uncertainty range by up to 1 km. This indicates that even slight improvements, such as the harmonisation of existing near-surface data, can pay off in terms of quality of gravity inversion estimates.
Tue, 01 Jan 2019 00:00:00 GMThttp://hdl.handle.net/11368/2951724.12019-01-01T00:00:00ZError Characteristics of Satellite-only Global Gravity Models after Solid Earth Data Reductionshttp://hdl.handle.net/11368/2951678.1Titolo: Error Characteristics of Satellite-only Global Gravity Models after Solid Earth Data Reductions
Abstract: The spatial homogeneity provided by satellite-only gravity models has been successfully exploited to probe the lithosphere density structure and its related quantities (e.g. composition and temperature). Compared with other observables, these models provide an unparalleled spatial coverage, which comes with the price of lower resolution.
Geophysical applications of gravity products start with data reduction, stripping the gravity effect of "known masses" to isolate an anomalous field. Uncertainties in the reductions, which rely on a-priori data, accumulate in the anomaly and are non-trivially propagated to the inversion results. The static spatial distribution of mass in the lithosphere is responsible for a large part of the observed signal, well above the sensitivity of the products. At the same time, the uncertainties in reductions can reach the same magnitude as the enquired source.
We aimed at providing an error estimate for solid Earth applications, in the form of error curves "after reduction", in the spectral domain, and maps of the spatial distribution of uncertainty. We computed a set of reductions for crustal and mantle inhomogeneities. Uncertainties in the input quantities were propagated trough Monte Carlo methods. Depth uncertainties, if not provided with the input data, were assigned according to method-specific assumptions. Estimates of density and its variance come from distributions fitted to literature data, from petrophysics, and from worst-case assumptions where no data is available. We report the results of these tests globally. Simulated improvements in the input data show how slight improvements in quality would pay off in terms of error reduction.
Tue, 01 Jan 2019 00:00:00 GMThttp://hdl.handle.net/11368/2951678.12019-01-01T00:00:00ZGOCE and future gravity missions for geothermal energy exploitationhttp://hdl.handle.net/11368/2883174Titolo: GOCE and future gravity missions for geothermal energy exploitation
Abstract: Geothermal energy is a valuable renewable energy source the exploitation of which contributes to the worldwide reduction of consumption of fossil fuels oil and gas. The exploitation of geothermal energy is facilitated where the thermal gradient is higher than average leading to increased surface heat flow. Apart from the hydrologic circulation properties which depend on rock fractures and are important due to the heat transportation from the hotter layers to the surface, essential properties that increase the thermal gradient are crustal thinning and radiogenic heat producing rocks. Crustal thickness and rock composition form the link to the exploration with the satellite derived gravity field, because both induce subsurface mass changes that generate observable gravity anomalies. The recognition of gravity as a useful investigation tool for geothermal energy lead to a cooperation with ESA and the International Renewable Energy Agency (IRENA) that included the GOCE derived gravity field in the online geothermal energy investigation tool of the IRENA database. The relation between the gravity field products as the free air gravity anomaly, the Bouguer and isostatic anomalies and the heat flow values is though not straightforward and has not a unique relationship. It is complicated by the fact that it depends on the geodynamical context, on the geologic context and the age of the crustal rocks. Globally the geological context and geodynamical history of an area is known close to everywhere, so that a specific known relationship between gravity and geothermal potential can be applied. In this study we show the results of a systematic analysis of the problem, including some simulations of the key factors. The study relies on the data of GOCE and the resolution and accuracy of this satellite. We also give conclusions on the improved exploration power of a gravity mission with higher spatial resolution and reduced data error, as could be achieved in principle by flying an atom interferometer sensor on board a satellite.
Fri, 01 Jan 2016 00:00:00 GMThttp://hdl.handle.net/11368/28831742016-01-01T00:00:00ZInferring the lithospheric thermal structure from satellite gravimetryhttp://hdl.handle.net/11368/2961201Titolo: Inferring the lithospheric thermal structure from satellite gravimetry
Fri, 20 Mar 2020 00:00:00 GMThttp://hdl.handle.net/11368/29612012020-03-20T00:00:00ZConstraining the continental crust radioactive heat production with satellite-derived gravity models : revisiting the linear relationshiphttp://hdl.handle.net/11368/2916569Titolo: Constraining the continental crust radioactive heat production with satellite-derived gravity models : revisiting the linear relationship
Sun, 01 Jan 2017 00:00:00 GMThttp://hdl.handle.net/11368/29165692017-01-01T00:00:00ZConstraining the continental crust radioactive heat production with satellite -derived gravity models : revisiting the linear relationshiphttp://hdl.handle.net/11368/2912751Titolo: Constraining the continental crust radioactive heat production with satellite -derived gravity models : revisiting the linear relationship
Sun, 01 Jan 2017 00:00:00 GMThttp://hdl.handle.net/11368/29127512017-01-01T00:00:00ZLa gravimetria da satellite come vincolo nelle stime di flusso di calore : primi risultatihttp://hdl.handle.net/11368/2904582Titolo: La gravimetria da satellite come vincolo nelle stime di flusso di calore : primi risultati
Abstract: Un confronto tra modelli globali di gravità (quali quelli ottenuti dai dati del satellite GOCE) e mappe di flusso di calore in superficie -due osservabili geofisiche non legate da semplici leggi- suggerisce un legame tra anomalia di Bouguer e diversi regimi di trasporto del calore.
In un quadro finalizzato a valutare quanto sia possibile quantificare in maniera rigorosa tale relazione, abbiamo verificato come un semplice modello in cui valga una relazione diretta spessore crostale - produzione radiogenica di calore in crosta continentale possa essere utilizzato per stimare la componente di flusso sub-continentale.
A causa dei vincoli logistici ed economici associati alle misure dirette del flusso di calore, la distribuzione di queste non è omogenea: in particolare è presente un bias verso i flussi elevati, associato all'interesse per lo sfruttamento della risorsa geotermica ad alta entalpia. Persistono aree prive di misure anche in zone non remote dell'Europa centro-occidentale. Compensare questi vuoti d'informazione tramite interpolazione può comportare la sovrastima dell'estensione delle zone ad alto flusso.
Una possibile strategia per ovviare a ciò è la separazione tra componenti di flusso a diverse profondità, con l'obiettivo di isolare le componenti più profonde (rappresentate dal flusso attraverso la base della crosta), alla quale sono associate lunghezze caratteristiche delle anomalie termiche misurate in superficie maggiori rispetto a quelle dovute a strutture più localizzate.
Otteniamo questo tramite una strategia di backstripping, stimando la componente crostale del flusso con la profondità di due interfacce crostali, usate come fattore di scala, ottenute tramite inversione del dato di gravità. Il risultato è una mappa di flusso a scala regionale (risoluzione di circa 100 km), che presentiamo in un area studio (includente Alpi e bacini adiacenti, massiccio renano, Graben del Reno), confrontandola col risultato di un'interpolazione non vincolata. Questo prodotto, meno suscettibile all'influenza di fenomeni locali, ha permesso di isolare i fattori e le criticità su cui andrà indirizzata una più sofisticata modellazione.
Fri, 01 Jan 2016 00:00:00 GMThttp://hdl.handle.net/11368/29045822016-01-01T00:00:00ZParameter sensitivity in satellite-gravity-constrained geothermal
modellinghttp://hdl.handle.net/11368/2904592Titolo: Parameter sensitivity in satellite-gravity-constrained geothermal
modelling
Abstract: The use of satellite gravity data in thermal structure estimates require identifying the factors that affect the gravity
field and are related to the thermal characteristics of the lithosphere.
We propose a set of forward-modelled synthetics, investigating the model response in terms of heat flow, temperature,
and gravity effect at satellite altitude. The sensitivity analysis concerns the parameters involved, as heat
production, thermal conductivity, density and their temperature dependence.
We discuss the effect of the horizontal smoothing due to heat conduction, the superposition of the bulk thermal
effect of near-surface processes (e.g. advection in ground-water and permeable faults, paleoclimatic effects,
blanketing by sediments), and the out-of equilibrium conditions due to tectonic transients. All of them have the
potential to distort the gravity-derived estimates.We find that the temperature-conductivity relationship has a small
effect with respect to other parameter uncertainties on the modelled temperature depth variation, surface heat flow,
thermal lithosphere thickness.
We conclude that the global gravity is useful for geothermal studies.
Sun, 01 Jan 2017 00:00:00 GMThttp://hdl.handle.net/11368/29045922017-01-01T00:00:00ZGeothermal estimates from GOCE data alone: assessment of feasibility
and first resultshttp://hdl.handle.net/11368/2898380Titolo: Geothermal estimates from GOCE data alone: assessment of feasibility
and first results
Abstract: The characteristics of the available global gravity models derived from satellite gravity suggest that they could be
applied in modelling the downward continuation of the temperature field at a continental scale.
To obtain this, we quantified how and to which extent the mass distribution that we can obtain from inverse modelling
of gravity can be linked to the factors affecting the temperature field, such as the radiogenic heat production
and the thermal conductivity of rocks.
Since there is no direct physical law linking the two fields, we resort to a reference lithosphere, built up on a set of
lithological parameters –including their associated uncertainties.
A central and most critical assumption is that the crustal heat production can be tied to crustal thickness, a relationship
which strength shows extreme variability in different geodynamic domains. We take this into account,
including it as a parameter uncertainty and propagating it to the results.
Pursuing the search for a reliable method to isolate the component of the heat flow due to the crustal heat production
from the available measurements, we test this framework on the go_cons_gcf_2_tim_r5 release of the
GOCE-derived field.
We so obtain a satisfactory distinction between different heat transport domains (dominated by heat production,
conduction from the mantle, or shallow plays), which proved helpful in interpolating regional heat flow maps at
the resolution of the gravity data (about 140 km).
Sun, 01 Jan 2017 00:00:00 GMThttp://hdl.handle.net/11368/28983802017-01-01T00:00:00Z