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The reactivation of faults and the generation of fractures can be caused by stress changes due to injection and/or production of fluids into and/or from the subsurface. The simulation of these processes, which could be associated with (micro-)seismicity, is affected by a high uncertainty. The aim of this work is at developing a mathematical framework to quantify and possibly reduce the prior modeling uncertainties by assimilation of seismic data. The mechanics of fault (re-)activation is simulated by a Finite Element (FE) numerical model where the discontinuous displacements between the fault surfaces are suitably considered using appropriate Interface Elements (IEs). The study is carried out by using a stochastic approach, with a global sensitivity analysis (gSA) based on Sobol' indices initially performed to estimate the influence of the input parameters on the model solution. Then, a Markov Chain Monte Carlo (MCMC) sampling technique based on the generalized Polynomial Chaos expansion (gPC) surrogate solution is used to update the prior information conditioned on seismic observations. The methodology is tested on a 3D synthetic test case. The uncertain input is the natural stress regime and the Mohr-Coulomb parameters characterizing the fault activation criterion. A good reduction of the prior uncertainty is obtained, showing that the assimilation of seismic data can have a promising potential for improving the subsurface characterization. [ABSTRACT FROM AUTHOR]

Geomechanical modelling of the processes associated to the exploitation of subsurface resources, such as land subsidence or triggered/induced seismicity, is a common practice of major interest. The prediction reliability depends on different sources of uncertainty, such as the parameterization of the constitutive model characterizing the deep rock behaviour. In this study, we focus on a Sobol'-based sensitivity analysis and uncertainty reduction via assimilation of land deformations. A synthetic test case application on a deep hydrocarbon reservoir is considered, where land settlements are predicted with the aid of a 3-D Finite Element (FE) model. Data assimilation is performed via the Ensemble Smoother (ES) technique and its variation in the form of Multiple Data Assimilation (ES-MDA). However, the ES convergence is guaranteed with a large number of Monte Carlo (MC) simulations, that may be computationally infeasible in large scale and complex systems. For this reason, a surrogate model based on the generalized Polynomial Chaos Expansion (gPCE) is proposed as an approximation of the forward problem. This approach allows to efficiently compute the Sobol' indices for the sensitivity analysis and greatly reduce the computational cost of the original ES and MDA formulations, also enhancing the accuracy of the overall prediction process. [ABSTRACT FROM AUTHOR]

The Vietnamese Mekong Delta was formed by rapid transgression during the second half of the Holocene by deposition of mainly unconsolidated, fine-grained (clayey) sediments undergoing high compaction rates. The natural subsidence can seriously impact the already vulnerable delta plain as its low elevation exposes the delta to global sea level rise, flooding, salinization. Human activities such as groundwater pumping, infrastructural loading, sand mining and dam construction have exacerbated the effects of natural consolidation. Here we present a novel modeling study that has allowed to reproduce the formation and evolution of the Mekong delta over the past 4000 years. Using an adaptive finite-element mesh, the model properly simulates accretion and natural consolidation characterizing the delta evolution. Large soil grain motion and the delayed dissipation of pore-water overpressure are accounted for. We find that natural compaction of Holocene deposits following delta evolution exceeds predicted values of absolute sea level rise. The unprecedented high rates (up to ~20 mm/yr) threaten the lower delta plain with permanent inundation and inevitably reduce the designed service life of flood defense structures along the coast. Total subsidence and sediment delivery to the delta plain will determine its future elevation and vulnerability to relative sea level rise. [ABSTRACT FROM AUTHOR]

Aseisimic earth fissures are complex consequences of groundwater withdrawal and natural hydrogeologic conditions. This paper aims to improve the understanding of the mechanism of earth fissuring and investigate the relative importance of various factors to fissure activity, including bedrock geometry, piezometric depletion, compressibility and thickness of the exploited aquifer. For these purposes, a test case characterized by an impermeable and incompressible rock ridge in a subsiding basin is developed, where stress/displacement analyses and fissure state are predicted using an interface-finite element model. Three different methods for global sensitivity analysis are used to quantify the extent of the fissure opening to the aforementioned factors. The conventional sampling based Sobol' sensitivity analysis is compared to two surrogate based methods, the general polynomial chaos expansion based Sobol' analysis and a feature importance evaluation of a gradient boosting decision tree model. Numerical results indicate that earth fissure is forming in response to tensile stress accumulation above the ridge associated to pore-pressure depletion, inducing the fissure opening at land surface with further downward propagation. Sensitivity analysis highlights that the geometry of bedrock ridge is the most influential feature. Specifically, the fissure grows more when the ridge is steeper and closer to the land surface. Pore pressure depletion is a secondary feature and required to reach a certain threshold to activate the fissure. As for this specific application, the gradient boosting tree is the most suitable method for its better performance in capturing fissure characteristics. [ABSTRACT FROM AUTHOR]

Anthropogenic land subsidence can be evaluated and predicted by numerical models, which are often built over deterministic analyses. However, uncertainties and approximations are present, as in any other modeling activity of real-world phenomena. This study aims at combining data assimilation techniques with a physically-based numerical model of anthropogenic land subsidence in a novel and comprehensive workflow, to overcome the main limitations concerning the way traditional deterministic analyses use the available measurements. The proposed methodology allows to reduce uncertainties affecting the model, identify the most appropriate rock constitutive behavior and characterize the most significant governing geomechanical parameters. The proposed methodological approach has been applied in a synthetic test case representative of the Upper Adriatic basin, Italy. The integration of data assimilation techniques into geomechanical modeling appears to be a useful and effective tool for a more reliable study of anthropogenic land subsidence. [ABSTRACT FROM AUTHOR]

• Unraveling the elastic and inelastic components of deformation and hydraulic head. • Quantifying the elastic and inelastic parameters at different depths. • The storage parameters are obviously correlated with the depth and lithology. • The percentage of permanent storage volume loss is estimated. Land subsidence is a geological process mainly caused by groundwater overdraft. Numerical modeling of land subsidence is the main method used for its simulation and prediction. The elastic skeletal storage coefficient (S ke), inelastic skeletal storage coefficient (S kv), and the related specific values (S ske and S skv) are fundamental parameters to quantify land subsidence. In this paper, a novel approach integrating fast independent component analysis (Fast-ICA) with variable preconsolidation head decomposition method is proposed to disentangle S ske and S skv at various depth and over time from piezometric and extensometer records. The proposed method is applied to areas affected by severe land subsidence in the North China Plain (Tianzhu, Pinggezhuang and Cangzhou stations). The elastic and inelastic parameters of the aquifer systems are quantified at different depths. It is found that S ske and S skv decrease with depth. The finer the sediment grain size is, the smaller of the ratio S ske / S skv . Moreover, S ke remains almost unchanged over time, while S kv decreases as compaction and land subsidence increase. [ABSTRACT FROM AUTHOR]

A Correction to this paper has been published: https://doi.org/10.1007/s10596-021-10079-6 [ABSTRACT FROM AUTHOR]

• A new methodology by coupling 3D hydro-mechanical models and A-DInSAR data. • Model catches pumping-induced aquifer drawdown and deformations. • Time-lag between pressure change and deformation is detected by wavelet analysis. • The procedure is tested in the strategic water resource of Madrid (Spain) • Madrid aquifer response to aquifer extraction/recovery is fast. A novel methodological approach to calibrate and validate three-dimensional (3D) finite element (FE) groundwater flow and geomechanical models has been implemented using Advanced Differential Interferometric SAR (A-DInSAR) data. In particular, we show how A-DInSAR data can be effectively used to (1) constrain the model set-up in evaluating the areal influence of the wellfield and (2) characterise the aquifer system, specifically the storage coefficient values, which represents a fundamental step in managing groundwater resources. The procedure has been tested to reconstruct the surface vertical and horizontal movements caused by the Manzanares-Jarama wellfield located northwest of Madrid (Spain). The wellfield was used to supply freshwater during major droughts over the period between 1994 and 2010. Previous A-DInSAR outcomes obtained by ERS-1/2 and ENVISAT acquisitions clearly revealed the seasonality of the land displacements associated to the withdrawal and recovery cycles that characterized the wellfield development. A time-lag of about one month, which is in the order of the time span between two SAR acquisitions, between the hydraulic head changes and the displacements has been detected in this site by a wavelet analysis of A-DInSAR and piezometer time series. The negligible delay between the forcing factor and the system response and the complete subsidence recovery when piezometric head recovers supported the understanding of a minor role played by the pore pressure propagation within clay layers and the almost perfectly elastic behavior of the system (viscosity is negligible), respectively. The developed geomechanical model satisfactorily reproduces the pumping-induced deformations with a Root Mean Square Error (RMSE) between observed and simulated land displacements in the order of 0.1–0.3 mm. The results give insights about the approach benefits in deeply understanding the spatio-temporal aquifer-system response to the management of this strategic water resource for Madrid. [ABSTRACT FROM AUTHOR]

• The numerical solution of the prediction of long-term dynamics of transitional environments. • Application of the Virtual Element Method. • Coarsening strategy applied to avoid a large number of discretization elements. The prediction of long-term dynamics of transitional environments, e.g., lagoon evolution, salt-marsh growth or river delta progradation, is an important issue to estimate the potential impacts of different scenarios on such vulnerable intertidal morphologies. The numerical simulation of the combined accretion and consolidation, i.e., the two main processes driving the dynamics of these environments, however, suffers from a significant geometric non-linearity, which may result in a pronounced grid distortion using standard grid-based discretization methods. The present work describes a novel numerical approach, based on the Virtual Element Method (VEM), for the long-term simulation of the vertical dynamics of transitional landforms. The VEM is a grid-based variational technique for the numerical discretization of Partial Differential Equations (PDEs) allowing for the use of very irregular meshes consisting of a free combination of different polyhedral elements. The model solves the groundwater flow equation, coupled to a geomechanical module based on Terzaghi's principle, in a large-deformation setting, taking into account both the geometric and the material non-linearity. The use of the VEM allows for a great flexibility in the element generation and management, avoiding the numerical issues connected with the adoption of strongly distorted meshes. The numerical model is developed, implemented and tested in real-world examples, showing an interesting potential for addressing complex environmental situations. [ABSTRACT FROM AUTHOR]